Specialty Sections From CHEST® Physician

Cardiogenic shock (CS) is being recognized more often in critically ill patients. This increased prevalence is likely due to a better understanding of CS and the benefit of improving cardiac output (CO) to ensure adequate oxygen delivery (DO₂). There is no one specific definition of CS; rather, CS describes a clinical condition in which a patient is suffering from cellular hypoperfusion due to an ineffective CO with normal or elevating intravascular filling pressures.

CS is often, but not always, caused by a cardiac dysfunction. The heart is not able to provide adequate DO₂ to the tissues. Hypoperfusion ensues. The body attempts to compensate for the poor perfusion by increasing heart rate, vasoconstriction, and shunting blood flow to vital organs. These compensatory mechanisms worsen perfusion by increasing myocardial ischemia which further worsens cardiac dysfunction. This is known as the downward spiral of CS (Ann Intern Med. 1999 Jul 6;131[1]).

There is a number of different etiologies for CS. Historically, acute myocardial infarctions (AMI) was the most common cause. In the last 20 years, AMI-induced CS has become less prevalent due to more aggressive reperfusion strategies. CS due to etiologies such as cardiomyopathy, myocarditis, right ventricle failure, and valvular pathologies have become more common. While the overarching goal is to restore DO₂ to the tissue, the optimal treatment may differ based on the etiology of the CS. The Society for Cardiovascular Angiography and Intervention (SCAI) published CS classification stages in 2019 and then updated the stages 2022 (J Am Coll Cardiol. 2022 Mar 8;79[9]:933-46). In addition to the stages, there is now a three-axis model to address risk stratification. These classifications are a practically means of identifying and treating patients presenting with or concern for acute CS.

Stage A (At Risk) patients are not experiencing CS, but they are the at risk population. The patient’s hemodynamics, physical exam, and markers of hypoperfusion are normal. Stage A includes patients who have had a recent AMI or have heart failure.

Stage B (Beginning) patients have evidence of hemodynamic instability but are able to maintain tissue perfusion. These patients will have true or relative hypotension or tachycardia (in an attempt to maintain CO). Distal perfusion is adequate, but signs of ensuing decompensation (eg, elevated jugular venous pressure [JVP]) are present. Lactate is <2.0 mmol/L. Clinicians must be vigilant and treat these patients aggressively, so they do not decompensate further. It can be difficult to identify these patients because their blood pressure may be “normal,” but upon investigation, the blood pressure is actually a drop from the patient’s baseline.

Chronic heart failure patients with a history of depressed cardiac function will often have periods of cardiac decompensation between stages A and B. These patients are able to maintain perfusion for longer periods of time before further decompensation with hypoperfusion. If and when they do decompensate, they will often have a steep downward trajectory, so it is advantageous to the patient to be aggressive early.

Stage C (Classic) patients have evidence of tissue hypoperfusion. While these patients will often have true or relative hypotension, it is not a definition of stage C. These patients have evidence of volume overload with elevated JVP and rales throughout their lung fields. They will have poor distal perfusion and cool extremities that may become mottled. Lactate is ≥ 2 mmol/L. B-type natriuretic peptide (BNP) and liver function test (LFTs) results are elevated, and urine output is diminished. If a pulmonary arterial catheter is placed (highly recommended), the cardiac index (CI) is < 2.2 L/min/m² and the pulmonary capillary wedge pressure (PCWP) is > 15 mm Hg. These patients look like what many clinicians think of when they think of CS.

These patients need better tissue perfusion. Inotropic support is needed to augment CO and DO₂. Pharmacologic support is often the initial step. These patients also benefit from volume removal. This is usually accomplished with aggressive diuresis with a loop diuretic.

Stage D (Deteriorating) patients have failed initial treatment with single inotropic support. Hypoperfusion is not getting better and is often worsening. Lactate is staying > 2 mmol/L or rising. BNP and LFTs are also rising. These patients require additional inotropes and usually need vasopressors. Mechanical cardiac support (MCS) is often needed in addition to pharmacologic inotropic support.

Stage E (Extremis) patients have actual or impending circulatory collapse. These patients are peri-arrest with profound hypotension, lactic acidosis (often > 8 mmol/L), and unconsciousness. These patients are worsening despite multiple strategies to augment CO and DO₂. These patients will likely die without emergent veno-arterial (VA) extracorporeal membrane oxygenation (ECMO). The goal of treatment is to stabilize the patient as quickly as possible to prevent cardiac arrest.

In addition to the stage of CS, SCAI developed the three-axis model of risk stratification as a conceptual model to be used for evaluation and prognostication. Etiology and phenotype, shock severity, and risk modifiers are factors related to patient outcomes from CS. This model is a way to individualize treatment to a specific patient.

Shock severity: What is the patient’s shock stage? What are the hemodynamics and metabolic abnormalities? What are the doses of the inotropes or vasopressors? Risk goes up with higher shock stages and vasoactive agent doses and worsening metabolic disturbances or hemodynamics.

Phenotype and etiology: what is the clinical etiology of the patient’s CS? Is this acute or acute on chronic? Which ventricle is involved? Is this cardiac driven or are other organs the driving factor? Single ventricle involvement is better than bi-ventricular failure. Cardiogenic collapse due to an overdose may have a better outcome than a massive AMI.

Risk modifiers: how old is the patient? What are the comorbidities? Did the patient have a cardiac arrest? What is the patient’s mental status? Some factors are modifiable, but others are not. The concept of chronologic vs. physiologic age may come into play. A frail 40 year old with stage 4 cancer and end stage renal failure may be assessed differently than a 70 year old with mild hypertension and an AMI.

The SCAI stages of CS are a pragmatic way to assess patients with an acute presentation of CS. These stages have defined criteria and treatment recommendations for all patients. The three-axis model allows the clinician to individualize patient care based on shock severity, etiology/phenotype, and risk modification. The goal of these stages is to identify and aggressively treat patients with CS, as well as identify when treatment is failing and additional therapies may be needed.

Dr. Gaillard is Associate Professor in the Departments of Anesthesiology, Section on Critical Care; Internal Medicine, Section on Pulmonology, Critical Care, Allergy, and Immunologic Diseases; and Emergency Medicine; Wake Forest School of Medicine, Winston-Salem, N.C.

Cardiogenic shock (CS) is being recognized more often in critically ill patients. This increased prevalence is likely due to a better understanding of CS and the benefit of improving cardiac output (CO) to ensure adequate oxygen delivery (DO₂). There is no one specific definition of CS; rather, CS describes a clinical condition in which a patient is suffering from cellular hypoperfusion due to an ineffective CO with normal or elevating intravascular filling pressures.

CS is often, but not always, caused by a cardiac dysfunction. The heart is not able to provide adequate DO₂ to the tissues. Hypoperfusion ensues. The body attempts to compensate for the poor perfusion by increasing heart rate, vasoconstriction, and shunting blood flow to vital organs. These compensatory mechanisms worsen perfusion by increasing myocardial ischemia which further worsens cardiac dysfunction. This is known as the downward spiral of CS (Ann Intern Med. 1999 Jul 6;131[1]).

There is a number of different etiologies for CS. Historically, acute myocardial infarctions (AMI) was the most common cause. In the last 20 years, AMI-induced CS has become less prevalent due to more aggressive reperfusion strategies. CS due to etiologies such as cardiomyopathy, myocarditis, right ventricle failure, and valvular pathologies have become more common. While the overarching goal is to restore DO₂ to the tissue, the optimal treatment may differ based on the etiology of the CS. The Society for Cardiovascular Angiography and Intervention (SCAI) published CS classification stages in 2019 and then updated the stages 2022 (J Am Coll Cardiol. 2022 Mar 8;79[9]:933-46). In addition to the stages, there is now a three-axis model to address risk stratification. These classifications are a practically means of identifying and treating patients presenting with or concern for acute CS.

Stage A (At Risk) patients are not experiencing CS, but they are the at risk population. The patient’s hemodynamics, physical exam, and markers of hypoperfusion are normal. Stage A includes patients who have had a recent AMI or have heart failure.

Stage B (Beginning) patients have evidence of hemodynamic instability but are able to maintain tissue perfusion. These patients will have true or relative hypotension or tachycardia (in an attempt to maintain CO). Distal perfusion is adequate, but signs of ensuing decompensation (eg, elevated jugular venous pressure [JVP]) are present. Lactate is <2.0 mmol/L. Clinicians must be vigilant and treat these patients aggressively, so they do not decompensate further. It can be difficult to identify these patients because their blood pressure may be “normal,” but upon investigation, the blood pressure is actually a drop from the patient’s baseline.

Chronic heart failure patients with a history of depressed cardiac function will often have periods of cardiac decompensation between stages A and B. These patients are able to maintain perfusion for longer periods of time before further decompensation with hypoperfusion. If and when they do decompensate, they will often have a steep downward trajectory, so it is advantageous to the patient to be aggressive early.

Stage C (Classic) patients have evidence of tissue hypoperfusion. While these patients will often have true or relative hypotension, it is not a definition of stage C. These patients have evidence of volume overload with elevated JVP and rales throughout their lung fields. They will have poor distal perfusion and cool extremities that may become mottled. Lactate is ≥ 2 mmol/L. B-type natriuretic peptide (BNP) and liver function test (LFTs) results are elevated, and urine output is diminished. If a pulmonary arterial catheter is placed (highly recommended), the cardiac index (CI) is < 2.2 L/min/m² and the pulmonary capillary wedge pressure (PCWP) is > 15 mm Hg. These patients look like what many clinicians think of when they think of CS.

These patients need better tissue perfusion. Inotropic support is needed to augment CO and DO₂. Pharmacologic support is often the initial step. These patients also benefit from volume removal. This is usually accomplished with aggressive diuresis with a loop diuretic.

Stage D (Deteriorating) patients have failed initial treatment with single inotropic support. Hypoperfusion is not getting better and is often worsening. Lactate is staying > 2 mmol/L or rising. BNP and LFTs are also rising. These patients require additional inotropes and usually need vasopressors. Mechanical cardiac support (MCS) is often needed in addition to pharmacologic inotropic support.

Stage E (Extremis) patients have actual or impending circulatory collapse. These patients are peri-arrest with profound hypotension, lactic acidosis (often > 8 mmol/L), and unconsciousness. These patients are worsening despite multiple strategies to augment CO and DO₂. These patients will likely die without emergent veno-arterial (VA) extracorporeal membrane oxygenation (ECMO). The goal of treatment is to stabilize the patient as quickly as possible to prevent cardiac arrest.

In addition to the stage of CS, SCAI developed the three-axis model of risk stratification as a conceptual model to be used for evaluation and prognostication. Etiology and phenotype, shock severity, and risk modifiers are factors related to patient outcomes from CS. This model is a way to individualize treatment to a specific patient.

Shock severity: What is the patient’s shock stage? What are the hemodynamics and metabolic abnormalities? What are the doses of the inotropes or vasopressors? Risk goes up with higher shock stages and vasoactive agent doses and worsening metabolic disturbances or hemodynamics.

Phenotype and etiology: what is the clinical etiology of the patient’s CS? Is this acute or acute on chronic? Which ventricle is involved? Is this cardiac driven or are other organs the driving factor? Single ventricle involvement is better than bi-ventricular failure. Cardiogenic collapse due to an overdose may have a better outcome than a massive AMI.

Risk modifiers: how old is the patient? What are the comorbidities? Did the patient have a cardiac arrest? What is the patient’s mental status? Some factors are modifiable, but others are not. The concept of chronologic vs. physiologic age may come into play. A frail 40 year old with stage 4 cancer and end stage renal failure may be assessed differently than a 70 year old with mild hypertension and an AMI.

The SCAI stages of CS are a pragmatic way to assess patients with an acute presentation of CS. These stages have defined criteria and treatment recommendations for all patients. The three-axis model allows the clinician to individualize patient care based on shock severity, etiology/phenotype, and risk modification. The goal of these stages is to identify and aggressively treat patients with CS, as well as identify when treatment is failing and additional therapies may be needed.

Dr. Gaillard is Associate Professor in the Departments of Anesthesiology, Section on Critical Care; Internal Medicine, Section on Pulmonology, Critical Care, Allergy, and Immunologic Diseases; and Emergency Medicine; Wake Forest School of Medicine, Winston-Salem, N.C.

Cardiogenic shock (CS) is being recognized more often in critically ill patients. This increased prevalence is likely due to a better understanding of CS and the benefit of improving cardiac output (CO) to ensure adequate oxygen delivery (DO₂). There is no one specific definition of CS; rather, CS describes a clinical condition in which a patient is suffering from cellular hypoperfusion due to an ineffective CO with normal or elevating intravascular filling pressures.

CS is often, but not always, caused by a cardiac dysfunction. The heart is not able to provide adequate DO₂ to the tissues. Hypoperfusion ensues. The body attempts to compensate for the poor perfusion by increasing heart rate, vasoconstriction, and shunting blood flow to vital organs. These compensatory mechanisms worsen perfusion by increasing myocardial ischemia which further worsens cardiac dysfunction. This is known as the downward spiral of CS (Ann Intern Med. 1999 Jul 6;131[1]).

There is a number of different etiologies for CS. Historically, acute myocardial infarctions (AMI) was the most common cause. In the last 20 years, AMI-induced CS has become less prevalent due to more aggressive reperfusion strategies. CS due to etiologies such as cardiomyopathy, myocarditis, right ventricle failure, and valvular pathologies have become more common. While the overarching goal is to restore DO₂ to the tissue, the optimal treatment may differ based on the etiology of the CS. The Society for Cardiovascular Angiography and Intervention (SCAI) published CS classification stages in 2019 and then updated the stages 2022 (J Am Coll Cardiol. 2022 Mar 8;79[9]:933-46). In addition to the stages, there is now a three-axis model to address risk stratification. These classifications are a practically means of identifying and treating patients presenting with or concern for acute CS.

Stage A (At Risk) patients are not experiencing CS, but they are the at risk population. The patient’s hemodynamics, physical exam, and markers of hypoperfusion are normal. Stage A includes patients who have had a recent AMI or have heart failure.

Stage B (Beginning) patients have evidence of hemodynamic instability but are able to maintain tissue perfusion. These patients will have true or relative hypotension or tachycardia (in an attempt to maintain CO). Distal perfusion is adequate, but signs of ensuing decompensation (eg, elevated jugular venous pressure [JVP]) are present. Lactate is <2.0 mmol/L. Clinicians must be vigilant and treat these patients aggressively, so they do not decompensate further. It can be difficult to identify these patients because their blood pressure may be “normal,” but upon investigation, the blood pressure is actually a drop from the patient’s baseline.

Chronic heart failure patients with a history of depressed cardiac function will often have periods of cardiac decompensation between stages A and B. These patients are able to maintain perfusion for longer periods of time before further decompensation with hypoperfusion. If and when they do decompensate, they will often have a steep downward trajectory, so it is advantageous to the patient to be aggressive early.

Stage C (Classic) patients have evidence of tissue hypoperfusion. While these patients will often have true or relative hypotension, it is not a definition of stage C. These patients have evidence of volume overload with elevated JVP and rales throughout their lung fields. They will have poor distal perfusion and cool extremities that may become mottled. Lactate is ≥ 2 mmol/L. B-type natriuretic peptide (BNP) and liver function test (LFTs) results are elevated, and urine output is diminished. If a pulmonary arterial catheter is placed (highly recommended), the cardiac index (CI) is < 2.2 L/min/m² and the pulmonary capillary wedge pressure (PCWP) is > 15 mm Hg. These patients look like what many clinicians think of when they think of CS.

These patients need better tissue perfusion. Inotropic support is needed to augment CO and DO₂. Pharmacologic support is often the initial step. These patients also benefit from volume removal. This is usually accomplished with aggressive diuresis with a loop diuretic.

Stage D (Deteriorating) patients have failed initial treatment with single inotropic support. Hypoperfusion is not getting better and is often worsening. Lactate is staying > 2 mmol/L or rising. BNP and LFTs are also rising. These patients require additional inotropes and usually need vasopressors. Mechanical cardiac support (MCS) is often needed in addition to pharmacologic inotropic support.

Stage E (Extremis) patients have actual or impending circulatory collapse. These patients are peri-arrest with profound hypotension, lactic acidosis (often > 8 mmol/L), and unconsciousness. These patients are worsening despite multiple strategies to augment CO and DO₂. These patients will likely die without emergent veno-arterial (VA) extracorporeal membrane oxygenation (ECMO). The goal of treatment is to stabilize the patient as quickly as possible to prevent cardiac arrest.

In addition to the stage of CS, SCAI developed the three-axis model of risk stratification as a conceptual model to be used for evaluation and prognostication. Etiology and phenotype, shock severity, and risk modifiers are factors related to patient outcomes from CS. This model is a way to individualize treatment to a specific patient.

Shock severity: What is the patient’s shock stage? What are the hemodynamics and metabolic abnormalities? What are the doses of the inotropes or vasopressors? Risk goes up with higher shock stages and vasoactive agent doses and worsening metabolic disturbances or hemodynamics.

Phenotype and etiology: what is the clinical etiology of the patient’s CS? Is this acute or acute on chronic? Which ventricle is involved? Is this cardiac driven or are other organs the driving factor? Single ventricle involvement is better than bi-ventricular failure. Cardiogenic collapse due to an overdose may have a better outcome than a massive AMI.

Risk modifiers: how old is the patient? What are the comorbidities? Did the patient have a cardiac arrest? What is the patient’s mental status? Some factors are modifiable, but others are not. The concept of chronologic vs. physiologic age may come into play. A frail 40 year old with stage 4 cancer and end stage renal failure may be assessed differently than a 70 year old with mild hypertension and an AMI.

The SCAI stages of CS are a pragmatic way to assess patients with an acute presentation of CS. These stages have defined criteria and treatment recommendations for all patients. The three-axis model allows the clinician to individualize patient care based on shock severity, etiology/phenotype, and risk modification. The goal of these stages is to identify and aggressively treat patients with CS, as well as identify when treatment is failing and additional therapies may be needed.

Dr. Gaillard is Associate Professor in the Departments of Anesthesiology, Section on Critical Care; Internal Medicine, Section on Pulmonology, Critical Care, Allergy, and Immunologic Diseases; and Emergency Medicine; Wake Forest School of Medicine, Winston-Salem, N.C.

Unexplained dyspnea is a common complaint among patients seen in pulmonary clinics, and can be difficult to define, quantify, and determine the etiology. The ATS official statement defined dyspnea as “a subjective experience of breathing discomfort that consists of qualitatively distinct sensations that vary in intensity” (Am J Respir Crit Care Med. 2012; 185:435). A myriad of diseases can cause dyspnea, including cardiac, pulmonary, neuromuscular, psychological, and hematologic disorders; obesity, deconditioning, and the normal aging process may also contribute to dyspnea. Adding further diagnostic confusion, multiple causes may exist in a given patient.

Finding the cause or causes of dyspnea can be difficult and may require extensive testing, time, and cost. Initially, a history and physical exam are performed with more focused testing undertaken depending on most likely causes. For most patients, initial evaluation includes a CBC, TSH, pulmonary function tests, chest radiograph, and, often, a transthoracic echocardiogram. If these tests are unrevealing, or if clinical suspicion is high, more costly, invasive, and time-consuming tests are obtained. These may include bronchoprovocation testing, cardiac stress tests, chest CT scan, and, if warranted, right- and/or left-sided heart catheterization. Ideally, these tests are utilized appropriately based on the patient’s clinical presentation and the results of initial evaluation. In addition to high cost, invasive testing risks injury.

Cardiopulmonary exercise testing (CPET) has been called the “gold standard” test for evaluation of unexplained dyspnea (Palange P, et al. Eur Respir J. 2007;29:185).

Symptom-limited CPET measures multiple physiological variables during stress, potentially identifying the cause of dyspnea that is not evident by measurements made at rest. CPET may also differentiate the limiting factor in patients with multiple diseases that each could be contributing to dyspnea. CPET provides an objective measurement of cardiorespiratory fitness and may provide prognostic information. CPET typically consists of a symptom-limited maximal incremental exercise test using either a treadmill or cycle ergometer. The primary measurements include oxygen uptake (Vo₂), carbon dioxide output (Vco₂), minute ventilation (VE), ECG, blood pressure, oxygen saturation (Spo₂) and, depending on the indication, arterial blood gases at rest and peak exercise. An invasive CPET includes the above measurements and the addition of a pulmonary artery catheter and radial artery catheter allowing the assessment of ventricular filling pressures, pulmonary arterial pressures, cardiac output, and measures of oxygen transport. Invasive CPET is less commonly performed in clinical practice due to cost, high resource utilization, and greater risk of complications.

What is the evidence that CPET is the gold standard for evaluating dyspnea? Limited evidence supports this claim. Martinez and colleagues (Chest. 1994;105[1]:168) evaluated 50 patients presenting with unexplained dyspnea with normal CBC, thyroid studies, chest radiograph, and spirometry with no-invasive CPET. CPET was used to make an initial diagnosis, and this was compared with a definitive diagnosis based on additional testing guided by CPET findings and response to targeted therapy. Most patients (68%) eventually received a diagnossis of normal, deconditioned, hyperactive airway disease, or a psychogenic cause of dyspnea. The important findings from this study include: (1) CPET was able to identify cardiac or pulmonary disease, if present; (2) A normal CPET excluded significant cardiac or pulmonary disease in most patients suggesting that a normal CPET is useful in limiting subsequent testing; (3) In some patients, CPET wasn’t able to accurately differentiate cardiac disease from deconditioning as both exhibited an abnormal CPET pattern including low peak Vo₂, low Vo₂ at anaerobic threshold, decreased O₂ pulse, and often low peak heart rate. In more than 75% of patients, the CPET, and focused testing based on CPET findings, confidently identified the cause of dyspnea not explained by routine testing.

There is evidence that invasive CPET may provide diagnostic information when the cause of dyspnea is not identified using noninvasive testing. Huang and colleagues (Eur J Prev Cardiol. 2017;24[11]:1190) investigated the use of invasive CPET in 530 patients who had undergone extensive evaluation for dyspnea, including noninvasive CPET in 30% of patients, and the diagnosis remained unclear. The cause of dyspnea was determinedin all patients and included: exercise-induced pulmonary arterial hypertension (17%), heart failure with preserved ejection fraction (18%), dysautonomia or preload failure (21%), oxidative myopathy (25%), primary hyperventilation (8%), and various other conditions (11%). Most patients had been undergoing work up for unexplained dyspnea for a median of 511 days before evaluation in the dyspnea clinic. Huang et al’s study demonstrates some of the limitations of noninvasive CPET, including distinguishing cardiac limitation from dysautonomia or preload failure, deconditioning, oxidative myopathies, and mild pulmonary vascular disease. This study didn’t answer how many patients having noninvasive CPET would need an invasive study to get their diagnosis.

A limitation of both the Martinez et al and Huang et al studies is that they were conducted at subspecialty dyspnea clinics located in large referral centers and may not be representative of patients seen in general pulmonary clinics for the evaluation of dyspnea. This may result in over-representation of less common diseases, such as oxidative myopathies and dysautonomia or preload failure. Even with this limitation, these two studies showed that CPETs have the potential to expedite diagnoses and treatment in patients with unexplained dyspnea.

More investigation is needed to understand the clinical utility, and potential cost savings, of CPET for patients referred to general pulmonary clinics with unexplained dyspnea. We retrospectively reviewed 89 patients who underwent CPET for unexplained dyspnea from 2017 to 2019 at Intermountain Medical Center (Cook CP. Eur Respir J. 2022; 60: Suppl. 66, 1939). Nearly 50% of the patients undergoing CPET were diagnosed with obesity, deconditioning, or normal. In patients under the age of 60 years, 64% were diagnosed with obesity, deconditioning, or a normal study. Conversely, 70% of patients over the age of 60 years had an abnormal cardiac or pulmonary limitation.

We also evaluated whether CPET affected diagnostic testing patterns in the 6 months following testing. We determined that potentially inappropriate testing was performed in only 13% of patients after obtaining a CPET diagnosis. These data suggest that CPET results affect ordering provider behavior. Also, in younger patients, in whom initial evaluation is unrevealing of cardiopulmonary disease, a CPET could be performed early in the evaluation process. This may result in decreased health care cost and time to diagnosis. At our institution, CPET is less expensive than a transthoracic echocardiogram.

So, is CPET worthy of its status as the gold standard for determining the etiology of unexplained dysp-nea? The answer for noninvasive CPET is a definite “maybe.” There is evidence that some CPET patterns support a specific diagnosis. However, referring providers may be disappointed by CPET reports that do not provide a definitive cause for a patient’s dyspnea. An abnormal cardiac limitation may be caused by systolic or diastolic dysfunction, myocardial ischemia, preload failure or dysautonomia, deconditioning, and oxidative myopathy. Even in these situations, a specific CPET pattern may limit the differential diagnosis and facilitate a more focused and cost-effective evaluation. A normal CPET provides reassurance that significant disease is not causing the patient’s dyspnea and prevent further unnecessary and costly evaluation.

Unexplained dyspnea is a common complaint among patients seen in pulmonary clinics, and can be difficult to define, quantify, and determine the etiology. The ATS official statement defined dyspnea as “a subjective experience of breathing discomfort that consists of qualitatively distinct sensations that vary in intensity” (Am J Respir Crit Care Med. 2012; 185:435). A myriad of diseases can cause dyspnea, including cardiac, pulmonary, neuromuscular, psychological, and hematologic disorders; obesity, deconditioning, and the normal aging process may also contribute to dyspnea. Adding further diagnostic confusion, multiple causes may exist in a given patient.

Finding the cause or causes of dyspnea can be difficult and may require extensive testing, time, and cost. Initially, a history and physical exam are performed with more focused testing undertaken depending on most likely causes. For most patients, initial evaluation includes a CBC, TSH, pulmonary function tests, chest radiograph, and, often, a transthoracic echocardiogram. If these tests are unrevealing, or if clinical suspicion is high, more costly, invasive, and time-consuming tests are obtained. These may include bronchoprovocation testing, cardiac stress tests, chest CT scan, and, if warranted, right- and/or left-sided heart catheterization. Ideally, these tests are utilized appropriately based on the patient’s clinical presentation and the results of initial evaluation. In addition to high cost, invasive testing risks injury.

Cardiopulmonary exercise testing (CPET) has been called the “gold standard” test for evaluation of unexplained dyspnea (Palange P, et al. Eur Respir J. 2007;29:185).

Symptom-limited CPET measures multiple physiological variables during stress, potentially identifying the cause of dyspnea that is not evident by measurements made at rest. CPET may also differentiate the limiting factor in patients with multiple diseases that each could be contributing to dyspnea. CPET provides an objective measurement of cardiorespiratory fitness and may provide prognostic information. CPET typically consists of a symptom-limited maximal incremental exercise test using either a treadmill or cycle ergometer. The primary measurements include oxygen uptake (Vo₂), carbon dioxide output (Vco₂), minute ventilation (VE), ECG, blood pressure, oxygen saturation (Spo₂) and, depending on the indication, arterial blood gases at rest and peak exercise. An invasive CPET includes the above measurements and the addition of a pulmonary artery catheter and radial artery catheter allowing the assessment of ventricular filling pressures, pulmonary arterial pressures, cardiac output, and measures of oxygen transport. Invasive CPET is less commonly performed in clinical practice due to cost, high resource utilization, and greater risk of complications.

What is the evidence that CPET is the gold standard for evaluating dyspnea? Limited evidence supports this claim. Martinez and colleagues (Chest. 1994;105[1]:168) evaluated 50 patients presenting with unexplained dyspnea with normal CBC, thyroid studies, chest radiograph, and spirometry with no-invasive CPET. CPET was used to make an initial diagnosis, and this was compared with a definitive diagnosis based on additional testing guided by CPET findings and response to targeted therapy. Most patients (68%) eventually received a diagnossis of normal, deconditioned, hyperactive airway disease, or a psychogenic cause of dyspnea. The important findings from this study include: (1) CPET was able to identify cardiac or pulmonary disease, if present; (2) A normal CPET excluded significant cardiac or pulmonary disease in most patients suggesting that a normal CPET is useful in limiting subsequent testing; (3) In some patients, CPET wasn’t able to accurately differentiate cardiac disease from deconditioning as both exhibited an abnormal CPET pattern including low peak Vo₂, low Vo₂ at anaerobic threshold, decreased O₂ pulse, and often low peak heart rate. In more than 75% of patients, the CPET, and focused testing based on CPET findings, confidently identified the cause of dyspnea not explained by routine testing.

There is evidence that invasive CPET may provide diagnostic information when the cause of dyspnea is not identified using noninvasive testing. Huang and colleagues (Eur J Prev Cardiol. 2017;24[11]:1190) investigated the use of invasive CPET in 530 patients who had undergone extensive evaluation for dyspnea, including noninvasive CPET in 30% of patients, and the diagnosis remained unclear. The cause of dyspnea was determinedin all patients and included: exercise-induced pulmonary arterial hypertension (17%), heart failure with preserved ejection fraction (18%), dysautonomia or preload failure (21%), oxidative myopathy (25%), primary hyperventilation (8%), and various other conditions (11%). Most patients had been undergoing work up for unexplained dyspnea for a median of 511 days before evaluation in the dyspnea clinic. Huang et al’s study demonstrates some of the limitations of noninvasive CPET, including distinguishing cardiac limitation from dysautonomia or preload failure, deconditioning, oxidative myopathies, and mild pulmonary vascular disease. This study didn’t answer how many patients having noninvasive CPET would need an invasive study to get their diagnosis.

A limitation of both the Martinez et al and Huang et al studies is that they were conducted at subspecialty dyspnea clinics located in large referral centers and may not be representative of patients seen in general pulmonary clinics for the evaluation of dyspnea. This may result in over-representation of less common diseases, such as oxidative myopathies and dysautonomia or preload failure. Even with this limitation, these two studies showed that CPETs have the potential to expedite diagnoses and treatment in patients with unexplained dyspnea.

More investigation is needed to understand the clinical utility, and potential cost savings, of CPET for patients referred to general pulmonary clinics with unexplained dyspnea. We retrospectively reviewed 89 patients who underwent CPET for unexplained dyspnea from 2017 to 2019 at Intermountain Medical Center (Cook CP. Eur Respir J. 2022; 60: Suppl. 66, 1939). Nearly 50% of the patients undergoing CPET were diagnosed with obesity, deconditioning, or normal. In patients under the age of 60 years, 64% were diagnosed with obesity, deconditioning, or a normal study. Conversely, 70% of patients over the age of 60 years had an abnormal cardiac or pulmonary limitation.

We also evaluated whether CPET affected diagnostic testing patterns in the 6 months following testing. We determined that potentially inappropriate testing was performed in only 13% of patients after obtaining a CPET diagnosis. These data suggest that CPET results affect ordering provider behavior. Also, in younger patients, in whom initial evaluation is unrevealing of cardiopulmonary disease, a CPET could be performed early in the evaluation process. This may result in decreased health care cost and time to diagnosis. At our institution, CPET is less expensive than a transthoracic echocardiogram.

So, is CPET worthy of its status as the gold standard for determining the etiology of unexplained dysp-nea? The answer for noninvasive CPET is a definite “maybe.” There is evidence that some CPET patterns support a specific diagnosis. However, referring providers may be disappointed by CPET reports that do not provide a definitive cause for a patient’s dyspnea. An abnormal cardiac limitation may be caused by systolic or diastolic dysfunction, myocardial ischemia, preload failure or dysautonomia, deconditioning, and oxidative myopathy. Even in these situations, a specific CPET pattern may limit the differential diagnosis and facilitate a more focused and cost-effective evaluation. A normal CPET provides reassurance that significant disease is not causing the patient’s dyspnea and prevent further unnecessary and costly evaluation.

Unexplained dyspnea is a common complaint among patients seen in pulmonary clinics, and can be difficult to define, quantify, and determine the etiology. The ATS official statement defined dyspnea as “a subjective experience of breathing discomfort that consists of qualitatively distinct sensations that vary in intensity” (Am J Respir Crit Care Med. 2012; 185:435). A myriad of diseases can cause dyspnea, including cardiac, pulmonary, neuromuscular, psychological, and hematologic disorders; obesity, deconditioning, and the normal aging process may also contribute to dyspnea. Adding further diagnostic confusion, multiple causes may exist in a given patient.

Finding the cause or causes of dyspnea can be difficult and may require extensive testing, time, and cost. Initially, a history and physical exam are performed with more focused testing undertaken depending on most likely causes. For most patients, initial evaluation includes a CBC, TSH, pulmonary function tests, chest radiograph, and, often, a transthoracic echocardiogram. If these tests are unrevealing, or if clinical suspicion is high, more costly, invasive, and time-consuming tests are obtained. These may include bronchoprovocation testing, cardiac stress tests, chest CT scan, and, if warranted, right- and/or left-sided heart catheterization. Ideally, these tests are utilized appropriately based on the patient’s clinical presentation and the results of initial evaluation. In addition to high cost, invasive testing risks injury.

Cardiopulmonary exercise testing (CPET) has been called the “gold standard” test for evaluation of unexplained dyspnea (Palange P, et al. Eur Respir J. 2007;29:185).

Symptom-limited CPET measures multiple physiological variables during stress, potentially identifying the cause of dyspnea that is not evident by measurements made at rest. CPET may also differentiate the limiting factor in patients with multiple diseases that each could be contributing to dyspnea. CPET provides an objective measurement of cardiorespiratory fitness and may provide prognostic information. CPET typically consists of a symptom-limited maximal incremental exercise test using either a treadmill or cycle ergometer. The primary measurements include oxygen uptake (Vo₂), carbon dioxide output (Vco₂), minute ventilation (VE), ECG, blood pressure, oxygen saturation (Spo₂) and, depending on the indication, arterial blood gases at rest and peak exercise. An invasive CPET includes the above measurements and the addition of a pulmonary artery catheter and radial artery catheter allowing the assessment of ventricular filling pressures, pulmonary arterial pressures, cardiac output, and measures of oxygen transport. Invasive CPET is less commonly performed in clinical practice due to cost, high resource utilization, and greater risk of complications.

What is the evidence that CPET is the gold standard for evaluating dyspnea? Limited evidence supports this claim. Martinez and colleagues (Chest. 1994;105[1]:168) evaluated 50 patients presenting with unexplained dyspnea with normal CBC, thyroid studies, chest radiograph, and spirometry with no-invasive CPET. CPET was used to make an initial diagnosis, and this was compared with a definitive diagnosis based on additional testing guided by CPET findings and response to targeted therapy. Most patients (68%) eventually received a diagnossis of normal, deconditioned, hyperactive airway disease, or a psychogenic cause of dyspnea. The important findings from this study include: (1) CPET was able to identify cardiac or pulmonary disease, if present; (2) A normal CPET excluded significant cardiac or pulmonary disease in most patients suggesting that a normal CPET is useful in limiting subsequent testing; (3) In some patients, CPET wasn’t able to accurately differentiate cardiac disease from deconditioning as both exhibited an abnormal CPET pattern including low peak Vo₂, low Vo₂ at anaerobic threshold, decreased O₂ pulse, and often low peak heart rate. In more than 75% of patients, the CPET, and focused testing based on CPET findings, confidently identified the cause of dyspnea not explained by routine testing.

There is evidence that invasive CPET may provide diagnostic information when the cause of dyspnea is not identified using noninvasive testing. Huang and colleagues (Eur J Prev Cardiol. 2017;24[11]:1190) investigated the use of invasive CPET in 530 patients who had undergone extensive evaluation for dyspnea, including noninvasive CPET in 30% of patients, and the diagnosis remained unclear. The cause of dyspnea was determinedin all patients and included: exercise-induced pulmonary arterial hypertension (17%), heart failure with preserved ejection fraction (18%), dysautonomia or preload failure (21%), oxidative myopathy (25%), primary hyperventilation (8%), and various other conditions (11%). Most patients had been undergoing work up for unexplained dyspnea for a median of 511 days before evaluation in the dyspnea clinic. Huang et al’s study demonstrates some of the limitations of noninvasive CPET, including distinguishing cardiac limitation from dysautonomia or preload failure, deconditioning, oxidative myopathies, and mild pulmonary vascular disease. This study didn’t answer how many patients having noninvasive CPET would need an invasive study to get their diagnosis.

A limitation of both the Martinez et al and Huang et al studies is that they were conducted at subspecialty dyspnea clinics located in large referral centers and may not be representative of patients seen in general pulmonary clinics for the evaluation of dyspnea. This may result in over-representation of less common diseases, such as oxidative myopathies and dysautonomia or preload failure. Even with this limitation, these two studies showed that CPETs have the potential to expedite diagnoses and treatment in patients with unexplained dyspnea.

More investigation is needed to understand the clinical utility, and potential cost savings, of CPET for patients referred to general pulmonary clinics with unexplained dyspnea. We retrospectively reviewed 89 patients who underwent CPET for unexplained dyspnea from 2017 to 2019 at Intermountain Medical Center (Cook CP. Eur Respir J. 2022; 60: Suppl. 66, 1939). Nearly 50% of the patients undergoing CPET were diagnosed with obesity, deconditioning, or normal. In patients under the age of 60 years, 64% were diagnosed with obesity, deconditioning, or a normal study. Conversely, 70% of patients over the age of 60 years had an abnormal cardiac or pulmonary limitation.

We also evaluated whether CPET affected diagnostic testing patterns in the 6 months following testing. We determined that potentially inappropriate testing was performed in only 13% of patients after obtaining a CPET diagnosis. These data suggest that CPET results affect ordering provider behavior. Also, in younger patients, in whom initial evaluation is unrevealing of cardiopulmonary disease, a CPET could be performed early in the evaluation process. This may result in decreased health care cost and time to diagnosis. At our institution, CPET is less expensive than a transthoracic echocardiogram.

So, is CPET worthy of its status as the gold standard for determining the etiology of unexplained dysp-nea? The answer for noninvasive CPET is a definite “maybe.” There is evidence that some CPET patterns support a specific diagnosis. However, referring providers may be disappointed by CPET reports that do not provide a definitive cause for a patient’s dyspnea. An abnormal cardiac limitation may be caused by systolic or diastolic dysfunction, myocardial ischemia, preload failure or dysautonomia, deconditioning, and oxidative myopathy. Even in these situations, a specific CPET pattern may limit the differential diagnosis and facilitate a more focused and cost-effective evaluation. A normal CPET provides reassurance that significant disease is not causing the patient’s dyspnea and prevent further unnecessary and costly evaluation.

In recent months, we have seen the results of the much awaited Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis (CLOVERS) trial showing that a restrictive fluid and early vasopressor strategy initiated on arrival of patients with sepsis and hypotension in the ED did not result in decreased mortality compared with a liberal fluid approach (PETAL Network. www.nejm.org/doi/10.1056/NEJMoa2202707). The March 2023 issue of CHEST Physician provided a synopsis of the trial highlighting several limitations (Splete H. CHEST Physician. 2023;18[3]:1). Last year in 2022, the Conservative versus Liberal Approach to Fluid Therapy in Septic Shock (CLASSIC) trial also showed no difference in mortality with restrictive fluid compared with standard fluid in patients with septic shock in the ICU already receiving vasopressor therapy (Meyhoff TS, et al. N Engl J Med. 2022;386[26]:2459). Did CLOVERS and CLASSIC resolve the ongoing debate about the timing and quantity of fluid resuscitation in sepsis? Did their results suggest a “you can do what you want” approach? Is the management of sepsis and septic shock limited to fluids vs vasopressors? Hopefully, the ongoing studies ARISE FLUIDS (NCT04569942), EVIS (NCT05179499), FRESHLY (NCT05453565), 1BED (NCT05273034), and REDUCE (NCT04931485) will further address these questions.

In the meantime, I continue to admit and care for patients with sepsis in the ICU. One example was a 72-year-old woman with a history of stroke, coronary artery disease, diabetes, and chronic kidney disease presenting with 3 days of progressive cough and dyspnea. In the ED, temperature was 38.2° C, heart rate 120 beats per min, respiratory rate 28/min, blood pressure 82/48 mm Hg, and weight 92 kg. She had audible crackles in the left lower lung. Her laboratory and imaging results supported a diagnosis of sepsis due to severe community-acquired pneumonia, including the following values: white blood cell 18.2 million/mm3; lactate 3.8 mmol/L; and creatinine 4.3 mg/dL.

While in the ED, the patient received 1 liter of crystalloid fluids and appropriate broad spectrum antibiotics. Repeat lactate value was 2.8 mmol/L. Patient’s blood pressure then decreased to 85/42 mm Hg. Norepinephrine was started peripherally and titrated to 6 mcg/min to achieve blood pressure 104/56 mm Hg. No further fluid administration was given, and the patient was admitted to the medical ICU. On admission, a repeat lactate had increased to 3.4 mmol/L with blood pressure of 80/45 mm Hg. Instead of further escalating vasopressor administration, she received 2 L of fluid and continued at 150 mL/h. Shortly after, norepinephrine was titrated off. Fluid resuscitation was then deescalated. We transfered the patient to the general ward within 12 hours of ICU admission.

Could we have avoided ICU admission and critical care resource utilization if the patient had received more optimal fluid resuscitation in the ED?

While our fear of fluids (or hydrophobia) may be unwarranted, the management of this patient was a common example of fluid restriction in sepsis (Jaehne AK, et al. Crit Care Med. 2016;44[12]:2263). By clinical criteria, she was in septic shock (requiring vasopressor) and appropriately required ICU admission. But, I would posit that the patient had severe sepsis based on pre-Sepsis 3 criteria. Optimal initial fluid resuscitation would have prevented her from requiring vasopressor and progressing to septic shock with ICU admission. Unfortunately, the patient’s care reflected the objective of CLOVERS and its results. Other than the lack of decreased mortality, decreased ventilator use, decreased renal replacement therapy, and decreased hospital length of stay, restricting fluids resulted in an increase of 8.1% (95% confidence interval 3.3 to 12.8) ICU utilization. Furthermore, the data and safety monitoring committee halted the trial for futility at two-thirds of enrollment. One must wonder if CLOVERS had completed its intended enrollment of 2,320 patients, negative outcomes would have occurred.

Should an astute clinician interpret the results of the CLOVERS and CLASSIC trials as “Fluids, it doesn’t matter, so I can do what I want?” Absolutely not! The literature is abundant with studies showing that increasing dose and/or number of vasopressors is associated with higher mortality in septic shock. One example is a recent multicenter prospective cohort study examining the association of vasopressor dosing during the first 24 hours and 30-day mortality in septic shock over 33 hospitals (Roberts RJ, et al. Crit Care Med. 2020;48[10]:1445).

Six hundred and sixteen patients were enrolled with 31% 30-day mortality. In 24 hours after shock diagnosis, patients received a median of 3.4 (1.9-5.3) L of fluids and 8.5 mcg/min norepinephrine equivalent. During the first 6 hours, increasing vasopressor dosing was associated with increased odds of mortality. Every 10 mcg/min increase in norepinephrine over the 24-hour period was associated with a 33% increased odds of mortality. Patients who received no fluids but 35 mcg/min norepinephrine in 6 hours had the highest mortality of 50%. As fluid volume increased, the association between vasopressor dosing and mortality decreased, such that at least 2 L of fluid during the first 6 hours was required for this association to become nonsignificant. Based on these results and a number of past studies, we should be cautious in believing that a resuscitation strategy favoring vasopressors would result in a better outcome.

Shock resuscitation is complex, and there is no one-size-fits-all approach. With the present climate, the success of resuscitation has been simplified to assessing fluid responsiveness. Trainees learn to identify the inferior vena cava and lung B-lines by ultrasound. With more advanced technology, stroke volume variation is considered. And, let us not forget the passive leg raise. Rarely can our fellows and residents recite the components of oxygen delivery as targets of shock resuscitation: preload, afterload, contractility, hemoglobin, and oxygen saturation. Another patient example comes to mind when fluid responsiveness alone is inadequate.

Our patient was a 46-year-old man now day 4 in the ICU with Klebsiella bacteremia and acute cholecystitis undergoing medical management. His comorbidities included diabetes, obesity, hypertension, and cardiomyopathy with ejection fraction 35%. He was supported sson mechanical ventilation, norepinephrine 20 mcg/min, and receiving appropriate antibiotics. For hemodynamic monitoring, a central venous and arterial catheter have been placed. The patient had a heart rate 92 beats per min, mean arterial pressure (MAP) 57 mm Hg, central venous pressure (CVP) 26 mm Hg, stroke volume variation (SVV) 9%, cardiac output (CO) 2.5 L/min, and central venous oxygen saturation (ScvO₂) 42%.

Based on these parameters, we initiated dobutamine at 2.5 mcg/kg/min, which was then titrated to 20 mcg/kg/min over 2 hours to achieve ScvO₂ 72%. Interestingly, CVP had decreased to 18 mm Hg, SVV increased to 16%, with CO 4.5 L/min. MAP also increased to 68 mm Hg. We then administered 1-L fluid bolus with the elevated SVV. Given the patient’s underlying cardiomyopathy, CVP < 20 mm Hg appeared to indicate a state of fluid responsiveness. After our fluid administration, heart rate 98 beats per min, MAP 70 mm Hg, CVP increased to 21 mm Hg, SVV 12%, CO 4.7 L/min, and ScvO₂ 74%. In acknowledging a mixed hypovolemic, cardiogenic, and septic shock, we had optimized his hemodynamic state. Importantly, during this exercise of hemodynamic manipulation, we were able to decrease norepinephrine to 8 mcg/min, maintaining dobutamine at 20 mcg/kg/min.

The above case illustrates that the hemodynamic perturbations in sepsis and septic shock are not simple. Patients do not present with a single shock state. An infection progressing to shock often is confounded by hypovolemia and underlying comorbidities, such as cardiac dysfunction. Without considering the complex physiology, our desire to continue the debate of fluids vs vasopressors is on the brink of taking us back several decades when the management of sepsis was to start a fluid bolus, administer “Rocephin,” and initiate dopamine. But I remind myself that we have made advances – now it’s 1 L lactated Ringer’s, administer “vanco and zosyn,” and initiate norepinephrine.

In recent months, we have seen the results of the much awaited Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis (CLOVERS) trial showing that a restrictive fluid and early vasopressor strategy initiated on arrival of patients with sepsis and hypotension in the ED did not result in decreased mortality compared with a liberal fluid approach (PETAL Network. www.nejm.org/doi/10.1056/NEJMoa2202707). The March 2023 issue of CHEST Physician provided a synopsis of the trial highlighting several limitations (Splete H. CHEST Physician. 2023;18[3]:1). Last year in 2022, the Conservative versus Liberal Approach to Fluid Therapy in Septic Shock (CLASSIC) trial also showed no difference in mortality with restrictive fluid compared with standard fluid in patients with septic shock in the ICU already receiving vasopressor therapy (Meyhoff TS, et al. N Engl J Med. 2022;386[26]:2459). Did CLOVERS and CLASSIC resolve the ongoing debate about the timing and quantity of fluid resuscitation in sepsis? Did their results suggest a “you can do what you want” approach? Is the management of sepsis and septic shock limited to fluids vs vasopressors? Hopefully, the ongoing studies ARISE FLUIDS (NCT04569942), EVIS (NCT05179499), FRESHLY (NCT05453565), 1BED (NCT05273034), and REDUCE (NCT04931485) will further address these questions.

In the meantime, I continue to admit and care for patients with sepsis in the ICU. One example was a 72-year-old woman with a history of stroke, coronary artery disease, diabetes, and chronic kidney disease presenting with 3 days of progressive cough and dyspnea. In the ED, temperature was 38.2° C, heart rate 120 beats per min, respiratory rate 28/min, blood pressure 82/48 mm Hg, and weight 92 kg. She had audible crackles in the left lower lung. Her laboratory and imaging results supported a diagnosis of sepsis due to severe community-acquired pneumonia, including the following values: white blood cell 18.2 million/mm3; lactate 3.8 mmol/L; and creatinine 4.3 mg/dL.

While in the ED, the patient received 1 liter of crystalloid fluids and appropriate broad spectrum antibiotics. Repeat lactate value was 2.8 mmol/L. Patient’s blood pressure then decreased to 85/42 mm Hg. Norepinephrine was started peripherally and titrated to 6 mcg/min to achieve blood pressure 104/56 mm Hg. No further fluid administration was given, and the patient was admitted to the medical ICU. On admission, a repeat lactate had increased to 3.4 mmol/L with blood pressure of 80/45 mm Hg. Instead of further escalating vasopressor administration, she received 2 L of fluid and continued at 150 mL/h. Shortly after, norepinephrine was titrated off. Fluid resuscitation was then deescalated. We transfered the patient to the general ward within 12 hours of ICU admission.

Could we have avoided ICU admission and critical care resource utilization if the patient had received more optimal fluid resuscitation in the ED?

While our fear of fluids (or hydrophobia) may be unwarranted, the management of this patient was a common example of fluid restriction in sepsis (Jaehne AK, et al. Crit Care Med. 2016;44[12]:2263). By clinical criteria, she was in septic shock (requiring vasopressor) and appropriately required ICU admission. But, I would posit that the patient had severe sepsis based on pre-Sepsis 3 criteria. Optimal initial fluid resuscitation would have prevented her from requiring vasopressor and progressing to septic shock with ICU admission. Unfortunately, the patient’s care reflected the objective of CLOVERS and its results. Other than the lack of decreased mortality, decreased ventilator use, decreased renal replacement therapy, and decreased hospital length of stay, restricting fluids resulted in an increase of 8.1% (95% confidence interval 3.3 to 12.8) ICU utilization. Furthermore, the data and safety monitoring committee halted the trial for futility at two-thirds of enrollment. One must wonder if CLOVERS had completed its intended enrollment of 2,320 patients, negative outcomes would have occurred.

Should an astute clinician interpret the results of the CLOVERS and CLASSIC trials as “Fluids, it doesn’t matter, so I can do what I want?” Absolutely not! The literature is abundant with studies showing that increasing dose and/or number of vasopressors is associated with higher mortality in septic shock. One example is a recent multicenter prospective cohort study examining the association of vasopressor dosing during the first 24 hours and 30-day mortality in septic shock over 33 hospitals (Roberts RJ, et al. Crit Care Med. 2020;48[10]:1445).

Six hundred and sixteen patients were enrolled with 31% 30-day mortality. In 24 hours after shock diagnosis, patients received a median of 3.4 (1.9-5.3) L of fluids and 8.5 mcg/min norepinephrine equivalent. During the first 6 hours, increasing vasopressor dosing was associated with increased odds of mortality. Every 10 mcg/min increase in norepinephrine over the 24-hour period was associated with a 33% increased odds of mortality. Patients who received no fluids but 35 mcg/min norepinephrine in 6 hours had the highest mortality of 50%. As fluid volume increased, the association between vasopressor dosing and mortality decreased, such that at least 2 L of fluid during the first 6 hours was required for this association to become nonsignificant. Based on these results and a number of past studies, we should be cautious in believing that a resuscitation strategy favoring vasopressors would result in a better outcome.

Shock resuscitation is complex, and there is no one-size-fits-all approach. With the present climate, the success of resuscitation has been simplified to assessing fluid responsiveness. Trainees learn to identify the inferior vena cava and lung B-lines by ultrasound. With more advanced technology, stroke volume variation is considered. And, let us not forget the passive leg raise. Rarely can our fellows and residents recite the components of oxygen delivery as targets of shock resuscitation: preload, afterload, contractility, hemoglobin, and oxygen saturation. Another patient example comes to mind when fluid responsiveness alone is inadequate.

Our patient was a 46-year-old man now day 4 in the ICU with Klebsiella bacteremia and acute cholecystitis undergoing medical management. His comorbidities included diabetes, obesity, hypertension, and cardiomyopathy with ejection fraction 35%. He was supported sson mechanical ventilation, norepinephrine 20 mcg/min, and receiving appropriate antibiotics. For hemodynamic monitoring, a central venous and arterial catheter have been placed. The patient had a heart rate 92 beats per min, mean arterial pressure (MAP) 57 mm Hg, central venous pressure (CVP) 26 mm Hg, stroke volume variation (SVV) 9%, cardiac output (CO) 2.5 L/min, and central venous oxygen saturation (ScvO₂) 42%.

Based on these parameters, we initiated dobutamine at 2.5 mcg/kg/min, which was then titrated to 20 mcg/kg/min over 2 hours to achieve ScvO₂ 72%. Interestingly, CVP had decreased to 18 mm Hg, SVV increased to 16%, with CO 4.5 L/min. MAP also increased to 68 mm Hg. We then administered 1-L fluid bolus with the elevated SVV. Given the patient’s underlying cardiomyopathy, CVP < 20 mm Hg appeared to indicate a state of fluid responsiveness. After our fluid administration, heart rate 98 beats per min, MAP 70 mm Hg, CVP increased to 21 mm Hg, SVV 12%, CO 4.7 L/min, and ScvO₂ 74%. In acknowledging a mixed hypovolemic, cardiogenic, and septic shock, we had optimized his hemodynamic state. Importantly, during this exercise of hemodynamic manipulation, we were able to decrease norepinephrine to 8 mcg/min, maintaining dobutamine at 20 mcg/kg/min.

The above case illustrates that the hemodynamic perturbations in sepsis and septic shock are not simple. Patients do not present with a single shock state. An infection progressing to shock often is confounded by hypovolemia and underlying comorbidities, such as cardiac dysfunction. Without considering the complex physiology, our desire to continue the debate of fluids vs vasopressors is on the brink of taking us back several decades when the management of sepsis was to start a fluid bolus, administer “Rocephin,” and initiate dopamine. But I remind myself that we have made advances – now it’s 1 L lactated Ringer’s, administer “vanco and zosyn,” and initiate norepinephrine.

In recent months, we have seen the results of the much awaited Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis (CLOVERS) trial showing that a restrictive fluid and early vasopressor strategy initiated on arrival of patients with sepsis and hypotension in the ED did not result in decreased mortality compared with a liberal fluid approach (PETAL Network. www.nejm.org/doi/10.1056/NEJMoa2202707). The March 2023 issue of CHEST Physician provided a synopsis of the trial highlighting several limitations (Splete H. CHEST Physician. 2023;18[3]:1). Last year in 2022, the Conservative versus Liberal Approach to Fluid Therapy in Septic Shock (CLASSIC) trial also showed no difference in mortality with restrictive fluid compared with standard fluid in patients with septic shock in the ICU already receiving vasopressor therapy (Meyhoff TS, et al. N Engl J Med. 2022;386[26]:2459). Did CLOVERS and CLASSIC resolve the ongoing debate about the timing and quantity of fluid resuscitation in sepsis? Did their results suggest a “you can do what you want” approach? Is the management of sepsis and septic shock limited to fluids vs vasopressors? Hopefully, the ongoing studies ARISE FLUIDS (NCT04569942), EVIS (NCT05179499), FRESHLY (NCT05453565), 1BED (NCT05273034), and REDUCE (NCT04931485) will further address these questions.

In the meantime, I continue to admit and care for patients with sepsis in the ICU. One example was a 72-year-old woman with a history of stroke, coronary artery disease, diabetes, and chronic kidney disease presenting with 3 days of progressive cough and dyspnea. In the ED, temperature was 38.2° C, heart rate 120 beats per min, respiratory rate 28/min, blood pressure 82/48 mm Hg, and weight 92 kg. She had audible crackles in the left lower lung. Her laboratory and imaging results supported a diagnosis of sepsis due to severe community-acquired pneumonia, including the following values: white blood cell 18.2 million/mm3; lactate 3.8 mmol/L; and creatinine 4.3 mg/dL.

While in the ED, the patient received 1 liter of crystalloid fluids and appropriate broad spectrum antibiotics. Repeat lactate value was 2.8 mmol/L. Patient’s blood pressure then decreased to 85/42 mm Hg. Norepinephrine was started peripherally and titrated to 6 mcg/min to achieve blood pressure 104/56 mm Hg. No further fluid administration was given, and the patient was admitted to the medical ICU. On admission, a repeat lactate had increased to 3.4 mmol/L with blood pressure of 80/45 mm Hg. Instead of further escalating vasopressor administration, she received 2 L of fluid and continued at 150 mL/h. Shortly after, norepinephrine was titrated off. Fluid resuscitation was then deescalated. We transfered the patient to the general ward within 12 hours of ICU admission.

Could we have avoided ICU admission and critical care resource utilization if the patient had received more optimal fluid resuscitation in the ED?

While our fear of fluids (or hydrophobia) may be unwarranted, the management of this patient was a common example of fluid restriction in sepsis (Jaehne AK, et al. Crit Care Med. 2016;44[12]:2263). By clinical criteria, she was in septic shock (requiring vasopressor) and appropriately required ICU admission. But, I would posit that the patient had severe sepsis based on pre-Sepsis 3 criteria. Optimal initial fluid resuscitation would have prevented her from requiring vasopressor and progressing to septic shock with ICU admission. Unfortunately, the patient’s care reflected the objective of CLOVERS and its results. Other than the lack of decreased mortality, decreased ventilator use, decreased renal replacement therapy, and decreased hospital length of stay, restricting fluids resulted in an increase of 8.1% (95% confidence interval 3.3 to 12.8) ICU utilization. Furthermore, the data and safety monitoring committee halted the trial for futility at two-thirds of enrollment. One must wonder if CLOVERS had completed its intended enrollment of 2,320 patients, negative outcomes would have occurred.

Should an astute clinician interpret the results of the CLOVERS and CLASSIC trials as “Fluids, it doesn’t matter, so I can do what I want?” Absolutely not! The literature is abundant with studies showing that increasing dose and/or number of vasopressors is associated with higher mortality in septic shock. One example is a recent multicenter prospective cohort study examining the association of vasopressor dosing during the first 24 hours and 30-day mortality in septic shock over 33 hospitals (Roberts RJ, et al. Crit Care Med. 2020;48[10]:1445).

Six hundred and sixteen patients were enrolled with 31% 30-day mortality. In 24 hours after shock diagnosis, patients received a median of 3.4 (1.9-5.3) L of fluids and 8.5 mcg/min norepinephrine equivalent. During the first 6 hours, increasing vasopressor dosing was associated with increased odds of mortality. Every 10 mcg/min increase in norepinephrine over the 24-hour period was associated with a 33% increased odds of mortality. Patients who received no fluids but 35 mcg/min norepinephrine in 6 hours had the highest mortality of 50%. As fluid volume increased, the association between vasopressor dosing and mortality decreased, such that at least 2 L of fluid during the first 6 hours was required for this association to become nonsignificant. Based on these results and a number of past studies, we should be cautious in believing that a resuscitation strategy favoring vasopressors would result in a better outcome.

Shock resuscitation is complex, and there is no one-size-fits-all approach. With the present climate, the success of resuscitation has been simplified to assessing fluid responsiveness. Trainees learn to identify the inferior vena cava and lung B-lines by ultrasound. With more advanced technology, stroke volume variation is considered. And, let us not forget the passive leg raise. Rarely can our fellows and residents recite the components of oxygen delivery as targets of shock resuscitation: preload, afterload, contractility, hemoglobin, and oxygen saturation. Another patient example comes to mind when fluid responsiveness alone is inadequate.

Our patient was a 46-year-old man now day 4 in the ICU with Klebsiella bacteremia and acute cholecystitis undergoing medical management. His comorbidities included diabetes, obesity, hypertension, and cardiomyopathy with ejection fraction 35%. He was supported sson mechanical ventilation, norepinephrine 20 mcg/min, and receiving appropriate antibiotics. For hemodynamic monitoring, a central venous and arterial catheter have been placed. The patient had a heart rate 92 beats per min, mean arterial pressure (MAP) 57 mm Hg, central venous pressure (CVP) 26 mm Hg, stroke volume variation (SVV) 9%, cardiac output (CO) 2.5 L/min, and central venous oxygen saturation (ScvO₂) 42%.

Based on these parameters, we initiated dobutamine at 2.5 mcg/kg/min, which was then titrated to 20 mcg/kg/min over 2 hours to achieve ScvO₂ 72%. Interestingly, CVP had decreased to 18 mm Hg, SVV increased to 16%, with CO 4.5 L/min. MAP also increased to 68 mm Hg. We then administered 1-L fluid bolus with the elevated SVV. Given the patient’s underlying cardiomyopathy, CVP < 20 mm Hg appeared to indicate a state of fluid responsiveness. After our fluid administration, heart rate 98 beats per min, MAP 70 mm Hg, CVP increased to 21 mm Hg, SVV 12%, CO 4.7 L/min, and ScvO₂ 74%. In acknowledging a mixed hypovolemic, cardiogenic, and septic shock, we had optimized his hemodynamic state. Importantly, during this exercise of hemodynamic manipulation, we were able to decrease norepinephrine to 8 mcg/min, maintaining dobutamine at 20 mcg/kg/min.

The above case illustrates that the hemodynamic perturbations in sepsis and septic shock are not simple. Patients do not present with a single shock state. An infection progressing to shock often is confounded by hypovolemia and underlying comorbidities, such as cardiac dysfunction. Without considering the complex physiology, our desire to continue the debate of fluids vs vasopressors is on the brink of taking us back several decades when the management of sepsis was to start a fluid bolus, administer “Rocephin,” and initiate dopamine. But I remind myself that we have made advances – now it’s 1 L lactated Ringer’s, administer “vanco and zosyn,” and initiate norepinephrine.

“Artificial intelligence (AI) in healthcare refers to the use of machine learning (ML), deep learning, natural language processing, and computer vision to process and analyze large amounts of health care data.”

The preceding line is a direct quote from ChatGPT when prompted with the question “What is AI in health care?” (OpenAI, 2022). AI has rapidly infiltrated our lives. From using facial recognition software to unlock our cellphones to scrolling through targeted media suggested by streaming services, our daily existence is interwoven with algorithms. With the recent introduction of GPT-3 (the model that powers ChatGPT) in late 2022 and its even more capable successor, GPT-4, in March 2023, AI will continue to dominate our everyday environment in even more complex and meaningful ways.

CHEST

For sleep medicine, the initial applications of AI in this field have been innovative and promising. To date, AI has been leveraged to explore sleep staging, respiratory event scoring, characterization of insomnia, prediction of circadian timing from gene expression, endotyping, and phenotyping of obstructive sleep apnea (OSA) (Bandyopadhyay A, et al. Sleep Breath. 2023;27[1]:39). Pépin and colleagues (JAMA Netw Open. 2020;3[1]:e1919657) combined ML with mandibular movement to diagnose OSA with a reasonable agreement to polysomnography as a novel home-based alternative for diagnosis. AI has also been used to predict adherence to positive airway pressure (PAP) therapy in OSA (Scioscia G, et al. Inform Health Soc Care. 2022;47[3]:274) and as a digital intervention tool accessed via a smartphone app for people with insomnia (Philip P, et al, J Med Internet Res. 2020;22[12]:e24268). The data-rich field of sleep medicine is primed for further advancements through AI, albeit with a few hurdles and regulations to overcome before becoming mainstream.
 

Future promise

Sleep medicine is uniquely positioned to develop robust AI algorithms because of its vast data trove. Using AI, scientists can efficiently analyze the raw data from polysomnography, consumer sleep technology (CST), and nightly remote monitoring (from PAP devices) to substantially improve comprehension and management of sleep disorders.

AI can redefine OSA through analysis of the big data available, rather than solely relying on the apnea-hypopnea index. In addition, novel variables such as facial structure; snoring index; temperature trends; and sleep environment, position, and timing using a camera-based contactless technology may be incorporated to enhance the diagnostic accuracy for OSA or better describe sleep quality. AI algorithms can also be embedded into the electronic health record (EHR) to facilitate screening for sleep disorders using patient characteristics, thus accelerating the recognition and evaluation of possible sleep disorders.

CHEST

New ways of collecting data may deliver deeper insights into sleep health, as well. CST such as wearables, nearables, and phone applications are improving with each iteration, resulting in more data about sleep for millions of people over thousands of nights.

AI can help achieve precision medicine by integrating multimodal data to establish endotypes and phenotypes of various sleep disorders. Delineating endotypes and phenotypes allows for personalized treatment recommendations, which may improve patient adherence and health outcomes.

Treatment personalization can also be achieved through AI by predicting compliance to various therapies and responses, as well as by discovering alternative forms of delivery to accomplish desired health outcomes. For example, to predict PAP compliance, we can record a patient encounter and use natural language processing to analyze their opinion of their treatment, extracting relevant keywords and combining such processing with other available data, such as environmental factors, sleep schedule, medical history, and other information extracted from the EHR. As another example, AI can determine the optimal time for cancer therapy by predicting a patient’s circadian timing (Hesse J, et al. Cancers (Basel). 2020;12[11]:3103). Circadian timing of drug delivery may be relevant in other specialties including cardiovascular disease, endocrine disorders, and psychiatric conditions due to its associations with sleep. Integration of the various “-omics” (eg, proteomics, genomics, and transcriptomics) with physiologic, behavioral, and environmental data can offer opportunities for drug discovery and possible prediction of sleep disorders and sleep-related morbidity. Although generative pretrained transformers are currently used to predict text (ie, ChatGPT), it is theoretically possible to also apply this technique to identify patients at risk for future sleep disorders from an earlier age.
 

Challenges to an AI renaissance

Despite making strides in numerous specialties such as radiology, ophthalmology, pathology, oncology, and dermatology, AI has not yet gained mainstream usage. Why isn’t AI as ubiquitous and heavily entrenched in health care as it is in other industries? According to the National Academy of Medicine’s AI in Healthcare: The Hope, The Hype, The Promise, The Peril, there are several realities to address before we fully embrace the AI revolution (Matheny M, et al. 2019).

First, AI algorithms should be trained on quality data that are representative of the population. Interoperability between health care systems and standardization across platforms is required to access large volumes of quality data. The current framework for data gathering is limited due to regulations, patient privacy concerns, and organizational preferences. The challenges to data acquisition and standardization of information will continue to snarl progress unless there are legislative remedies.

Furthermore, datasets should be diverse enough to avoid introducing bias into the AI algorithm. If the dataset is limited and health inequities (eg, societal bias and social determinants of health) are excluded from the training set, then the outcome will perpetuate further explicit and implicit biases.

The Food and Drug Administration (FDA) reviews and authorizes AI/ML-enabled devices. Its current regulatory structure treats AI as a static process and does not allow for exercise of its intrinsic ability to continuously learn from additional data, thereby preventing it from becoming more accurate and evolving with the population over time. A more flexible approach is needed.

Lastly, recent advanced AI algorithms including deep learning and neural network methodology function like a “black box.” The models are not explainable or transparent. Without clear comprehension of its methods, acceptance in clinical practice will be guarded and further risk of inherent biases may ensue.
 

A path forward

But these challenges, like any, can be overcome. Research in the area of differential privacy and the adoption of recent data-sharing standards (eg, HL7 FHIR) can facilitate access to training data (Saripalle R, et al. J Biomed Inform. 2019;94:103188). Regulators are also open to incorporating feedback from the AI research community and industry in favor of innovation in this frenetic domain. The FDA developed the AI/ML Software as a Medical Device Action Plan in response to stakeholder feedback for oversight (FDA, 2021). Specifically, the “Good Machine Learning Practice” will be developed to describe AI/ML best practices (eg, data management, training, interpretability, evaluation, and documentation) to guide product development and standardization.

Sleep medicine has significantly progressed over the last several decades. Rather than maintain the status quo, AI can help fill the existing knowledge gaps, augment clinical practice, and streamline operations by analyzing and processing data at a volume and efficiency beyond human capacity. Fallibility is inevitable in machines and humans; however, like humans, machines can improve with continued training and exposure.

We asked ChatGPT about the future of AI in sleep medicine. It states that AI could have a “significant impact” on sleep disorders diagnosis, treatment, prevention, and sleep tracking and monitoring. Only time will tell if its claims are accurate.

Dr. Tan is Clinical Associate Professor with the Division of Sleep Medicine at the Stanford University School of Medicine. Dr. Bhargava is Clinical Professor with the Division of Pediatric Pulmonary, Asthma, and Sleep Medicine at the Stanford University School of Medicine.

“Artificial intelligence (AI) in healthcare refers to the use of machine learning (ML), deep learning, natural language processing, and computer vision to process and analyze large amounts of health care data.”

The preceding line is a direct quote from ChatGPT when prompted with the question “What is AI in health care?” (OpenAI, 2022). AI has rapidly infiltrated our lives. From using facial recognition software to unlock our cellphones to scrolling through targeted media suggested by streaming services, our daily existence is interwoven with algorithms. With the recent introduction of GPT-3 (the model that powers ChatGPT) in late 2022 and its even more capable successor, GPT-4, in March 2023, AI will continue to dominate our everyday environment in even more complex and meaningful ways.

CHEST

For sleep medicine, the initial applications of AI in this field have been innovative and promising. To date, AI has been leveraged to explore sleep staging, respiratory event scoring, characterization of insomnia, prediction of circadian timing from gene expression, endotyping, and phenotyping of obstructive sleep apnea (OSA) (Bandyopadhyay A, et al. Sleep Breath. 2023;27[1]:39). Pépin and colleagues (JAMA Netw Open. 2020;3[1]:e1919657) combined ML with mandibular movement to diagnose OSA with a reasonable agreement to polysomnography as a novel home-based alternative for diagnosis. AI has also been used to predict adherence to positive airway pressure (PAP) therapy in OSA (Scioscia G, et al. Inform Health Soc Care. 2022;47[3]:274) and as a digital intervention tool accessed via a smartphone app for people with insomnia (Philip P, et al, J Med Internet Res. 2020;22[12]:e24268). The data-rich field of sleep medicine is primed for further advancements through AI, albeit with a few hurdles and regulations to overcome before becoming mainstream.
 

Future promise

Sleep medicine is uniquely positioned to develop robust AI algorithms because of its vast data trove. Using AI, scientists can efficiently analyze the raw data from polysomnography, consumer sleep technology (CST), and nightly remote monitoring (from PAP devices) to substantially improve comprehension and management of sleep disorders.

AI can redefine OSA through analysis of the big data available, rather than solely relying on the apnea-hypopnea index. In addition, novel variables such as facial structure; snoring index; temperature trends; and sleep environment, position, and timing using a camera-based contactless technology may be incorporated to enhance the diagnostic accuracy for OSA or better describe sleep quality. AI algorithms can also be embedded into the electronic health record (EHR) to facilitate screening for sleep disorders using patient characteristics, thus accelerating the recognition and evaluation of possible sleep disorders.

CHEST

New ways of collecting data may deliver deeper insights into sleep health, as well. CST such as wearables, nearables, and phone applications are improving with each iteration, resulting in more data about sleep for millions of people over thousands of nights.

AI can help achieve precision medicine by integrating multimodal data to establish endotypes and phenotypes of various sleep disorders. Delineating endotypes and phenotypes allows for personalized treatment recommendations, which may improve patient adherence and health outcomes.

Treatment personalization can also be achieved through AI by predicting compliance to various therapies and responses, as well as by discovering alternative forms of delivery to accomplish desired health outcomes. For example, to predict PAP compliance, we can record a patient encounter and use natural language processing to analyze their opinion of their treatment, extracting relevant keywords and combining such processing with other available data, such as environmental factors, sleep schedule, medical history, and other information extracted from the EHR. As another example, AI can determine the optimal time for cancer therapy by predicting a patient’s circadian timing (Hesse J, et al. Cancers (Basel). 2020;12[11]:3103). Circadian timing of drug delivery may be relevant in other specialties including cardiovascular disease, endocrine disorders, and psychiatric conditions due to its associations with sleep. Integration of the various “-omics” (eg, proteomics, genomics, and transcriptomics) with physiologic, behavioral, and environmental data can offer opportunities for drug discovery and possible prediction of sleep disorders and sleep-related morbidity. Although generative pretrained transformers are currently used to predict text (ie, ChatGPT), it is theoretically possible to also apply this technique to identify patients at risk for future sleep disorders from an earlier age.
 

Challenges to an AI renaissance

Despite making strides in numerous specialties such as radiology, ophthalmology, pathology, oncology, and dermatology, AI has not yet gained mainstream usage. Why isn’t AI as ubiquitous and heavily entrenched in health care as it is in other industries? According to the National Academy of Medicine’s AI in Healthcare: The Hope, The Hype, The Promise, The Peril, there are several realities to address before we fully embrace the AI revolution (Matheny M, et al. 2019).

First, AI algorithms should be trained on quality data that are representative of the population. Interoperability between health care systems and standardization across platforms is required to access large volumes of quality data. The current framework for data gathering is limited due to regulations, patient privacy concerns, and organizational preferences. The challenges to data acquisition and standardization of information will continue to snarl progress unless there are legislative remedies.

Furthermore, datasets should be diverse enough to avoid introducing bias into the AI algorithm. If the dataset is limited and health inequities (eg, societal bias and social determinants of health) are excluded from the training set, then the outcome will perpetuate further explicit and implicit biases.

The Food and Drug Administration (FDA) reviews and authorizes AI/ML-enabled devices. Its current regulatory structure treats AI as a static process and does not allow for exercise of its intrinsic ability to continuously learn from additional data, thereby preventing it from becoming more accurate and evolving with the population over time. A more flexible approach is needed.

Lastly, recent advanced AI algorithms including deep learning and neural network methodology function like a “black box.” The models are not explainable or transparent. Without clear comprehension of its methods, acceptance in clinical practice will be guarded and further risk of inherent biases may ensue.
 

A path forward

But these challenges, like any, can be overcome. Research in the area of differential privacy and the adoption of recent data-sharing standards (eg, HL7 FHIR) can facilitate access to training data (Saripalle R, et al. J Biomed Inform. 2019;94:103188). Regulators are also open to incorporating feedback from the AI research community and industry in favor of innovation in this frenetic domain. The FDA developed the AI/ML Software as a Medical Device Action Plan in response to stakeholder feedback for oversight (FDA, 2021). Specifically, the “Good Machine Learning Practice” will be developed to describe AI/ML best practices (eg, data management, training, interpretability, evaluation, and documentation) to guide product development and standardization.

Sleep medicine has significantly progressed over the last several decades. Rather than maintain the status quo, AI can help fill the existing knowledge gaps, augment clinical practice, and streamline operations by analyzing and processing data at a volume and efficiency beyond human capacity. Fallibility is inevitable in machines and humans; however, like humans, machines can improve with continued training and exposure.

We asked ChatGPT about the future of AI in sleep medicine. It states that AI could have a “significant impact” on sleep disorders diagnosis, treatment, prevention, and sleep tracking and monitoring. Only time will tell if its claims are accurate.

Dr. Tan is Clinical Associate Professor with the Division of Sleep Medicine at the Stanford University School of Medicine. Dr. Bhargava is Clinical Professor with the Division of Pediatric Pulmonary, Asthma, and Sleep Medicine at the Stanford University School of Medicine.

“Artificial intelligence (AI) in healthcare refers to the use of machine learning (ML), deep learning, natural language processing, and computer vision to process and analyze large amounts of health care data.”

The preceding line is a direct quote from ChatGPT when prompted with the question “What is AI in health care?” (OpenAI, 2022). AI has rapidly infiltrated our lives. From using facial recognition software to unlock our cellphones to scrolling through targeted media suggested by streaming services, our daily existence is interwoven with algorithms. With the recent introduction of GPT-3 (the model that powers ChatGPT) in late 2022 and its even more capable successor, GPT-4, in March 2023, AI will continue to dominate our everyday environment in even more complex and meaningful ways.

CHEST

For sleep medicine, the initial applications of AI in this field have been innovative and promising. To date, AI has been leveraged to explore sleep staging, respiratory event scoring, characterization of insomnia, prediction of circadian timing from gene expression, endotyping, and phenotyping of obstructive sleep apnea (OSA) (Bandyopadhyay A, et al. Sleep Breath. 2023;27[1]:39). Pépin and colleagues (JAMA Netw Open. 2020;3[1]:e1919657) combined ML with mandibular movement to diagnose OSA with a reasonable agreement to polysomnography as a novel home-based alternative for diagnosis. AI has also been used to predict adherence to positive airway pressure (PAP) therapy in OSA (Scioscia G, et al. Inform Health Soc Care. 2022;47[3]:274) and as a digital intervention tool accessed via a smartphone app for people with insomnia (Philip P, et al, J Med Internet Res. 2020;22[12]:e24268). The data-rich field of sleep medicine is primed for further advancements through AI, albeit with a few hurdles and regulations to overcome before becoming mainstream.
 

Future promise

Sleep medicine is uniquely positioned to develop robust AI algorithms because of its vast data trove. Using AI, scientists can efficiently analyze the raw data from polysomnography, consumer sleep technology (CST), and nightly remote monitoring (from PAP devices) to substantially improve comprehension and management of sleep disorders.

AI can redefine OSA through analysis of the big data available, rather than solely relying on the apnea-hypopnea index. In addition, novel variables such as facial structure; snoring index; temperature trends; and sleep environment, position, and timing using a camera-based contactless technology may be incorporated to enhance the diagnostic accuracy for OSA or better describe sleep quality. AI algorithms can also be embedded into the electronic health record (EHR) to facilitate screening for sleep disorders using patient characteristics, thus accelerating the recognition and evaluation of possible sleep disorders.

CHEST

New ways of collecting data may deliver deeper insights into sleep health, as well. CST such as wearables, nearables, and phone applications are improving with each iteration, resulting in more data about sleep for millions of people over thousands of nights.

AI can help achieve precision medicine by integrating multimodal data to establish endotypes and phenotypes of various sleep disorders. Delineating endotypes and phenotypes allows for personalized treatment recommendations, which may improve patient adherence and health outcomes.

Treatment personalization can also be achieved through AI by predicting compliance to various therapies and responses, as well as by discovering alternative forms of delivery to accomplish desired health outcomes. For example, to predict PAP compliance, we can record a patient encounter and use natural language processing to analyze their opinion of their treatment, extracting relevant keywords and combining such processing with other available data, such as environmental factors, sleep schedule, medical history, and other information extracted from the EHR. As another example, AI can determine the optimal time for cancer therapy by predicting a patient’s circadian timing (Hesse J, et al. Cancers (Basel). 2020;12[11]:3103). Circadian timing of drug delivery may be relevant in other specialties including cardiovascular disease, endocrine disorders, and psychiatric conditions due to its associations with sleep. Integration of the various “-omics” (eg, proteomics, genomics, and transcriptomics) with physiologic, behavioral, and environmental data can offer opportunities for drug discovery and possible prediction of sleep disorders and sleep-related morbidity. Although generative pretrained transformers are currently used to predict text (ie, ChatGPT), it is theoretically possible to also apply this technique to identify patients at risk for future sleep disorders from an earlier age.
 

Challenges to an AI renaissance

Despite making strides in numerous specialties such as radiology, ophthalmology, pathology, oncology, and dermatology, AI has not yet gained mainstream usage. Why isn’t AI as ubiquitous and heavily entrenched in health care as it is in other industries? According to the National Academy of Medicine’s AI in Healthcare: The Hope, The Hype, The Promise, The Peril, there are several realities to address before we fully embrace the AI revolution (Matheny M, et al. 2019).

First, AI algorithms should be trained on quality data that are representative of the population. Interoperability between health care systems and standardization across platforms is required to access large volumes of quality data. The current framework for data gathering is limited due to regulations, patient privacy concerns, and organizational preferences. The challenges to data acquisition and standardization of information will continue to snarl progress unless there are legislative remedies.

Furthermore, datasets should be diverse enough to avoid introducing bias into the AI algorithm. If the dataset is limited and health inequities (eg, societal bias and social determinants of health) are excluded from the training set, then the outcome will perpetuate further explicit and implicit biases.

The Food and Drug Administration (FDA) reviews and authorizes AI/ML-enabled devices. Its current regulatory structure treats AI as a static process and does not allow for exercise of its intrinsic ability to continuously learn from additional data, thereby preventing it from becoming more accurate and evolving with the population over time. A more flexible approach is needed.

Lastly, recent advanced AI algorithms including deep learning and neural network methodology function like a “black box.” The models are not explainable or transparent. Without clear comprehension of its methods, acceptance in clinical practice will be guarded and further risk of inherent biases may ensue.
 

A path forward

But these challenges, like any, can be overcome. Research in the area of differential privacy and the adoption of recent data-sharing standards (eg, HL7 FHIR) can facilitate access to training data (Saripalle R, et al. J Biomed Inform. 2019;94:103188). Regulators are also open to incorporating feedback from the AI research community and industry in favor of innovation in this frenetic domain. The FDA developed the AI/ML Software as a Medical Device Action Plan in response to stakeholder feedback for oversight (FDA, 2021). Specifically, the “Good Machine Learning Practice” will be developed to describe AI/ML best practices (eg, data management, training, interpretability, evaluation, and documentation) to guide product development and standardization.

Sleep medicine has significantly progressed over the last several decades. Rather than maintain the status quo, AI can help fill the existing knowledge gaps, augment clinical practice, and streamline operations by analyzing and processing data at a volume and efficiency beyond human capacity. Fallibility is inevitable in machines and humans; however, like humans, machines can improve with continued training and exposure.

We asked ChatGPT about the future of AI in sleep medicine. It states that AI could have a “significant impact” on sleep disorders diagnosis, treatment, prevention, and sleep tracking and monitoring. Only time will tell if its claims are accurate.

Dr. Tan is Clinical Associate Professor with the Division of Sleep Medicine at the Stanford University School of Medicine. Dr. Bhargava is Clinical Professor with the Division of Pediatric Pulmonary, Asthma, and Sleep Medicine at the Stanford University School of Medicine.

The threshold for abandoning supportive measures and initiating invasive mechanical ventilation (IMV) in patients with respiratory failure is unclear. Noninvasive respiratory support (RS) devices, such as high-flow nasal cannula (HFNC) and noninvasive positive-pressure ventilation (NIV), are tools used to support patients in distress prior to failure and the need for IMV. However, prolonged RS in patients who ultimately require IMV can be harmful.

As the COVID-19 pandemic evolved, ICUs around the world were overrun by patients with varying degrees of respiratory failure. With this novel pathogen came novel approaches to management. Here we will review data available prior to the pandemic and relate them to emerging evidence on prolonged RS in patients with COVID-19. We believe it is time to acknowledge that prolonged RS in patients who ultimately require IMV is likely deleterious. Increased awareness and care to avoid this situation (often meaning earlier intubation) should be implemented in clinical practice.

CHEST

Excessive tidal volume delivered during IMV can lead to lung injury. Though this principle is widely accepted, the recognition that the same physiology holds in a spontaneously breathing patient receiving RS has been slow to take hold. In the presence of a high respiratory drive injury from overdistension and large transpulmonary pressure, swings can occur with or without IMV. An excellent review summarizing the existing evidence of this risk was published years before the COVID-19 pandemic (Brochard L, et al. AJRCCM. 2017;195[4]:438).

A number of pre-COVID-19 publications focused on examining this topic in clinical practice deserve specific mention. A study of respiratory mechanics in patients on NIV found it was nearly impossible to meet traditional targets for lung protective tidal volumes. Those patients who progressed to IMV had higher expired tidal volumes (Carteaux G, et al. Crit Care Med. 2016;44[2]:282). A large systematic review and metanalysis including more than 11,000 immunocompromised patients found delayed intubation led to increased mortality (Dumas G, et al. AJRCCM. 2021;204[2]:187). This study did not specifically implicate RS days and patient self-induced lung injury as factors driving the excess mortality; another smaller propensity-matched retrospective analysis of patients in the ICU supported with HFNC noted a 65% reduction in mortality among patients intubated after less than vs greater than 48 hours on HFNC who ultimately required IMV (Kang B, et al. Intensive Care Med. 2015;41[4]:623).

Despite this and other existing evidence regarding the hazards of prolonged RS prior to IMV, COVID-19’s burden on the health care system dramatically changed the way hypoxemic respiratory failure is managed in the ICU. Anecdotally, during the height of the pandemic, it was commonplace to encounter patients with severe COVID-19 supported with very high RS settings for days or often weeks. Occasionally, RS may have stabilized breathing mechanics. However, it was often our experience that among those patients supported with RS for extended periods prior to IMV lung compliance was poor, lung recovery did not occur, and prognosis was dismal. Various factors, including early reports of high mortality among patients with COVID-19 supported with IMV, resulted in reliance on RS as a means for delaying or avoiding IMV. Interestingly, a propensity-matched study of more than 2,700 patients found that prolonged RS was associated with significantly higher in-hospital mortality but despite this finding, the practice increased over the course of the pandemic (Riera J, et al. Eur Respir J. 2023;61[3]:2201426). Further, a prospective study comparing outcomes between patients intubated within 48 hours for COVID-19-related respiratory failure to those intubated later found a greater risk of in-hospital mortality and worse long-term outpatient lung function testing (in survivors) in the latter group.

CHEST

It has previously been postulated that longer duration of IMV prior to the initiation of extracorporeal membrane oxygenation (ECMO) support in patients with hypoxemic respiratory failure may contribute to worse overall ECMO-related outcomes. This supposition is based on the principle that ECMO protects the lung by reducing ventilatory drive, tidal volume, and transpulmonary pressure swings. Several studies have documented an increase in mortality in patients supported with ECMO for COVID-19-related respiratory failure over the course of the pandemic. These investigators have noted that time to cannulation, but not IMV days (possibly reflecting duration of RS), correlates with worse ECMO outcomes (Ahmad Q, et al. ASAIO J. 2022;68[2]:171; Barbaro R, et al. Lancet. 2021;398[10307]:1230). We wonder if this reflects greater attention to low tidal volume ventilation during IMV but lack of awareness of or the inability to prevent injurious ventilation during prolonged RS. We view this as an important area for future research that may aid in patient selection in the ongoing effort to improve COVID-19-related ECMO outcomes.

The COVID-19 pandemic remains a significant burden on the health care system. Changes in care necessitated by the crisis produced innovations with the potential to rapidly improve outcomes. Notably though, it also has resulted in negative changes in response to a new pathogen that are hard to reconcile with physiologic principles. Evidence before and since the emergence of COVID-19 suggests prolonged RS prior to IMV is potentially harmful. It is critical for clinicians to recognize this principle and take steps to mitigate this problem in patients where a positive response to RS is not demonstrated in a timely manner.



Drs. Wilson and Chandel are with the Department of Pulmonary and Critical Care, Walter Reed National Military Medical Center, Washington, DC.

The threshold for abandoning supportive measures and initiating invasive mechanical ventilation (IMV) in patients with respiratory failure is unclear. Noninvasive respiratory support (RS) devices, such as high-flow nasal cannula (HFNC) and noninvasive positive-pressure ventilation (NIV), are tools used to support patients in distress prior to failure and the need for IMV. However, prolonged RS in patients who ultimately require IMV can be harmful.

As the COVID-19 pandemic evolved, ICUs around the world were overrun by patients with varying degrees of respiratory failure. With this novel pathogen came novel approaches to management. Here we will review data available prior to the pandemic and relate them to emerging evidence on prolonged RS in patients with COVID-19. We believe it is time to acknowledge that prolonged RS in patients who ultimately require IMV is likely deleterious. Increased awareness and care to avoid this situation (often meaning earlier intubation) should be implemented in clinical practice.

CHEST

Excessive tidal volume delivered during IMV can lead to lung injury. Though this principle is widely accepted, the recognition that the same physiology holds in a spontaneously breathing patient receiving RS has been slow to take hold. In the presence of a high respiratory drive injury from overdistension and large transpulmonary pressure, swings can occur with or without IMV. An excellent review summarizing the existing evidence of this risk was published years before the COVID-19 pandemic (Brochard L, et al. AJRCCM. 2017;195[4]:438).

A number of pre-COVID-19 publications focused on examining this topic in clinical practice deserve specific mention. A study of respiratory mechanics in patients on NIV found it was nearly impossible to meet traditional targets for lung protective tidal volumes. Those patients who progressed to IMV had higher expired tidal volumes (Carteaux G, et al. Crit Care Med. 2016;44[2]:282). A large systematic review and metanalysis including more than 11,000 immunocompromised patients found delayed intubation led to increased mortality (Dumas G, et al. AJRCCM. 2021;204[2]:187). This study did not specifically implicate RS days and patient self-induced lung injury as factors driving the excess mortality; another smaller propensity-matched retrospective analysis of patients in the ICU supported with HFNC noted a 65% reduction in mortality among patients intubated after less than vs greater than 48 hours on HFNC who ultimately required IMV (Kang B, et al. Intensive Care Med. 2015;41[4]:623).

Despite this and other existing evidence regarding the hazards of prolonged RS prior to IMV, COVID-19’s burden on the health care system dramatically changed the way hypoxemic respiratory failure is managed in the ICU. Anecdotally, during the height of the pandemic, it was commonplace to encounter patients with severe COVID-19 supported with very high RS settings for days or often weeks. Occasionally, RS may have stabilized breathing mechanics. However, it was often our experience that among those patients supported with RS for extended periods prior to IMV lung compliance was poor, lung recovery did not occur, and prognosis was dismal. Various factors, including early reports of high mortality among patients with COVID-19 supported with IMV, resulted in reliance on RS as a means for delaying or avoiding IMV. Interestingly, a propensity-matched study of more than 2,700 patients found that prolonged RS was associated with significantly higher in-hospital mortality but despite this finding, the practice increased over the course of the pandemic (Riera J, et al. Eur Respir J. 2023;61[3]:2201426). Further, a prospective study comparing outcomes between patients intubated within 48 hours for COVID-19-related respiratory failure to those intubated later found a greater risk of in-hospital mortality and worse long-term outpatient lung function testing (in survivors) in the latter group.

CHEST

It has previously been postulated that longer duration of IMV prior to the initiation of extracorporeal membrane oxygenation (ECMO) support in patients with hypoxemic respiratory failure may contribute to worse overall ECMO-related outcomes. This supposition is based on the principle that ECMO protects the lung by reducing ventilatory drive, tidal volume, and transpulmonary pressure swings. Several studies have documented an increase in mortality in patients supported with ECMO for COVID-19-related respiratory failure over the course of the pandemic. These investigators have noted that time to cannulation, but not IMV days (possibly reflecting duration of RS), correlates with worse ECMO outcomes (Ahmad Q, et al. ASAIO J. 2022;68[2]:171; Barbaro R, et al. Lancet. 2021;398[10307]:1230). We wonder if this reflects greater attention to low tidal volume ventilation during IMV but lack of awareness of or the inability to prevent injurious ventilation during prolonged RS. We view this as an important area for future research that may aid in patient selection in the ongoing effort to improve COVID-19-related ECMO outcomes.

The COVID-19 pandemic remains a significant burden on the health care system. Changes in care necessitated by the crisis produced innovations with the potential to rapidly improve outcomes. Notably though, it also has resulted in negative changes in response to a new pathogen that are hard to reconcile with physiologic principles. Evidence before and since the emergence of COVID-19 suggests prolonged RS prior to IMV is potentially harmful. It is critical for clinicians to recognize this principle and take steps to mitigate this problem in patients where a positive response to RS is not demonstrated in a timely manner.



Drs. Wilson and Chandel are with the Department of Pulmonary and Critical Care, Walter Reed National Military Medical Center, Washington, DC.

The threshold for abandoning supportive measures and initiating invasive mechanical ventilation (IMV) in patients with respiratory failure is unclear. Noninvasive respiratory support (RS) devices, such as high-flow nasal cannula (HFNC) and noninvasive positive-pressure ventilation (NIV), are tools used to support patients in distress prior to failure and the need for IMV. However, prolonged RS in patients who ultimately require IMV can be harmful.

As the COVID-19 pandemic evolved, ICUs around the world were overrun by patients with varying degrees of respiratory failure. With this novel pathogen came novel approaches to management. Here we will review data available prior to the pandemic and relate them to emerging evidence on prolonged RS in patients with COVID-19. We believe it is time to acknowledge that prolonged RS in patients who ultimately require IMV is likely deleterious. Increased awareness and care to avoid this situation (often meaning earlier intubation) should be implemented in clinical practice.

CHEST

Excessive tidal volume delivered during IMV can lead to lung injury. Though this principle is widely accepted, the recognition that the same physiology holds in a spontaneously breathing patient receiving RS has been slow to take hold. In the presence of a high respiratory drive injury from overdistension and large transpulmonary pressure, swings can occur with or without IMV. An excellent review summarizing the existing evidence of this risk was published years before the COVID-19 pandemic (Brochard L, et al. AJRCCM. 2017;195[4]:438).

A number of pre-COVID-19 publications focused on examining this topic in clinical practice deserve specific mention. A study of respiratory mechanics in patients on NIV found it was nearly impossible to meet traditional targets for lung protective tidal volumes. Those patients who progressed to IMV had higher expired tidal volumes (Carteaux G, et al. Crit Care Med. 2016;44[2]:282). A large systematic review and metanalysis including more than 11,000 immunocompromised patients found delayed intubation led to increased mortality (Dumas G, et al. AJRCCM. 2021;204[2]:187). This study did not specifically implicate RS days and patient self-induced lung injury as factors driving the excess mortality; another smaller propensity-matched retrospective analysis of patients in the ICU supported with HFNC noted a 65% reduction in mortality among patients intubated after less than vs greater than 48 hours on HFNC who ultimately required IMV (Kang B, et al. Intensive Care Med. 2015;41[4]:623).

Despite this and other existing evidence regarding the hazards of prolonged RS prior to IMV, COVID-19’s burden on the health care system dramatically changed the way hypoxemic respiratory failure is managed in the ICU. Anecdotally, during the height of the pandemic, it was commonplace to encounter patients with severe COVID-19 supported with very high RS settings for days or often weeks. Occasionally, RS may have stabilized breathing mechanics. However, it was often our experience that among those patients supported with RS for extended periods prior to IMV lung compliance was poor, lung recovery did not occur, and prognosis was dismal. Various factors, including early reports of high mortality among patients with COVID-19 supported with IMV, resulted in reliance on RS as a means for delaying or avoiding IMV. Interestingly, a propensity-matched study of more than 2,700 patients found that prolonged RS was associated with significantly higher in-hospital mortality but despite this finding, the practice increased over the course of the pandemic (Riera J, et al. Eur Respir J. 2023;61[3]:2201426). Further, a prospective study comparing outcomes between patients intubated within 48 hours for COVID-19-related respiratory failure to those intubated later found a greater risk of in-hospital mortality and worse long-term outpatient lung function testing (in survivors) in the latter group.

CHEST

It has previously been postulated that longer duration of IMV prior to the initiation of extracorporeal membrane oxygenation (ECMO) support in patients with hypoxemic respiratory failure may contribute to worse overall ECMO-related outcomes. This supposition is based on the principle that ECMO protects the lung by reducing ventilatory drive, tidal volume, and transpulmonary pressure swings. Several studies have documented an increase in mortality in patients supported with ECMO for COVID-19-related respiratory failure over the course of the pandemic. These investigators have noted that time to cannulation, but not IMV days (possibly reflecting duration of RS), correlates with worse ECMO outcomes (Ahmad Q, et al. ASAIO J. 2022;68[2]:171; Barbaro R, et al. Lancet. 2021;398[10307]:1230). We wonder if this reflects greater attention to low tidal volume ventilation during IMV but lack of awareness of or the inability to prevent injurious ventilation during prolonged RS. We view this as an important area for future research that may aid in patient selection in the ongoing effort to improve COVID-19-related ECMO outcomes.

The COVID-19 pandemic remains a significant burden on the health care system. Changes in care necessitated by the crisis produced innovations with the potential to rapidly improve outcomes. Notably though, it also has resulted in negative changes in response to a new pathogen that are hard to reconcile with physiologic principles. Evidence before and since the emergence of COVID-19 suggests prolonged RS prior to IMV is potentially harmful. It is critical for clinicians to recognize this principle and take steps to mitigate this problem in patients where a positive response to RS is not demonstrated in a timely manner.



Drs. Wilson and Chandel are with the Department of Pulmonary and Critical Care, Walter Reed National Military Medical Center, Washington, DC.

As you may have seen in the February issue, in my year serving as President of the American College of Chest Physicians, I will be periodically contributing to CHEST Physician with the latest updates and to serve as a touchpoint for what we are currently working on.

For this contribution, I want to share and reflect upon the recent Nurse Work Environment study published by the American Association of Critical-Care Nurses (AACN). Deployed in 2021, the now-published study concluded that there is serious need for “bold, intentional, and relentless” efforts to create and sustain healthy work environments that foster excellence in patient care and optimal outcomes for patients, nurses, and other members of the health care team.

CHEST

To achieve this, AACN recommends adhering to the Healthy Work Environments (HWE) Standards created in 2005 but that are more pertinent than ever in 2023.

As close partners of the AACN through the Critical Care Societies Collaborative, the CHEST organization applauds and vehemently supports the need for increased efforts to support nurses and other members of the care team.

In a previous article for CHEST Physician, I spoke about my goals for 2023 and one of those goals was to focus on increasing the membership of a variety of providers who help care for patients, including advanced practice providers, respiratory therapists, registered nurses, and others. CHEST is already an inclusive organization to a variety of health care providers, but we can do more, and this is a great time to reemphasize the importance of the care team by showing our support of the AACN and the working conditions of nurses.

Beyond supporting other organizations, the CHEST Board of Regents will focus on new ways to make the organization a valuable resource to every member at every level of their career and with every designation.

The (HWE) Standards that I encourage all CHEST members to support include:

• Skilled communication and true collaboration between doctors, nurses and other clinicians.
• Effective decision-making that includes nurses in the process for input and expertise.
• Appropriate staffing that ensures an effective match between patient needs and the skills of the nurse.
• Meaningful recognition by rewarding and appreciating the value that everyone brings to the team.
• Authentic leadership that embraces a healthy work environment and is supportive of every member of the care team.

Let’s all make a dedicated effort to be intentional in our support of our care team colleagues to improve the working environment and overall patient care.

Think of one thing you can do at your own institution or in your practice to improve the work environment for all those on your team. And then make it happen!

Please reach out with ideas or questions.

As you may have seen in the February issue, in my year serving as President of the American College of Chest Physicians, I will be periodically contributing to CHEST Physician with the latest updates and to serve as a touchpoint for what we are currently working on.

For this contribution, I want to share and reflect upon the recent Nurse Work Environment study published by the American Association of Critical-Care Nurses (AACN). Deployed in 2021, the now-published study concluded that there is serious need for “bold, intentional, and relentless” efforts to create and sustain healthy work environments that foster excellence in patient care and optimal outcomes for patients, nurses, and other members of the health care team.

CHEST

To achieve this, AACN recommends adhering to the Healthy Work Environments (HWE) Standards created in 2005 but that are more pertinent than ever in 2023.

As close partners of the AACN through the Critical Care Societies Collaborative, the CHEST organization applauds and vehemently supports the need for increased efforts to support nurses and other members of the care team.

In a previous article for CHEST Physician, I spoke about my goals for 2023 and one of those goals was to focus on increasing the membership of a variety of providers who help care for patients, including advanced practice providers, respiratory therapists, registered nurses, and others. CHEST is already an inclusive organization to a variety of health care providers, but we can do more, and this is a great time to reemphasize the importance of the care team by showing our support of the AACN and the working conditions of nurses.

Beyond supporting other organizations, the CHEST Board of Regents will focus on new ways to make the organization a valuable resource to every member at every level of their career and with every designation.

The (HWE) Standards that I encourage all CHEST members to support include:

• Skilled communication and true collaboration between doctors, nurses and other clinicians.
• Effective decision-making that includes nurses in the process for input and expertise.
• Appropriate staffing that ensures an effective match between patient needs and the skills of the nurse.
• Meaningful recognition by rewarding and appreciating the value that everyone brings to the team.
• Authentic leadership that embraces a healthy work environment and is supportive of every member of the care team.

Let’s all make a dedicated effort to be intentional in our support of our care team colleagues to improve the working environment and overall patient care.

Think of one thing you can do at your own institution or in your practice to improve the work environment for all those on your team. And then make it happen!

Please reach out with ideas or questions.

As you may have seen in the February issue, in my year serving as President of the American College of Chest Physicians, I will be periodically contributing to CHEST Physician with the latest updates and to serve as a touchpoint for what we are currently working on.

For this contribution, I want to share and reflect upon the recent Nurse Work Environment study published by the American Association of Critical-Care Nurses (AACN). Deployed in 2021, the now-published study concluded that there is serious need for “bold, intentional, and relentless” efforts to create and sustain healthy work environments that foster excellence in patient care and optimal outcomes for patients, nurses, and other members of the health care team.

CHEST

To achieve this, AACN recommends adhering to the Healthy Work Environments (HWE) Standards created in 2005 but that are more pertinent than ever in 2023.

As close partners of the AACN through the Critical Care Societies Collaborative, the CHEST organization applauds and vehemently supports the need for increased efforts to support nurses and other members of the care team.

In a previous article for CHEST Physician, I spoke about my goals for 2023 and one of those goals was to focus on increasing the membership of a variety of providers who help care for patients, including advanced practice providers, respiratory therapists, registered nurses, and others. CHEST is already an inclusive organization to a variety of health care providers, but we can do more, and this is a great time to reemphasize the importance of the care team by showing our support of the AACN and the working conditions of nurses.

Beyond supporting other organizations, the CHEST Board of Regents will focus on new ways to make the organization a valuable resource to every member at every level of their career and with every designation.

The (HWE) Standards that I encourage all CHEST members to support include:

• Skilled communication and true collaboration between doctors, nurses and other clinicians.
• Effective decision-making that includes nurses in the process for input and expertise.
• Appropriate staffing that ensures an effective match between patient needs and the skills of the nurse.
• Meaningful recognition by rewarding and appreciating the value that everyone brings to the team.
• Authentic leadership that embraces a healthy work environment and is supportive of every member of the care team.

Let’s all make a dedicated effort to be intentional in our support of our care team colleagues to improve the working environment and overall patient care.

Think of one thing you can do at your own institution or in your practice to improve the work environment for all those on your team. And then make it happen!

Please reach out with ideas or questions.

The overnight shift in the MCU began as it does for many intensivists, by hearing about ED admissions, transfers from outside hospitals, sick floor patients, and high-risk patients in the MICU. Earlier in the day, the MICU team had admitted a 39-year-old woman with a severe asthma attack that required endotracheal intubation and mechanical ventilation in the ED for hypercarbic respiratory failure. After intubation, she had no audible air movement on chest exam, severe hypercarbic respiratory acidosis determined by an arterial blood gas, a clear chest radiograph, and negative findings on a respiratory viral panel. Her family said that she had run out of her steroid inhaler a month earlier and could not afford a refill. She had been using increasing amounts of albuterol over the past week before developing severe shortness of breath on the day of admission. The ED and MICU teams aggressively treated her with high-dose inhaled albuterol, ipratropium, and IV magnesium sulfate for bronchodilation; methylprednisolone for airway inflammation; and continuous ketamine for sedation, analgesia, and bronchodilation (Rehder KJ, et al. Respir Care. 2017;62[6]:849). Her airway pressures continued to be high despite using lung protective ventilation, so she was shifted to a permissive hypercapnia ventilation strategy using neuromuscular blockade, deep sedation, and low minute-ventilation (Laher AE, et al. J Intensive Care Med. 2018;33[9]:491).

CHEST

Two hours into the shift, the bedside nurse noted that the patient had become hypotensive. Her ventilator pressures remained stable with peak inspiratory pressures of 38-42 cm H₂O, plateau pressures of 28-30 cm H₂O, auto-positive end-expiratory pressure (auto-PEEP) of 10-12 cm H₂O, and fractional inspiratory oxygen (FiO₂) of 40%. A repeat chest radiograph showed no signs of barotrauma, but arterial blood gas values showed severe respiratory acidosis with a pH of 7.05 and a PCO₂ > 100 mm Hg. Her condition stabilized when she received a continuous infusion of bicarbonate to control her acidosis and low-dose IV norepinephrine for blood pressure control. It was at that moment that the bedside nurse astutely asked whether we should consider starting ECMO for the patient, as coauthor Dr. Arun Kannappan had done for a similar patient with asthma a month earlier. Dr. Vandivier notes, “My first response was that ECMO was not needed, because our patient had stabilized, and I had taken care of many patients like this in the past. But as I considered the situation more carefully, it was clear that any further decompensation could put our patient’s life at risk by not leaving enough time to start ECMO in a controlled setting. In short, my ‘traditional’ approach left little room for error in a patient with high ventilator pressures and hemodynamic instability.”

CHEST

ECMO is a technique used to add oxygen or remove CO₂ from the blood of people with different forms of respiratory failure (Fan E, et al. Intensive Care Med. 2016;2:712) that was first used by Hill and colleagues in 1966 for trauma-induced ARDS (Hill JD, et al. N Engl J Med. 1972;286:629). The ECMO circuit pumps blood from the venous system into an oxygenator that adds oxygen and removes CO₂ before blood is returned to either the venous or arterial circulation (Intensive Care Med. 2016;42:712). Venovenous ECMO (vvECMO) is used in clinical scenarios where only oxygenation and/or CO₂ removal is needed, whereas venoarterial ECMO (vaECMO) is reserved for situations where additional hemodynamic support is necessary. ECMO is traditionally thought of as a means to increase blood oxygenation, but it is less widely appreciated that ECMO is particularly effective at removing blood CO₂. In addition to ECMO helping to normalize oxygenation or eliminate CO₂, it can also be used to lower tidal volumes, decrease airway pressures, and allow “lungs to rest” with the goal of avoiding ventilator-induced lung injury (VILI).

CHEST

Standing at the bedside, it seemed to the authors that it was the right time to think about instituting a salvage therapy. But was there evidence that ECMO could improve survival? Were there clear guidelines for when to initiate ECMO, and was ECMO more effective than other salvage therapies such as inhaled volatile anesthetics?

Since McDonnell and colleagues first described the use of ECMO for a severe asthma exacerbation in 1981 (Ann Thoracic Surg. 1981;31[2]:171), about 95 articles have been published. Other than two registry studies and a recent epidemiologic study, all of these publications were case reports, case series, and reviews. Mikkelsen and colleagues (ASAIO J. 2009;55[1]:47) performed a retrospective, cohort study using the International Extracorporeal Life Support (ECLS) Organization Registry to determine whether ECMO use for status asthmaticus was associated with greater survival than the use of ECMO for other causes of respiratory failure. From 1986 through 2006, a total of 2,127 cases of respiratory failure were identified that required ECMO, including 27 for status asthmaticus and 1,233 for other causes. Their analysis showed that 83.3% of asthmatics treated with ECMO survived to hospital discharge, compared with 50.8% of people treated with ECMO for respiratory failure not due to asthma, with an odds ratio (OR) of 4.86 favoring survival of asthmatics (OR = 4.86; 95% CI, 1.65-14.31, P = .004).

Yeo and colleagues (Yeo HJ, et al. Critical Care. 2017;21:297) also used the ECLS Organization Registry to measure survival to hospital discharge, complications, and clinical factors associated with in-hospital mortality for asthmatics treated with ECMO. They included 272 people treated with ECMO for asthma between 1992 and 2016, after excluding people treated with ECMO for cardiopulmonary resuscitation or cardiac dysfunction. ECMO was associated with improvements in ventilator mechanics, including a reduction in respiratory rate, FiO₂, peak inspiratory pressure, mean airway pressure, and driving pressure. Use of ECMO for status asthmaticus was also associated with an 83.5% survival to hospital discharge, similar to the study by Mikkelsen and colleagues. Hemorrhage, the most common complication, occurred in roughly a quarter of people treated with ECMO. In the multivariate analysis, age, bleeding, pre-ECMO PEEP, post-ECMO FiO₂, and driving pressure were all associated with higher in-hospital mortality.

Although there are no formal criteria to guide use of ECMO for asthma exacerbations with respiratory failure, a number of physicians and a physician organization have recommended that ECMO be considered for persistently high ventilator pressures, uncontrolled respiratory acidosis, or hemodynamic instability. Because our patient qualified for ECMO based on all three suggested criteria, we consulted cardiac surgery who quickly started her on vvECMO. She remained on ECMO for 4 days until she was decannulated, extubated, and discharged home.

Despite this positive outcome, the lack of a high-quality, controlled study to help guide our decision was surprising given the ability of ECMO to efficiently remove CO₂ and to decrease ventilator pressures. The lack of guidance prompted us to perform a retrospective, epidemiologic cohort study to determine whether treatment with ECMO for asthma exacerbations with respiratory failure was associated with reduced mortality, compared with people treated without ECMO (Zakrajsek JK, Chest. 2023;163[1]:38). The study included 13,714 people admitted to an ECMO-capable hospital with respiratory failure that required invasive ventilation because of an asthma exacerbation between 2010 and 2020, of which 127 were treated with ECMO and 13,587 were not. During this period, use of ECMO as a salvage therapy for severe asthma exacerbations was a rare event, but it became more common over time. With the limitation that 40% of asthma patients were transferred from an outside hospital, 74% were started on ECMO in the first 2 hospital days, and 94% were started within the first week of hospitalization. Once started, ECMO was continued for a median of 1.0 day and range of 1-49 days. Hospital mortality was 14.6% in the ECMO group versus 26.2% in the no ECMO group, which equated to an 11.6% absolute risk reduction (P = 0.03) and 52% relative risk reduction (P = 0.04) in mortality. ECMO was associated with hospital costs that were $114,000 higher per patient, compared with the no ECMO group, but did not affect intensive care unit length of stay, hospital length of stay, or time on invasive mechanical ventilation.

We were pleased that our patient had a good outcome, and were reassured by our study results. But we were left to wonder whether ECMO really was the best salvage therapy for asthma exacerbations with respiratory failure, and if it was initiated for the right indications at the best time. These are important treatment considerations that take on new urgency given that physicians are increasingly looking to ECMO as a salvage therapy for refractory asthma, and the recent FDA approval of low-flow, extracorporeal CO₂ removal systems that could make CO₂ removal a more available, and perhaps less expensive, strategy. Despite promising epidemiological data, it will be important that these questions are answered with well-designed clinical trials so that physicians can be armed with the knowledge needed to navigate complex clinical scenarios, and ultimately to prevent unfortunate deaths from a reversible disease.

The overnight shift in the MCU began as it does for many intensivists, by hearing about ED admissions, transfers from outside hospitals, sick floor patients, and high-risk patients in the MICU. Earlier in the day, the MICU team had admitted a 39-year-old woman with a severe asthma attack that required endotracheal intubation and mechanical ventilation in the ED for hypercarbic respiratory failure. After intubation, she had no audible air movement on chest exam, severe hypercarbic respiratory acidosis determined by an arterial blood gas, a clear chest radiograph, and negative findings on a respiratory viral panel. Her family said that she had run out of her steroid inhaler a month earlier and could not afford a refill. She had been using increasing amounts of albuterol over the past week before developing severe shortness of breath on the day of admission. The ED and MICU teams aggressively treated her with high-dose inhaled albuterol, ipratropium, and IV magnesium sulfate for bronchodilation; methylprednisolone for airway inflammation; and continuous ketamine for sedation, analgesia, and bronchodilation (Rehder KJ, et al. Respir Care. 2017;62[6]:849). Her airway pressures continued to be high despite using lung protective ventilation, so she was shifted to a permissive hypercapnia ventilation strategy using neuromuscular blockade, deep sedation, and low minute-ventilation (Laher AE, et al. J Intensive Care Med. 2018;33[9]:491).

CHEST

Two hours into the shift, the bedside nurse noted that the patient had become hypotensive. Her ventilator pressures remained stable with peak inspiratory pressures of 38-42 cm H₂O, plateau pressures of 28-30 cm H₂O, auto-positive end-expiratory pressure (auto-PEEP) of 10-12 cm H₂O, and fractional inspiratory oxygen (FiO₂) of 40%. A repeat chest radiograph showed no signs of barotrauma, but arterial blood gas values showed severe respiratory acidosis with a pH of 7.05 and a PCO₂ > 100 mm Hg. Her condition stabilized when she received a continuous infusion of bicarbonate to control her acidosis and low-dose IV norepinephrine for blood pressure control. It was at that moment that the bedside nurse astutely asked whether we should consider starting ECMO for the patient, as coauthor Dr. Arun Kannappan had done for a similar patient with asthma a month earlier. Dr. Vandivier notes, “My first response was that ECMO was not needed, because our patient had stabilized, and I had taken care of many patients like this in the past. But as I considered the situation more carefully, it was clear that any further decompensation could put our patient’s life at risk by not leaving enough time to start ECMO in a controlled setting. In short, my ‘traditional’ approach left little room for error in a patient with high ventilator pressures and hemodynamic instability.”

CHEST

ECMO is a technique used to add oxygen or remove CO₂ from the blood of people with different forms of respiratory failure (Fan E, et al. Intensive Care Med. 2016;2:712) that was first used by Hill and colleagues in 1966 for trauma-induced ARDS (Hill JD, et al. N Engl J Med. 1972;286:629). The ECMO circuit pumps blood from the venous system into an oxygenator that adds oxygen and removes CO₂ before blood is returned to either the venous or arterial circulation (Intensive Care Med. 2016;42:712). Venovenous ECMO (vvECMO) is used in clinical scenarios where only oxygenation and/or CO₂ removal is needed, whereas venoarterial ECMO (vaECMO) is reserved for situations where additional hemodynamic support is necessary. ECMO is traditionally thought of as a means to increase blood oxygenation, but it is less widely appreciated that ECMO is particularly effective at removing blood CO₂. In addition to ECMO helping to normalize oxygenation or eliminate CO₂, it can also be used to lower tidal volumes, decrease airway pressures, and allow “lungs to rest” with the goal of avoiding ventilator-induced lung injury (VILI).

CHEST

Standing at the bedside, it seemed to the authors that it was the right time to think about instituting a salvage therapy. But was there evidence that ECMO could improve survival? Were there clear guidelines for when to initiate ECMO, and was ECMO more effective than other salvage therapies such as inhaled volatile anesthetics?

Since McDonnell and colleagues first described the use of ECMO for a severe asthma exacerbation in 1981 (Ann Thoracic Surg. 1981;31[2]:171), about 95 articles have been published. Other than two registry studies and a recent epidemiologic study, all of these publications were case reports, case series, and reviews. Mikkelsen and colleagues (ASAIO J. 2009;55[1]:47) performed a retrospective, cohort study using the International Extracorporeal Life Support (ECLS) Organization Registry to determine whether ECMO use for status asthmaticus was associated with greater survival than the use of ECMO for other causes of respiratory failure. From 1986 through 2006, a total of 2,127 cases of respiratory failure were identified that required ECMO, including 27 for status asthmaticus and 1,233 for other causes. Their analysis showed that 83.3% of asthmatics treated with ECMO survived to hospital discharge, compared with 50.8% of people treated with ECMO for respiratory failure not due to asthma, with an odds ratio (OR) of 4.86 favoring survival of asthmatics (OR = 4.86; 95% CI, 1.65-14.31, P = .004).

Yeo and colleagues (Yeo HJ, et al. Critical Care. 2017;21:297) also used the ECLS Organization Registry to measure survival to hospital discharge, complications, and clinical factors associated with in-hospital mortality for asthmatics treated with ECMO. They included 272 people treated with ECMO for asthma between 1992 and 2016, after excluding people treated with ECMO for cardiopulmonary resuscitation or cardiac dysfunction. ECMO was associated with improvements in ventilator mechanics, including a reduction in respiratory rate, FiO₂, peak inspiratory pressure, mean airway pressure, and driving pressure. Use of ECMO for status asthmaticus was also associated with an 83.5% survival to hospital discharge, similar to the study by Mikkelsen and colleagues. Hemorrhage, the most common complication, occurred in roughly a quarter of people treated with ECMO. In the multivariate analysis, age, bleeding, pre-ECMO PEEP, post-ECMO FiO₂, and driving pressure were all associated with higher in-hospital mortality.

Although there are no formal criteria to guide use of ECMO for asthma exacerbations with respiratory failure, a number of physicians and a physician organization have recommended that ECMO be considered for persistently high ventilator pressures, uncontrolled respiratory acidosis, or hemodynamic instability. Because our patient qualified for ECMO based on all three suggested criteria, we consulted cardiac surgery who quickly started her on vvECMO. She remained on ECMO for 4 days until she was decannulated, extubated, and discharged home.

Despite this positive outcome, the lack of a high-quality, controlled study to help guide our decision was surprising given the ability of ECMO to efficiently remove CO₂ and to decrease ventilator pressures. The lack of guidance prompted us to perform a retrospective, epidemiologic cohort study to determine whether treatment with ECMO for asthma exacerbations with respiratory failure was associated with reduced mortality, compared with people treated without ECMO (Zakrajsek JK, Chest. 2023;163[1]:38). The study included 13,714 people admitted to an ECMO-capable hospital with respiratory failure that required invasive ventilation because of an asthma exacerbation between 2010 and 2020, of which 127 were treated with ECMO and 13,587 were not. During this period, use of ECMO as a salvage therapy for severe asthma exacerbations was a rare event, but it became more common over time. With the limitation that 40% of asthma patients were transferred from an outside hospital, 74% were started on ECMO in the first 2 hospital days, and 94% were started within the first week of hospitalization. Once started, ECMO was continued for a median of 1.0 day and range of 1-49 days. Hospital mortality was 14.6% in the ECMO group versus 26.2% in the no ECMO group, which equated to an 11.6% absolute risk reduction (P = 0.03) and 52% relative risk reduction (P = 0.04) in mortality. ECMO was associated with hospital costs that were $114,000 higher per patient, compared with the no ECMO group, but did not affect intensive care unit length of stay, hospital length of stay, or time on invasive mechanical ventilation.

We were pleased that our patient had a good outcome, and were reassured by our study results. But we were left to wonder whether ECMO really was the best salvage therapy for asthma exacerbations with respiratory failure, and if it was initiated for the right indications at the best time. These are important treatment considerations that take on new urgency given that physicians are increasingly looking to ECMO as a salvage therapy for refractory asthma, and the recent FDA approval of low-flow, extracorporeal CO₂ removal systems that could make CO₂ removal a more available, and perhaps less expensive, strategy. Despite promising epidemiological data, it will be important that these questions are answered with well-designed clinical trials so that physicians can be armed with the knowledge needed to navigate complex clinical scenarios, and ultimately to prevent unfortunate deaths from a reversible disease.

The overnight shift in the MCU began as it does for many intensivists, by hearing about ED admissions, transfers from outside hospitals, sick floor patients, and high-risk patients in the MICU. Earlier in the day, the MICU team had admitted a 39-year-old woman with a severe asthma attack that required endotracheal intubation and mechanical ventilation in the ED for hypercarbic respiratory failure. After intubation, she had no audible air movement on chest exam, severe hypercarbic respiratory acidosis determined by an arterial blood gas, a clear chest radiograph, and negative findings on a respiratory viral panel. Her family said that she had run out of her steroid inhaler a month earlier and could not afford a refill. She had been using increasing amounts of albuterol over the past week before developing severe shortness of breath on the day of admission. The ED and MICU teams aggressively treated her with high-dose inhaled albuterol, ipratropium, and IV magnesium sulfate for bronchodilation; methylprednisolone for airway inflammation; and continuous ketamine for sedation, analgesia, and bronchodilation (Rehder KJ, et al. Respir Care. 2017;62[6]:849). Her airway pressures continued to be high despite using lung protective ventilation, so she was shifted to a permissive hypercapnia ventilation strategy using neuromuscular blockade, deep sedation, and low minute-ventilation (Laher AE, et al. J Intensive Care Med. 2018;33[9]:491).

CHEST

Two hours into the shift, the bedside nurse noted that the patient had become hypotensive. Her ventilator pressures remained stable with peak inspiratory pressures of 38-42 cm H₂O, plateau pressures of 28-30 cm H₂O, auto-positive end-expiratory pressure (auto-PEEP) of 10-12 cm H₂O, and fractional inspiratory oxygen (FiO₂) of 40%. A repeat chest radiograph showed no signs of barotrauma, but arterial blood gas values showed severe respiratory acidosis with a pH of 7.05 and a PCO₂ > 100 mm Hg. Her condition stabilized when she received a continuous infusion of bicarbonate to control her acidosis and low-dose IV norepinephrine for blood pressure control. It was at that moment that the bedside nurse astutely asked whether we should consider starting ECMO for the patient, as coauthor Dr. Arun Kannappan had done for a similar patient with asthma a month earlier. Dr. Vandivier notes, “My first response was that ECMO was not needed, because our patient had stabilized, and I had taken care of many patients like this in the past. But as I considered the situation more carefully, it was clear that any further decompensation could put our patient’s life at risk by not leaving enough time to start ECMO in a controlled setting. In short, my ‘traditional’ approach left little room for error in a patient with high ventilator pressures and hemodynamic instability.”

CHEST

ECMO is a technique used to add oxygen or remove CO₂ from the blood of people with different forms of respiratory failure (Fan E, et al. Intensive Care Med. 2016;2:712) that was first used by Hill and colleagues in 1966 for trauma-induced ARDS (Hill JD, et al. N Engl J Med. 1972;286:629). The ECMO circuit pumps blood from the venous system into an oxygenator that adds oxygen and removes CO₂ before blood is returned to either the venous or arterial circulation (Intensive Care Med. 2016;42:712). Venovenous ECMO (vvECMO) is used in clinical scenarios where only oxygenation and/or CO₂ removal is needed, whereas venoarterial ECMO (vaECMO) is reserved for situations where additional hemodynamic support is necessary. ECMO is traditionally thought of as a means to increase blood oxygenation, but it is less widely appreciated that ECMO is particularly effective at removing blood CO₂. In addition to ECMO helping to normalize oxygenation or eliminate CO₂, it can also be used to lower tidal volumes, decrease airway pressures, and allow “lungs to rest” with the goal of avoiding ventilator-induced lung injury (VILI).

CHEST

Standing at the bedside, it seemed to the authors that it was the right time to think about instituting a salvage therapy. But was there evidence that ECMO could improve survival? Were there clear guidelines for when to initiate ECMO, and was ECMO more effective than other salvage therapies such as inhaled volatile anesthetics?

Since McDonnell and colleagues first described the use of ECMO for a severe asthma exacerbation in 1981 (Ann Thoracic Surg. 1981;31[2]:171), about 95 articles have been published. Other than two registry studies and a recent epidemiologic study, all of these publications were case reports, case series, and reviews. Mikkelsen and colleagues (ASAIO J. 2009;55[1]:47) performed a retrospective, cohort study using the International Extracorporeal Life Support (ECLS) Organization Registry to determine whether ECMO use for status asthmaticus was associated with greater survival than the use of ECMO for other causes of respiratory failure. From 1986 through 2006, a total of 2,127 cases of respiratory failure were identified that required ECMO, including 27 for status asthmaticus and 1,233 for other causes. Their analysis showed that 83.3% of asthmatics treated with ECMO survived to hospital discharge, compared with 50.8% of people treated with ECMO for respiratory failure not due to asthma, with an odds ratio (OR) of 4.86 favoring survival of asthmatics (OR = 4.86; 95% CI, 1.65-14.31, P = .004).

Yeo and colleagues (Yeo HJ, et al. Critical Care. 2017;21:297) also used the ECLS Organization Registry to measure survival to hospital discharge, complications, and clinical factors associated with in-hospital mortality for asthmatics treated with ECMO. They included 272 people treated with ECMO for asthma between 1992 and 2016, after excluding people treated with ECMO for cardiopulmonary resuscitation or cardiac dysfunction. ECMO was associated with improvements in ventilator mechanics, including a reduction in respiratory rate, FiO₂, peak inspiratory pressure, mean airway pressure, and driving pressure. Use of ECMO for status asthmaticus was also associated with an 83.5% survival to hospital discharge, similar to the study by Mikkelsen and colleagues. Hemorrhage, the most common complication, occurred in roughly a quarter of people treated with ECMO. In the multivariate analysis, age, bleeding, pre-ECMO PEEP, post-ECMO FiO₂, and driving pressure were all associated with higher in-hospital mortality.

Although there are no formal criteria to guide use of ECMO for asthma exacerbations with respiratory failure, a number of physicians and a physician organization have recommended that ECMO be considered for persistently high ventilator pressures, uncontrolled respiratory acidosis, or hemodynamic instability. Because our patient qualified for ECMO based on all three suggested criteria, we consulted cardiac surgery who quickly started her on vvECMO. She remained on ECMO for 4 days until she was decannulated, extubated, and discharged home.

Despite this positive outcome, the lack of a high-quality, controlled study to help guide our decision was surprising given the ability of ECMO to efficiently remove CO₂ and to decrease ventilator pressures. The lack of guidance prompted us to perform a retrospective, epidemiologic cohort study to determine whether treatment with ECMO for asthma exacerbations with respiratory failure was associated with reduced mortality, compared with people treated without ECMO (Zakrajsek JK, Chest. 2023;163[1]:38). The study included 13,714 people admitted to an ECMO-capable hospital with respiratory failure that required invasive ventilation because of an asthma exacerbation between 2010 and 2020, of which 127 were treated with ECMO and 13,587 were not. During this period, use of ECMO as a salvage therapy for severe asthma exacerbations was a rare event, but it became more common over time. With the limitation that 40% of asthma patients were transferred from an outside hospital, 74% were started on ECMO in the first 2 hospital days, and 94% were started within the first week of hospitalization. Once started, ECMO was continued for a median of 1.0 day and range of 1-49 days. Hospital mortality was 14.6% in the ECMO group versus 26.2% in the no ECMO group, which equated to an 11.6% absolute risk reduction (P = 0.03) and 52% relative risk reduction (P = 0.04) in mortality. ECMO was associated with hospital costs that were $114,000 higher per patient, compared with the no ECMO group, but did not affect intensive care unit length of stay, hospital length of stay, or time on invasive mechanical ventilation.

We were pleased that our patient had a good outcome, and were reassured by our study results. But we were left to wonder whether ECMO really was the best salvage therapy for asthma exacerbations with respiratory failure, and if it was initiated for the right indications at the best time. These are important treatment considerations that take on new urgency given that physicians are increasingly looking to ECMO as a salvage therapy for refractory asthma, and the recent FDA approval of low-flow, extracorporeal CO₂ removal systems that could make CO₂ removal a more available, and perhaps less expensive, strategy. Despite promising epidemiological data, it will be important that these questions are answered with well-designed clinical trials so that physicians can be armed with the knowledge needed to navigate complex clinical scenarios, and ultimately to prevent unfortunate deaths from a reversible disease.

In our current society, it is likely that the “skinny patient with COPD” who walks into your clinic is less and less your “traditional” patient with COPD. We are seeing in our health care systems more of the “blue bloaters” – patients with COPD and significant obesity. This phenotype is representing what we are seeing worldwide as a consequence of the rising obesity prevalence. In the United States, the prepandemic (2017-2020) estimated percentage of adults over the age of 40 with obesity, defined as a body mass index (BMI) of at least 30 kg/m², was over 40%. Moreover, the estimated percentage of adults with morbid obesity (BMI at least 40 kg/m₂) is close to 10% (Akinbami, LJ et al. Vital Health Stat. 2022:190:1-36) and trending up. These patients with the “triple overlap” of morbid obesity, COPD, and awake daytime hypercapnia are being seen in clinics and in-hospital settings with increasing frequency, often presenting with complicating comorbidities such as acute respiratory failure, acute heart failure, kidney disease, or pulmonary hypertension. We are now faced with managing these patients with complex disease.

The obesity paradox does not seem applicable in the triple overlap phenotype. Patients with COPD who are overweight, defined as “mild obesity,” have lower mortality when compared with normal weight and underweight patients with COPD; however, this effect diminishes when BMI increases beyond 32 kg/m². With increasing obesity severity and aging, the risk of both obstructive sleep apnea (OSA) and hypoventilation increases. It is well documented that COPD-OSA overlap is linked to worse outcomes and that continuous positive airway pressure (CPAP) as first-line therapy decreases readmission rates and mortality. The triple overlap phenotypic patients, however, are presenting with chronic hypercapnic respiratory failure in a backdrop of morbid obesity, unlike the stable COPD-OSA overlap. The pathophysiology of hypoventilation in obesity is complex and multifactorial, and, although significant overlaps likely exist with comorbid COPD, by current definitions, to establish a diagnosis of obesity hypoventilation syndrome (OHS), one must have excluded other causes of hypoventilation, such as COPD.

These patients with the triple overlap of morbid obesity, awake daytime hypercapnia, and COPD are the subset of patients that providers struggle to fit in a diagnosis or in clinical research trials.
 

The triple overlap is a distinct syndrome

Different labels have been used in the medical literature: hypercapnic OSA-COPD overlap, morbid obesity and OSA-COPD overlap, hypercapnic morbidly obese COPD and OHS-COPD overlap. A better characterization of this distinctive phenotype is much needed. Patients with OSA-COPD overlap, for example, have an increased propensity to develop hypercapnia at higher FEV₁ when compared with COPD without OSA – but this is thought to be a consequence of prolonged and frequent apneas and hypopneas compounded with obesity-related central hypoventilation. We found that morbidly obese patients with OSA-COPD overlap have a higher hypoxia burden, more severe OSA, and are frequently prescribed noninvasive ventilation after a failed titration polysomnogram (Htun ZM, et al. Am J Respir Crit Care Med. 2019;199:A1382), perhaps signaling a distinctive phenotype with worse outcomes, but the study had the inherent limitations of a single-center, retrospective design lacking data on awake hypercapnia. On the other side, the term OHS-COPD is contradictory and confusing based on current OHS diagnostic criteria.

In standardizing diagnostic criteria for patients with this triple overlap syndrome, challenges remain: would the patient with a BMI of 70 kg/m² and fixed chronic airflow obstruction with FEV₁ 72% fall under the category of hypercapnic COPD vs OHS? Do these patients have worse outcomes regardless of their predominant feature? Would outcomes change if the apnea hypopnea index (AHI) is 10/h vs 65/h? More importantly, do patients with the triple overlap of COPD, morbid obesity, and daytime hypercapnia have worse outcomes when compared with hypercapnic COPD, or OHS with/without OSA? These questions can be better addressed once we agree on a definition. The patients with triple overlap syndrome have been traditionally excluded from clinical trials: the patient with morbid obesity has been excluded from chronic hypercapnic COPD clinical trials, and the patient with COPD has been excluded from OHS trials.

There are no specific clinical guidelines for this triple overlap phenotype. Positive airway pressure is the mainstay of treatment. CPAP is recommended as first-line therapy for patients with OSA-COPD overlap syndrome, while noninvasive ventilation (NIV) with bilevel positive airway pressure (BPAP) is recommended as first-line for the stable ambulatory hypercapnic patient with COPD. It is unclear if NIV is superior to CPAP in patients with triple overlap syndrome, although recently published data showed greater efficacy in reducing carbon dioxide (PaCO₂) and improving quality of life in a small group of subjects (Zheng et al. J Clin Sleep Med. 2022;18[1]:99-107). To take a step further, the subtleties of NIV set up, such as rise time and minimum inspiratory time, are contradictory: the goal in ventilating patients with COPD is to shorten inspiratory time, prolonging expiratory time, therefore allowing a shortened inspiratory cycle. In obesity, ventilation strategies aim to prolong and sustain inspiratory time to improve ventilation and dependent atelectasis. Another area of uncertainty is device selection. Should we aim to provide a respiratory assist device (RAD): the traditional, rent to own bilevel PAP without auto-expiratory positive airway pressure (EPAP) capabilities and lower maximum inspiratory pressure delivery capacity, vs a home mechanical ventilator at a higher expense, life-time rental, and one-way only data monitoring, which limits remote prescription adjustments, but allow auto-EPAP settings for patients with comorbid OSA? More importantly, how do we get these patients, who do not fit in any of the specified insurance criteria for PAP therapy approved for treatment?

A uniform diagnostic definition and clear taxonomy allows for resource allocation, from government funded grants for clinical trials to a better-informed distribution of health care systems resources and support health care policy changes to improve patient-centric outcomes. Here, we propose that the morbidly obese patient (BMI >40 kg/m2) with chronic airflow obstruction and a forced expiratory ratio (FEV₁/FVC) <0.7 with awake daytime hypercapnia (PaCO₂ > 45 mm Hg) represents a different entity/phenotype and fits best under the triple overlap syndrome taxonomy.

We suspect that these patients have worse outcomes, including comorbidity burden, quality of life, exacerbation rates, longer hospital length-of-stay, and respiratory and all-cause mortality. Large, multicenter, controlled trials comparing the long-term effectiveness of NIV and CPAP: measurements of respiratory function, gas exchange, blood pressure, and health related quality of life are needed. This is a group of patients that may specifically benefit from volume-targeted pressure support mode ventilation with auto-EPAP capabilities upon discharge from the hospital after an acute exacerbation.
 

Inpatient (sleep medicine) and outpatient transitions

In patients hospitalized with the triple overlap syndrome, there are certain considerations that are of special interest. Given comorbid hypercapnia and limited data on NIV superiority over CPAP, a sleep study should not be needed for NIV qualification. In addition, the medical team may consider the following (Figure 1):

1. Noninvasive Ventilation:

a. Maintaining a high-pressure support differential between inspiratory positive airway pressure (IPAP) and EPAP. This can usually be achieved at 8-10 cm H₂O, further adjusting to target a tidal volume (Vt) of 8 mL/kg of ideal body weight (IBW).

b. Higher EPAP: To overcome dependent atelectasis, improve ventilation-perfusion (VQ) matching, and better treat upper airway resistance both during wakefulness and sleep. Also, adjustments of EPAP at bedside should be considered to counteract auto-PEEP-related ineffective triggering if observed.

c. OSA screening and EPAP adjustment: for high residual obstructive apneas or hypopneas if data are available on the NIV device, or with the use of peripheral arterial tonometry sleep testing devices with NIV on overnight before discharge.

d. Does the patient meet criteria for oxygen supplementation at home? Wean oxygen off, if possible.

2. Case-managers can help establish services with a durable medical equipment provider with expertise in advanced PAP devices.3. Obesity management, Consider referral to an obesity management program for lifestyle/dietary modifications along with pharmacotherapy or bariatric surgery interventions.

4. Close follow-up, track exacerbations. Device download data are crucial to monitor adherence/tolerance and treatment effectiveness with particular interest in AHI, oximetry, and CO₂ trends monitoring. Some patients may need dedicated titration polysomnograms to adjust ventilation settings, for optimization of residual OSA or for oxygen addition or discontinuation.
 

Conclusion

Patients with the triple overlap phenotype have not been systematically defined, studied, or included in clinical trials. We anticipate that these patients have worse outcomes: quality of life, symptom and comorbidity burden, exacerbation rates, in-hospital mortality, longer hospital stay and ICU stay, and respiratory and all-cause mortality. This is a group of patients that may specifically benefit from domiciliary NIV set-up upon discharge from the hospital with close follow-up. Properly identifying these patients will help pulmonologists and health care systems direct resources to optimally manage this complex group of patients. Funding of research trials to support clinical guidelines development should be prioritized. Triple overlap syndrome is different from COPD-OSA overlap, OHS with moderate to severe OSA, or OHS without significant OSA.

In our current society, it is likely that the “skinny patient with COPD” who walks into your clinic is less and less your “traditional” patient with COPD. We are seeing in our health care systems more of the “blue bloaters” – patients with COPD and significant obesity. This phenotype is representing what we are seeing worldwide as a consequence of the rising obesity prevalence. In the United States, the prepandemic (2017-2020) estimated percentage of adults over the age of 40 with obesity, defined as a body mass index (BMI) of at least 30 kg/m², was over 40%. Moreover, the estimated percentage of adults with morbid obesity (BMI at least 40 kg/m₂) is close to 10% (Akinbami, LJ et al. Vital Health Stat. 2022:190:1-36) and trending up. These patients with the “triple overlap” of morbid obesity, COPD, and awake daytime hypercapnia are being seen in clinics and in-hospital settings with increasing frequency, often presenting with complicating comorbidities such as acute respiratory failure, acute heart failure, kidney disease, or pulmonary hypertension. We are now faced with managing these patients with complex disease.

The obesity paradox does not seem applicable in the triple overlap phenotype. Patients with COPD who are overweight, defined as “mild obesity,” have lower mortality when compared with normal weight and underweight patients with COPD; however, this effect diminishes when BMI increases beyond 32 kg/m². With increasing obesity severity and aging, the risk of both obstructive sleep apnea (OSA) and hypoventilation increases. It is well documented that COPD-OSA overlap is linked to worse outcomes and that continuous positive airway pressure (CPAP) as first-line therapy decreases readmission rates and mortality. The triple overlap phenotypic patients, however, are presenting with chronic hypercapnic respiratory failure in a backdrop of morbid obesity, unlike the stable COPD-OSA overlap. The pathophysiology of hypoventilation in obesity is complex and multifactorial, and, although significant overlaps likely exist with comorbid COPD, by current definitions, to establish a diagnosis of obesity hypoventilation syndrome (OHS), one must have excluded other causes of hypoventilation, such as COPD.

These patients with the triple overlap of morbid obesity, awake daytime hypercapnia, and COPD are the subset of patients that providers struggle to fit in a diagnosis or in clinical research trials.
 

The triple overlap is a distinct syndrome

Different labels have been used in the medical literature: hypercapnic OSA-COPD overlap, morbid obesity and OSA-COPD overlap, hypercapnic morbidly obese COPD and OHS-COPD overlap. A better characterization of this distinctive phenotype is much needed. Patients with OSA-COPD overlap, for example, have an increased propensity to develop hypercapnia at higher FEV₁ when compared with COPD without OSA – but this is thought to be a consequence of prolonged and frequent apneas and hypopneas compounded with obesity-related central hypoventilation. We found that morbidly obese patients with OSA-COPD overlap have a higher hypoxia burden, more severe OSA, and are frequently prescribed noninvasive ventilation after a failed titration polysomnogram (Htun ZM, et al. Am J Respir Crit Care Med. 2019;199:A1382), perhaps signaling a distinctive phenotype with worse outcomes, but the study had the inherent limitations of a single-center, retrospective design lacking data on awake hypercapnia. On the other side, the term OHS-COPD is contradictory and confusing based on current OHS diagnostic criteria.

In standardizing diagnostic criteria for patients with this triple overlap syndrome, challenges remain: would the patient with a BMI of 70 kg/m² and fixed chronic airflow obstruction with FEV₁ 72% fall under the category of hypercapnic COPD vs OHS? Do these patients have worse outcomes regardless of their predominant feature? Would outcomes change if the apnea hypopnea index (AHI) is 10/h vs 65/h? More importantly, do patients with the triple overlap of COPD, morbid obesity, and daytime hypercapnia have worse outcomes when compared with hypercapnic COPD, or OHS with/without OSA? These questions can be better addressed once we agree on a definition. The patients with triple overlap syndrome have been traditionally excluded from clinical trials: the patient with morbid obesity has been excluded from chronic hypercapnic COPD clinical trials, and the patient with COPD has been excluded from OHS trials.

There are no specific clinical guidelines for this triple overlap phenotype. Positive airway pressure is the mainstay of treatment. CPAP is recommended as first-line therapy for patients with OSA-COPD overlap syndrome, while noninvasive ventilation (NIV) with bilevel positive airway pressure (BPAP) is recommended as first-line for the stable ambulatory hypercapnic patient with COPD. It is unclear if NIV is superior to CPAP in patients with triple overlap syndrome, although recently published data showed greater efficacy in reducing carbon dioxide (PaCO₂) and improving quality of life in a small group of subjects (Zheng et al. J Clin Sleep Med. 2022;18[1]:99-107). To take a step further, the subtleties of NIV set up, such as rise time and minimum inspiratory time, are contradictory: the goal in ventilating patients with COPD is to shorten inspiratory time, prolonging expiratory time, therefore allowing a shortened inspiratory cycle. In obesity, ventilation strategies aim to prolong and sustain inspiratory time to improve ventilation and dependent atelectasis. Another area of uncertainty is device selection. Should we aim to provide a respiratory assist device (RAD): the traditional, rent to own bilevel PAP without auto-expiratory positive airway pressure (EPAP) capabilities and lower maximum inspiratory pressure delivery capacity, vs a home mechanical ventilator at a higher expense, life-time rental, and one-way only data monitoring, which limits remote prescription adjustments, but allow auto-EPAP settings for patients with comorbid OSA? More importantly, how do we get these patients, who do not fit in any of the specified insurance criteria for PAP therapy approved for treatment?

A uniform diagnostic definition and clear taxonomy allows for resource allocation, from government funded grants for clinical trials to a better-informed distribution of health care systems resources and support health care policy changes to improve patient-centric outcomes. Here, we propose that the morbidly obese patient (BMI >40 kg/m2) with chronic airflow obstruction and a forced expiratory ratio (FEV₁/FVC) <0.7 with awake daytime hypercapnia (PaCO₂ > 45 mm Hg) represents a different entity/phenotype and fits best under the triple overlap syndrome taxonomy.

We suspect that these patients have worse outcomes, including comorbidity burden, quality of life, exacerbation rates, longer hospital length-of-stay, and respiratory and all-cause mortality. Large, multicenter, controlled trials comparing the long-term effectiveness of NIV and CPAP: measurements of respiratory function, gas exchange, blood pressure, and health related quality of life are needed. This is a group of patients that may specifically benefit from volume-targeted pressure support mode ventilation with auto-EPAP capabilities upon discharge from the hospital after an acute exacerbation.
 

Inpatient (sleep medicine) and outpatient transitions

In patients hospitalized with the triple overlap syndrome, there are certain considerations that are of special interest. Given comorbid hypercapnia and limited data on NIV superiority over CPAP, a sleep study should not be needed for NIV qualification. In addition, the medical team may consider the following (Figure 1):

1. Noninvasive Ventilation:

a. Maintaining a high-pressure support differential between inspiratory positive airway pressure (IPAP) and EPAP. This can usually be achieved at 8-10 cm H₂O, further adjusting to target a tidal volume (Vt) of 8 mL/kg of ideal body weight (IBW).

b. Higher EPAP: To overcome dependent atelectasis, improve ventilation-perfusion (VQ) matching, and better treat upper airway resistance both during wakefulness and sleep. Also, adjustments of EPAP at bedside should be considered to counteract auto-PEEP-related ineffective triggering if observed.

c. OSA screening and EPAP adjustment: for high residual obstructive apneas or hypopneas if data are available on the NIV device, or with the use of peripheral arterial tonometry sleep testing devices with NIV on overnight before discharge.

d. Does the patient meet criteria for oxygen supplementation at home? Wean oxygen off, if possible.

2. Case-managers can help establish services with a durable medical equipment provider with expertise in advanced PAP devices.3. Obesity management, Consider referral to an obesity management program for lifestyle/dietary modifications along with pharmacotherapy or bariatric surgery interventions.

4. Close follow-up, track exacerbations. Device download data are crucial to monitor adherence/tolerance and treatment effectiveness with particular interest in AHI, oximetry, and CO₂ trends monitoring. Some patients may need dedicated titration polysomnograms to adjust ventilation settings, for optimization of residual OSA or for oxygen addition or discontinuation.
 

Conclusion

Patients with the triple overlap phenotype have not been systematically defined, studied, or included in clinical trials. We anticipate that these patients have worse outcomes: quality of life, symptom and comorbidity burden, exacerbation rates, in-hospital mortality, longer hospital stay and ICU stay, and respiratory and all-cause mortality. This is a group of patients that may specifically benefit from domiciliary NIV set-up upon discharge from the hospital with close follow-up. Properly identifying these patients will help pulmonologists and health care systems direct resources to optimally manage this complex group of patients. Funding of research trials to support clinical guidelines development should be prioritized. Triple overlap syndrome is different from COPD-OSA overlap, OHS with moderate to severe OSA, or OHS without significant OSA.

In our current society, it is likely that the “skinny patient with COPD” who walks into your clinic is less and less your “traditional” patient with COPD. We are seeing in our health care systems more of the “blue bloaters” – patients with COPD and significant obesity. This phenotype is representing what we are seeing worldwide as a consequence of the rising obesity prevalence. In the United States, the prepandemic (2017-2020) estimated percentage of adults over the age of 40 with obesity, defined as a body mass index (BMI) of at least 30 kg/m², was over 40%. Moreover, the estimated percentage of adults with morbid obesity (BMI at least 40 kg/m₂) is close to 10% (Akinbami, LJ et al. Vital Health Stat. 2022:190:1-36) and trending up. These patients with the “triple overlap” of morbid obesity, COPD, and awake daytime hypercapnia are being seen in clinics and in-hospital settings with increasing frequency, often presenting with complicating comorbidities such as acute respiratory failure, acute heart failure, kidney disease, or pulmonary hypertension. We are now faced with managing these patients with complex disease.

The obesity paradox does not seem applicable in the triple overlap phenotype. Patients with COPD who are overweight, defined as “mild obesity,” have lower mortality when compared with normal weight and underweight patients with COPD; however, this effect diminishes when BMI increases beyond 32 kg/m². With increasing obesity severity and aging, the risk of both obstructive sleep apnea (OSA) and hypoventilation increases. It is well documented that COPD-OSA overlap is linked to worse outcomes and that continuous positive airway pressure (CPAP) as first-line therapy decreases readmission rates and mortality. The triple overlap phenotypic patients, however, are presenting with chronic hypercapnic respiratory failure in a backdrop of morbid obesity, unlike the stable COPD-OSA overlap. The pathophysiology of hypoventilation in obesity is complex and multifactorial, and, although significant overlaps likely exist with comorbid COPD, by current definitions, to establish a diagnosis of obesity hypoventilation syndrome (OHS), one must have excluded other causes of hypoventilation, such as COPD.

These patients with the triple overlap of morbid obesity, awake daytime hypercapnia, and COPD are the subset of patients that providers struggle to fit in a diagnosis or in clinical research trials.
 

The triple overlap is a distinct syndrome

Different labels have been used in the medical literature: hypercapnic OSA-COPD overlap, morbid obesity and OSA-COPD overlap, hypercapnic morbidly obese COPD and OHS-COPD overlap. A better characterization of this distinctive phenotype is much needed. Patients with OSA-COPD overlap, for example, have an increased propensity to develop hypercapnia at higher FEV₁ when compared with COPD without OSA – but this is thought to be a consequence of prolonged and frequent apneas and hypopneas compounded with obesity-related central hypoventilation. We found that morbidly obese patients with OSA-COPD overlap have a higher hypoxia burden, more severe OSA, and are frequently prescribed noninvasive ventilation after a failed titration polysomnogram (Htun ZM, et al. Am J Respir Crit Care Med. 2019;199:A1382), perhaps signaling a distinctive phenotype with worse outcomes, but the study had the inherent limitations of a single-center, retrospective design lacking data on awake hypercapnia. On the other side, the term OHS-COPD is contradictory and confusing based on current OHS diagnostic criteria.

In standardizing diagnostic criteria for patients with this triple overlap syndrome, challenges remain: would the patient with a BMI of 70 kg/m² and fixed chronic airflow obstruction with FEV₁ 72% fall under the category of hypercapnic COPD vs OHS? Do these patients have worse outcomes regardless of their predominant feature? Would outcomes change if the apnea hypopnea index (AHI) is 10/h vs 65/h? More importantly, do patients with the triple overlap of COPD, morbid obesity, and daytime hypercapnia have worse outcomes when compared with hypercapnic COPD, or OHS with/without OSA? These questions can be better addressed once we agree on a definition. The patients with triple overlap syndrome have been traditionally excluded from clinical trials: the patient with morbid obesity has been excluded from chronic hypercapnic COPD clinical trials, and the patient with COPD has been excluded from OHS trials.

There are no specific clinical guidelines for this triple overlap phenotype. Positive airway pressure is the mainstay of treatment. CPAP is recommended as first-line therapy for patients with OSA-COPD overlap syndrome, while noninvasive ventilation (NIV) with bilevel positive airway pressure (BPAP) is recommended as first-line for the stable ambulatory hypercapnic patient with COPD. It is unclear if NIV is superior to CPAP in patients with triple overlap syndrome, although recently published data showed greater efficacy in reducing carbon dioxide (PaCO₂) and improving quality of life in a small group of subjects (Zheng et al. J Clin Sleep Med. 2022;18[1]:99-107). To take a step further, the subtleties of NIV set up, such as rise time and minimum inspiratory time, are contradictory: the goal in ventilating patients with COPD is to shorten inspiratory time, prolonging expiratory time, therefore allowing a shortened inspiratory cycle. In obesity, ventilation strategies aim to prolong and sustain inspiratory time to improve ventilation and dependent atelectasis. Another area of uncertainty is device selection. Should we aim to provide a respiratory assist device (RAD): the traditional, rent to own bilevel PAP without auto-expiratory positive airway pressure (EPAP) capabilities and lower maximum inspiratory pressure delivery capacity, vs a home mechanical ventilator at a higher expense, life-time rental, and one-way only data monitoring, which limits remote prescription adjustments, but allow auto-EPAP settings for patients with comorbid OSA? More importantly, how do we get these patients, who do not fit in any of the specified insurance criteria for PAP therapy approved for treatment?

A uniform diagnostic definition and clear taxonomy allows for resource allocation, from government funded grants for clinical trials to a better-informed distribution of health care systems resources and support health care policy changes to improve patient-centric outcomes. Here, we propose that the morbidly obese patient (BMI >40 kg/m2) with chronic airflow obstruction and a forced expiratory ratio (FEV₁/FVC) <0.7 with awake daytime hypercapnia (PaCO₂ > 45 mm Hg) represents a different entity/phenotype and fits best under the triple overlap syndrome taxonomy.

We suspect that these patients have worse outcomes, including comorbidity burden, quality of life, exacerbation rates, longer hospital length-of-stay, and respiratory and all-cause mortality. Large, multicenter, controlled trials comparing the long-term effectiveness of NIV and CPAP: measurements of respiratory function, gas exchange, blood pressure, and health related quality of life are needed. This is a group of patients that may specifically benefit from volume-targeted pressure support mode ventilation with auto-EPAP capabilities upon discharge from the hospital after an acute exacerbation.
 

Inpatient (sleep medicine) and outpatient transitions

In patients hospitalized with the triple overlap syndrome, there are certain considerations that are of special interest. Given comorbid hypercapnia and limited data on NIV superiority over CPAP, a sleep study should not be needed for NIV qualification. In addition, the medical team may consider the following (Figure 1):

1. Noninvasive Ventilation:

a. Maintaining a high-pressure support differential between inspiratory positive airway pressure (IPAP) and EPAP. This can usually be achieved at 8-10 cm H₂O, further adjusting to target a tidal volume (Vt) of 8 mL/kg of ideal body weight (IBW).

b. Higher EPAP: To overcome dependent atelectasis, improve ventilation-perfusion (VQ) matching, and better treat upper airway resistance both during wakefulness and sleep. Also, adjustments of EPAP at bedside should be considered to counteract auto-PEEP-related ineffective triggering if observed.

c. OSA screening and EPAP adjustment: for high residual obstructive apneas or hypopneas if data are available on the NIV device, or with the use of peripheral arterial tonometry sleep testing devices with NIV on overnight before discharge.

d. Does the patient meet criteria for oxygen supplementation at home? Wean oxygen off, if possible.

2. Case-managers can help establish services with a durable medical equipment provider with expertise in advanced PAP devices.3. Obesity management, Consider referral to an obesity management program for lifestyle/dietary modifications along with pharmacotherapy or bariatric surgery interventions.

4. Close follow-up, track exacerbations. Device download data are crucial to monitor adherence/tolerance and treatment effectiveness with particular interest in AHI, oximetry, and CO₂ trends monitoring. Some patients may need dedicated titration polysomnograms to adjust ventilation settings, for optimization of residual OSA or for oxygen addition or discontinuation.
 

Conclusion

Patients with the triple overlap phenotype have not been systematically defined, studied, or included in clinical trials. We anticipate that these patients have worse outcomes: quality of life, symptom and comorbidity burden, exacerbation rates, in-hospital mortality, longer hospital stay and ICU stay, and respiratory and all-cause mortality. This is a group of patients that may specifically benefit from domiciliary NIV set-up upon discharge from the hospital with close follow-up. Properly identifying these patients will help pulmonologists and health care systems direct resources to optimally manage this complex group of patients. Funding of research trials to support clinical guidelines development should be prioritized. Triple overlap syndrome is different from COPD-OSA overlap, OHS with moderate to severe OSA, or OHS without significant OSA.

Since the first SARS-CoV-2 (COVID-19) outbreak in Wuhan, China, in December 2019, more than 6.6 million deaths have occurred. Management strategies for patients with COVID-19 pneumonia/ARDS have continued to evolve during the pandemic. One of the strategies for those cases refractory to traditional ARDS treatments has been the use of extracorporeal membrane oxygenation (ECMO).

Before the COVID-19 pandemic, a substantial amount of data regarding the use of ECMO in ARDS was gathered during the H1N1 influenza outbreak in 2009. Mortality ranged from 8% to 65% (Zangrillo, et al. Crit Care. 2013;17[1]:R30). From these data, we learned the importance of patient selection. Young patients with few co-morbidities and less than 7 days supported by mechanical ventilation did remarkably better than elderly patients or those who had prolonged positive-pressure ventilation prior to ECMO.  

To date, the mortality rate for COVID-19 patients with ARDS requiring ECMO is 48% based on data from ELSO. Interestingly though, using May 1, 2020, as a cutoff date, mortality rates for patients with COVID-19 receiving ECMO significantly increased from 37% to 52% (Barbaro, et al. Lancet. 2021;398[10307]:1230). This escalation in mortality engendered concern that ECMO may not be useful in treating patients with COVID-19 and ARDS.

Several factors can be cited for this increase in mortality. First, many new ECMO programs launched after May 1. These new programs had a higher mortality rate (59%) compared with established programs, suggesting that program and provider experience play a significant role in patient outcomes (Barbaro, et al. Lancet. 2021;398[10307]:1230). Second, patients in the latter part of 2020 experienced much longer intervals between the onset of symptoms and time of intubation. Clinicians had a tendency to delay intubation as long as possible. Subsequently, the number of days receiving high flow nasal oxygen or noninvasive ventilation (NIV) was significantly longer (Schmidt, et al. Crit Care. 2021;25[1]:355). These data suggest that prolonged NIV on high Fio2 may be a negative prognostic indicator and should be considered when assessing a patient’s candidacy for ECMO.

Early in the pandemic, clinicians realized that average ECMO run times for patients with COVID-19 and ARDS were significantly longer, 15 vs 9 days, respectively (Jacobs, et al. Ann Thorac Surg. 2022;113[5]:1452). With such long run times, beds were slow to turn over, and a shortage of ECMO beds resulted during the height of the pandemic. In a retrospective study, Gannon looked at 90 patients, all of whom were deemed medically appropriate for ECMO. Two groups were created: (1) no capacity for ECMO vs (2) ECMO provided. Mortality rates were staggering at 89% and 43%, respectively (P =.001) (Gannon, et al. Am J Respir Crit Care Med. 2022;205[11]:1354). This study demonstrated a profound point: during a pandemic, when demand overcomes supply, there is a unique opportunity to see the effect of lifesaving therapies, such as ECMO, on outcomes. This study was particularly poignant, as the average age of the patients was 40 years old.  

It is now widely accepted that prone positioning has survival benefit in ARDS. Prone positioning while receiving ECMO has generally been avoided due to concern for potential complications associated with the cannula(s). However, it has been shown that prone positioning while receiving veno-venous (VV) -ECMO reduces mortality rates, 37% proned vs 50% supine positioning (P =.02) (Giani, et al. Ann Am Thorac Soc. 2021;18[3]:495). In this study, no major complications occurred, and minor complications occurred in 6% of the proning events. Prone positioning improves ventilation-perfusion mismatch and reduces hypoxic vasoconstriction, which is thought to be right-sided heart-protective.  

Right-sided heart dysfunction (RHD) is common in ARDS, whether COVID-19-related or not. The pathogenesis includes hypoxic vasoconstriction, pulmonary fibrosis, and ventilator-induced lung injury. Pulmonary microthrombi and patient-specific characteristics, such as obesity, are additional factors leading to RHD in patients with COVID-19. During the pandemic, several articles described using right-sided heart protective cannulation strategies for patients with COVID-19 requiring ECMO with favorable results (Mustafa, et al. JAMA Surg. 2020;155[10]:990; Cain, et al. J Surg Res. 2021;264:81-89). This right-sided heart protective strategy involves inserting a single access dual lumen cannula into the right internal jugular vein, which is advanced into the pulmonary artery, effectively bypassing the right ventricle. This setup is more typical of right ventricle assist device (RVAD), rather than typical VV-ECMO, which returns blood to the right atrium. Unfortunately, these studies did not include echocardiographic information to evaluate the effects of this intervention on RVD, and this is an area for future research. However, this vein to pulmonary artery strategy was found to facilitate decreased sedation, earlier liberation from mechanical ventilation, reduced need for tracheostomy, improved mobilization out of bed, and ease in prone positioning (Mustafa, et al. JAMA Surg. 2020;155[10]:990).

In conclusion, there is evidence to support the use of ECMO in patients with COVID-19 patients and ARDS failing conventional mechanical ventilation. The success of ECMO therapy is highly dependent on patient selection. Prolonged use of NIV on high Fio2 may be a negative predictor of ECMO survival and should be considered when assessing a patient for ECMO candidacy. Prone positioning with ECMO has been shown to have survival benefit and should be considered in all patients receiving ECMO.
 

Dr. Gaillard, Dr. Staples, and Dr. Kapoor are with the Department of Anesthesiology, Section on Critical Care, at Wake Forest School of Medicine in Winston-Salem, N.C. Dr. Gaillard is also with the Department of Emergency Medicine and Department of Internal Medicine, Section on Pulmonary, Critical Care, Allergy, and Immunology at Wake Forest School of Medicine.

Since the first SARS-CoV-2 (COVID-19) outbreak in Wuhan, China, in December 2019, more than 6.6 million deaths have occurred. Management strategies for patients with COVID-19 pneumonia/ARDS have continued to evolve during the pandemic. One of the strategies for those cases refractory to traditional ARDS treatments has been the use of extracorporeal membrane oxygenation (ECMO).

Before the COVID-19 pandemic, a substantial amount of data regarding the use of ECMO in ARDS was gathered during the H1N1 influenza outbreak in 2009. Mortality ranged from 8% to 65% (Zangrillo, et al. Crit Care. 2013;17[1]:R30). From these data, we learned the importance of patient selection. Young patients with few co-morbidities and less than 7 days supported by mechanical ventilation did remarkably better than elderly patients or those who had prolonged positive-pressure ventilation prior to ECMO.  

To date, the mortality rate for COVID-19 patients with ARDS requiring ECMO is 48% based on data from ELSO. Interestingly though, using May 1, 2020, as a cutoff date, mortality rates for patients with COVID-19 receiving ECMO significantly increased from 37% to 52% (Barbaro, et al. Lancet. 2021;398[10307]:1230). This escalation in mortality engendered concern that ECMO may not be useful in treating patients with COVID-19 and ARDS.

Several factors can be cited for this increase in mortality. First, many new ECMO programs launched after May 1. These new programs had a higher mortality rate (59%) compared with established programs, suggesting that program and provider experience play a significant role in patient outcomes (Barbaro, et al. Lancet. 2021;398[10307]:1230). Second, patients in the latter part of 2020 experienced much longer intervals between the onset of symptoms and time of intubation. Clinicians had a tendency to delay intubation as long as possible. Subsequently, the number of days receiving high flow nasal oxygen or noninvasive ventilation (NIV) was significantly longer (Schmidt, et al. Crit Care. 2021;25[1]:355). These data suggest that prolonged NIV on high Fio2 may be a negative prognostic indicator and should be considered when assessing a patient’s candidacy for ECMO.

Early in the pandemic, clinicians realized that average ECMO run times for patients with COVID-19 and ARDS were significantly longer, 15 vs 9 days, respectively (Jacobs, et al. Ann Thorac Surg. 2022;113[5]:1452). With such long run times, beds were slow to turn over, and a shortage of ECMO beds resulted during the height of the pandemic. In a retrospective study, Gannon looked at 90 patients, all of whom were deemed medically appropriate for ECMO. Two groups were created: (1) no capacity for ECMO vs (2) ECMO provided. Mortality rates were staggering at 89% and 43%, respectively (P =.001) (Gannon, et al. Am J Respir Crit Care Med. 2022;205[11]:1354). This study demonstrated a profound point: during a pandemic, when demand overcomes supply, there is a unique opportunity to see the effect of lifesaving therapies, such as ECMO, on outcomes. This study was particularly poignant, as the average age of the patients was 40 years old.  

It is now widely accepted that prone positioning has survival benefit in ARDS. Prone positioning while receiving ECMO has generally been avoided due to concern for potential complications associated with the cannula(s). However, it has been shown that prone positioning while receiving veno-venous (VV) -ECMO reduces mortality rates, 37% proned vs 50% supine positioning (P =.02) (Giani, et al. Ann Am Thorac Soc. 2021;18[3]:495). In this study, no major complications occurred, and minor complications occurred in 6% of the proning events. Prone positioning improves ventilation-perfusion mismatch and reduces hypoxic vasoconstriction, which is thought to be right-sided heart-protective.  

Right-sided heart dysfunction (RHD) is common in ARDS, whether COVID-19-related or not. The pathogenesis includes hypoxic vasoconstriction, pulmonary fibrosis, and ventilator-induced lung injury. Pulmonary microthrombi and patient-specific characteristics, such as obesity, are additional factors leading to RHD in patients with COVID-19. During the pandemic, several articles described using right-sided heart protective cannulation strategies for patients with COVID-19 requiring ECMO with favorable results (Mustafa, et al. JAMA Surg. 2020;155[10]:990; Cain, et al. J Surg Res. 2021;264:81-89). This right-sided heart protective strategy involves inserting a single access dual lumen cannula into the right internal jugular vein, which is advanced into the pulmonary artery, effectively bypassing the right ventricle. This setup is more typical of right ventricle assist device (RVAD), rather than typical VV-ECMO, which returns blood to the right atrium. Unfortunately, these studies did not include echocardiographic information to evaluate the effects of this intervention on RVD, and this is an area for future research. However, this vein to pulmonary artery strategy was found to facilitate decreased sedation, earlier liberation from mechanical ventilation, reduced need for tracheostomy, improved mobilization out of bed, and ease in prone positioning (Mustafa, et al. JAMA Surg. 2020;155[10]:990).

In conclusion, there is evidence to support the use of ECMO in patients with COVID-19 patients and ARDS failing conventional mechanical ventilation. The success of ECMO therapy is highly dependent on patient selection. Prolonged use of NIV on high Fio2 may be a negative predictor of ECMO survival and should be considered when assessing a patient for ECMO candidacy. Prone positioning with ECMO has been shown to have survival benefit and should be considered in all patients receiving ECMO.
 

Dr. Gaillard, Dr. Staples, and Dr. Kapoor are with the Department of Anesthesiology, Section on Critical Care, at Wake Forest School of Medicine in Winston-Salem, N.C. Dr. Gaillard is also with the Department of Emergency Medicine and Department of Internal Medicine, Section on Pulmonary, Critical Care, Allergy, and Immunology at Wake Forest School of Medicine.

Since the first SARS-CoV-2 (COVID-19) outbreak in Wuhan, China, in December 2019, more than 6.6 million deaths have occurred. Management strategies for patients with COVID-19 pneumonia/ARDS have continued to evolve during the pandemic. One of the strategies for those cases refractory to traditional ARDS treatments has been the use of extracorporeal membrane oxygenation (ECMO).

Before the COVID-19 pandemic, a substantial amount of data regarding the use of ECMO in ARDS was gathered during the H1N1 influenza outbreak in 2009. Mortality ranged from 8% to 65% (Zangrillo, et al. Crit Care. 2013;17[1]:R30). From these data, we learned the importance of patient selection. Young patients with few co-morbidities and less than 7 days supported by mechanical ventilation did remarkably better than elderly patients or those who had prolonged positive-pressure ventilation prior to ECMO.  

To date, the mortality rate for COVID-19 patients with ARDS requiring ECMO is 48% based on data from ELSO. Interestingly though, using May 1, 2020, as a cutoff date, mortality rates for patients with COVID-19 receiving ECMO significantly increased from 37% to 52% (Barbaro, et al. Lancet. 2021;398[10307]:1230). This escalation in mortality engendered concern that ECMO may not be useful in treating patients with COVID-19 and ARDS.

Several factors can be cited for this increase in mortality. First, many new ECMO programs launched after May 1. These new programs had a higher mortality rate (59%) compared with established programs, suggesting that program and provider experience play a significant role in patient outcomes (Barbaro, et al. Lancet. 2021;398[10307]:1230). Second, patients in the latter part of 2020 experienced much longer intervals between the onset of symptoms and time of intubation. Clinicians had a tendency to delay intubation as long as possible. Subsequently, the number of days receiving high flow nasal oxygen or noninvasive ventilation (NIV) was significantly longer (Schmidt, et al. Crit Care. 2021;25[1]:355). These data suggest that prolonged NIV on high Fio2 may be a negative prognostic indicator and should be considered when assessing a patient’s candidacy for ECMO.

Early in the pandemic, clinicians realized that average ECMO run times for patients with COVID-19 and ARDS were significantly longer, 15 vs 9 days, respectively (Jacobs, et al. Ann Thorac Surg. 2022;113[5]:1452). With such long run times, beds were slow to turn over, and a shortage of ECMO beds resulted during the height of the pandemic. In a retrospective study, Gannon looked at 90 patients, all of whom were deemed medically appropriate for ECMO. Two groups were created: (1) no capacity for ECMO vs (2) ECMO provided. Mortality rates were staggering at 89% and 43%, respectively (P =.001) (Gannon, et al. Am J Respir Crit Care Med. 2022;205[11]:1354). This study demonstrated a profound point: during a pandemic, when demand overcomes supply, there is a unique opportunity to see the effect of lifesaving therapies, such as ECMO, on outcomes. This study was particularly poignant, as the average age of the patients was 40 years old.  

It is now widely accepted that prone positioning has survival benefit in ARDS. Prone positioning while receiving ECMO has generally been avoided due to concern for potential complications associated with the cannula(s). However, it has been shown that prone positioning while receiving veno-venous (VV) -ECMO reduces mortality rates, 37% proned vs 50% supine positioning (P =.02) (Giani, et al. Ann Am Thorac Soc. 2021;18[3]:495). In this study, no major complications occurred, and minor complications occurred in 6% of the proning events. Prone positioning improves ventilation-perfusion mismatch and reduces hypoxic vasoconstriction, which is thought to be right-sided heart-protective.  

Right-sided heart dysfunction (RHD) is common in ARDS, whether COVID-19-related or not. The pathogenesis includes hypoxic vasoconstriction, pulmonary fibrosis, and ventilator-induced lung injury. Pulmonary microthrombi and patient-specific characteristics, such as obesity, are additional factors leading to RHD in patients with COVID-19. During the pandemic, several articles described using right-sided heart protective cannulation strategies for patients with COVID-19 requiring ECMO with favorable results (Mustafa, et al. JAMA Surg. 2020;155[10]:990; Cain, et al. J Surg Res. 2021;264:81-89). This right-sided heart protective strategy involves inserting a single access dual lumen cannula into the right internal jugular vein, which is advanced into the pulmonary artery, effectively bypassing the right ventricle. This setup is more typical of right ventricle assist device (RVAD), rather than typical VV-ECMO, which returns blood to the right atrium. Unfortunately, these studies did not include echocardiographic information to evaluate the effects of this intervention on RVD, and this is an area for future research. However, this vein to pulmonary artery strategy was found to facilitate decreased sedation, earlier liberation from mechanical ventilation, reduced need for tracheostomy, improved mobilization out of bed, and ease in prone positioning (Mustafa, et al. JAMA Surg. 2020;155[10]:990).

In conclusion, there is evidence to support the use of ECMO in patients with COVID-19 patients and ARDS failing conventional mechanical ventilation. The success of ECMO therapy is highly dependent on patient selection. Prolonged use of NIV on high Fio2 may be a negative predictor of ECMO survival and should be considered when assessing a patient for ECMO candidacy. Prone positioning with ECMO has been shown to have survival benefit and should be considered in all patients receiving ECMO.
 

Dr. Gaillard, Dr. Staples, and Dr. Kapoor are with the Department of Anesthesiology, Section on Critical Care, at Wake Forest School of Medicine in Winston-Salem, N.C. Dr. Gaillard is also with the Department of Emergency Medicine and Department of Internal Medicine, Section on Pulmonary, Critical Care, Allergy, and Immunology at Wake Forest School of Medicine.

The European Respiratory Society (ERS) and American Thoracic Society (ATS) just published an update to their guidelines on lung function interpretation (Stanojevic S, et al. Eur Respir J. 2022; 60: 2101499). As with any update, the document builds on past work and integrates new advances the field has seen since 2005.

The current iteration comes at a time when academics, clinicians, and epidemiologists are re-analyzing what we think we know about the complex ways race and ethnicity intersect with the practice of medicine. Several experts on lung function testing, many if not most of whom are authors on the ERS/ATS guideline, have written letters or published reviews commenting on the way accounting for race or ethnicity affects lung function interpretation.

Race/ethnicity and lung function was also the topic of an excellent session at the recent CHEST 2022 Annual Meeting in Nashville, Tennessee. Here, we’ll provide a brief review and direct the reader to relevant sources for a more detailed analysis.

Spirometry is an integral part of the diagnosis and management of a wide range of pulmonary conditions. Dr. Aaron Baugh from the University of California San Francisco (UCSF) lectured on the spirometer’s history at CHEST 2022 and detailed its interactions with race over the past 2 centuries. Other authors have chronicled this history, as well (Braun L, et al. Can J Respir Ther. 2015;51[4]:99-101). The short version is that since the British surgeon John Hutchinson created the first spirometer in 1846, race has been a part of the discussion of lung function interpretation.

In 2022, we know far more about the factors that determine lung function than we did in the 19th century. Age, height, and sex assigned at birth all explain a high percentage of the variability seen in FEV1 and FVC. When modeled, race also explains a portion of the variability, and the NHANES III investigators found its inclusion in regression equations, along with age, height, and sex, improved their precision. Case closed, right? Modern medicine is defined by phenotyping, precision, and individualized care, so why shouldn’t race be a part of lung function interpretation?

Well, it’s complicated. With the increasing recognition of health disparities across racial groups the way race is incorporated in medical practice is understandably being scrutinized. As clinicians and academics, we must analyze the root cause of differences in health outcomes between racial groups.

Publications on pulse oximetry (Gottlieb ER, et al. JAMA Intern Med. 2022; 182:849-858) and glomerular filtration rate (Williams WW, et al. N Engl J Med. 2021;385:1804-1806) have revealed some of the ways our use of instruments and equations may exacerbate or perpetuate current disparities. Even small differences in a measure like pulse oximetry could have a profound impact on clinical decisions at the individual and population levels.

The 2022 ERS/ATS lung function interpretation guidelines have abandoned the use of NHANES III as a reference set. They now recommend the equations developed by the Global Lung Initiative (GLI) for referencing to normal for spirometry, diffusion capacity, and lung volumes. For spirometry the GLI was able to integrate data from countries around the world. This allowed ethnicity to be included in their regression equations and, similar to NHANES III, they found ethnicity improved the precision of their equations. They also published an equation that did not account for country of origin that could be applied to individuals of any race/ethnicity (Quanjer PH, et al. Eur Respir J. 2014;43:505-512). This allowed for applying the GLI equations to external data sets with or without ethnicity included as a co-variate.

Given well-established discrepancies in spirometry, it should come as no surprise that applying the race/ethnicity-neutral GLI equations to non-White populations increases the percentage of patients with pulmonary defects (Moffett AT, et al. Am J Respir Crit Care Med. 2021; A1030). Other data suggest that elimination of race/ethnicity as a co-variate improves the association between percent predicted lung function and important outcomes like mortality (McCormack MC, et al. Am J Respir Crit Care Med. 2022;205:723-724). The first analysis implies that by adjusting for race/ethnicity we may be missing abnormalities, and the second suggests accuracy for outcomes is lost. So case closed, right? Let’s abandon race/ethnicity as a co- variate for our spirometry reference equations.

Perhaps, but a few caveats are in order. It’s important to note that doing so would result in a dramatic increase in abnormal findings in otherwise healthy and asymptomatic non-White individuals. This could negatively affect eligibility for employment and military service (Townsend MC, et al. Am J Respir Crit Care Med. 2022;789-790). We’ve also yet to fully explain the factors driving differences in lung function between races. If socioeconomic factors explained the entirety of the difference, it would be easier to argue for elimination of using race/ethnicity in our equations. Currently, the etiology is thought to be multifactorial and is yet to be fully explained (Braun L, et al. Eur Respir J. 2013;41:1362-1370).

The more we look for institutional racism, the more we will find it. As we realize that attaining health and wellness is more difficult for the disenfranchised, we need to ensure our current practices are part of the solution.

The ERS/ATS guidelines suggest eliminating fixed correction factors for race but do not require elimination of race/ethnicity as a co-variate in the equations selected for use. This seems very reasonable given what we know now. As pulmonary medicine academics and researchers, we need to continue to study the impact integrating race/ethnicity has on precision, accuracy, and clinical outcomes. As pulmonary medicine clinicians, we need to be aware of the reference equations being used in our lab, understand how inclusion of race/ethnicity affects findings, and act accordingly, depending on the clinical situation.
 

Dr. Ghionni is a Pulmonary/Critical Care Fellow, and Dr. Woods is Program Director – PCCM Fellowship and Associate Program Director – IM Residency, Medstar Washington Hospital Center; Dr. Woods is Associate Professor of Medicine, Georgetown University School of Medicine, Washington, DC.

The European Respiratory Society (ERS) and American Thoracic Society (ATS) just published an update to their guidelines on lung function interpretation (Stanojevic S, et al. Eur Respir J. 2022; 60: 2101499). As with any update, the document builds on past work and integrates new advances the field has seen since 2005.

The current iteration comes at a time when academics, clinicians, and epidemiologists are re-analyzing what we think we know about the complex ways race and ethnicity intersect with the practice of medicine. Several experts on lung function testing, many if not most of whom are authors on the ERS/ATS guideline, have written letters or published reviews commenting on the way accounting for race or ethnicity affects lung function interpretation.

Race/ethnicity and lung function was also the topic of an excellent session at the recent CHEST 2022 Annual Meeting in Nashville, Tennessee. Here, we’ll provide a brief review and direct the reader to relevant sources for a more detailed analysis.

Spirometry is an integral part of the diagnosis and management of a wide range of pulmonary conditions. Dr. Aaron Baugh from the University of California San Francisco (UCSF) lectured on the spirometer’s history at CHEST 2022 and detailed its interactions with race over the past 2 centuries. Other authors have chronicled this history, as well (Braun L, et al. Can J Respir Ther. 2015;51[4]:99-101). The short version is that since the British surgeon John Hutchinson created the first spirometer in 1846, race has been a part of the discussion of lung function interpretation.

In 2022, we know far more about the factors that determine lung function than we did in the 19th century. Age, height, and sex assigned at birth all explain a high percentage of the variability seen in FEV1 and FVC. When modeled, race also explains a portion of the variability, and the NHANES III investigators found its inclusion in regression equations, along with age, height, and sex, improved their precision. Case closed, right? Modern medicine is defined by phenotyping, precision, and individualized care, so why shouldn’t race be a part of lung function interpretation?

Well, it’s complicated. With the increasing recognition of health disparities across racial groups the way race is incorporated in medical practice is understandably being scrutinized. As clinicians and academics, we must analyze the root cause of differences in health outcomes between racial groups.

Publications on pulse oximetry (Gottlieb ER, et al. JAMA Intern Med. 2022; 182:849-858) and glomerular filtration rate (Williams WW, et al. N Engl J Med. 2021;385:1804-1806) have revealed some of the ways our use of instruments and equations may exacerbate or perpetuate current disparities. Even small differences in a measure like pulse oximetry could have a profound impact on clinical decisions at the individual and population levels.

The 2022 ERS/ATS lung function interpretation guidelines have abandoned the use of NHANES III as a reference set. They now recommend the equations developed by the Global Lung Initiative (GLI) for referencing to normal for spirometry, diffusion capacity, and lung volumes. For spirometry the GLI was able to integrate data from countries around the world. This allowed ethnicity to be included in their regression equations and, similar to NHANES III, they found ethnicity improved the precision of their equations. They also published an equation that did not account for country of origin that could be applied to individuals of any race/ethnicity (Quanjer PH, et al. Eur Respir J. 2014;43:505-512). This allowed for applying the GLI equations to external data sets with or without ethnicity included as a co-variate.

Given well-established discrepancies in spirometry, it should come as no surprise that applying the race/ethnicity-neutral GLI equations to non-White populations increases the percentage of patients with pulmonary defects (Moffett AT, et al. Am J Respir Crit Care Med. 2021; A1030). Other data suggest that elimination of race/ethnicity as a co-variate improves the association between percent predicted lung function and important outcomes like mortality (McCormack MC, et al. Am J Respir Crit Care Med. 2022;205:723-724). The first analysis implies that by adjusting for race/ethnicity we may be missing abnormalities, and the second suggests accuracy for outcomes is lost. So case closed, right? Let’s abandon race/ethnicity as a co- variate for our spirometry reference equations.

Perhaps, but a few caveats are in order. It’s important to note that doing so would result in a dramatic increase in abnormal findings in otherwise healthy and asymptomatic non-White individuals. This could negatively affect eligibility for employment and military service (Townsend MC, et al. Am J Respir Crit Care Med. 2022;789-790). We’ve also yet to fully explain the factors driving differences in lung function between races. If socioeconomic factors explained the entirety of the difference, it would be easier to argue for elimination of using race/ethnicity in our equations. Currently, the etiology is thought to be multifactorial and is yet to be fully explained (Braun L, et al. Eur Respir J. 2013;41:1362-1370).

The more we look for institutional racism, the more we will find it. As we realize that attaining health and wellness is more difficult for the disenfranchised, we need to ensure our current practices are part of the solution.

The ERS/ATS guidelines suggest eliminating fixed correction factors for race but do not require elimination of race/ethnicity as a co-variate in the equations selected for use. This seems very reasonable given what we know now. As pulmonary medicine academics and researchers, we need to continue to study the impact integrating race/ethnicity has on precision, accuracy, and clinical outcomes. As pulmonary medicine clinicians, we need to be aware of the reference equations being used in our lab, understand how inclusion of race/ethnicity affects findings, and act accordingly, depending on the clinical situation.
 

Dr. Ghionni is a Pulmonary/Critical Care Fellow, and Dr. Woods is Program Director – PCCM Fellowship and Associate Program Director – IM Residency, Medstar Washington Hospital Center; Dr. Woods is Associate Professor of Medicine, Georgetown University School of Medicine, Washington, DC.

The European Respiratory Society (ERS) and American Thoracic Society (ATS) just published an update to their guidelines on lung function interpretation (Stanojevic S, et al. Eur Respir J. 2022; 60: 2101499). As with any update, the document builds on past work and integrates new advances the field has seen since 2005.

The current iteration comes at a time when academics, clinicians, and epidemiologists are re-analyzing what we think we know about the complex ways race and ethnicity intersect with the practice of medicine. Several experts on lung function testing, many if not most of whom are authors on the ERS/ATS guideline, have written letters or published reviews commenting on the way accounting for race or ethnicity affects lung function interpretation.

Race/ethnicity and lung function was also the topic of an excellent session at the recent CHEST 2022 Annual Meeting in Nashville, Tennessee. Here, we’ll provide a brief review and direct the reader to relevant sources for a more detailed analysis.

Spirometry is an integral part of the diagnosis and management of a wide range of pulmonary conditions. Dr. Aaron Baugh from the University of California San Francisco (UCSF) lectured on the spirometer’s history at CHEST 2022 and detailed its interactions with race over the past 2 centuries. Other authors have chronicled this history, as well (Braun L, et al. Can J Respir Ther. 2015;51[4]:99-101). The short version is that since the British surgeon John Hutchinson created the first spirometer in 1846, race has been a part of the discussion of lung function interpretation.

In 2022, we know far more about the factors that determine lung function than we did in the 19th century. Age, height, and sex assigned at birth all explain a high percentage of the variability seen in FEV1 and FVC. When modeled, race also explains a portion of the variability, and the NHANES III investigators found its inclusion in regression equations, along with age, height, and sex, improved their precision. Case closed, right? Modern medicine is defined by phenotyping, precision, and individualized care, so why shouldn’t race be a part of lung function interpretation?

Well, it’s complicated. With the increasing recognition of health disparities across racial groups the way race is incorporated in medical practice is understandably being scrutinized. As clinicians and academics, we must analyze the root cause of differences in health outcomes between racial groups.

Publications on pulse oximetry (Gottlieb ER, et al. JAMA Intern Med. 2022; 182:849-858) and glomerular filtration rate (Williams WW, et al. N Engl J Med. 2021;385:1804-1806) have revealed some of the ways our use of instruments and equations may exacerbate or perpetuate current disparities. Even small differences in a measure like pulse oximetry could have a profound impact on clinical decisions at the individual and population levels.

The 2022 ERS/ATS lung function interpretation guidelines have abandoned the use of NHANES III as a reference set. They now recommend the equations developed by the Global Lung Initiative (GLI) for referencing to normal for spirometry, diffusion capacity, and lung volumes. For spirometry the GLI was able to integrate data from countries around the world. This allowed ethnicity to be included in their regression equations and, similar to NHANES III, they found ethnicity improved the precision of their equations. They also published an equation that did not account for country of origin that could be applied to individuals of any race/ethnicity (Quanjer PH, et al. Eur Respir J. 2014;43:505-512). This allowed for applying the GLI equations to external data sets with or without ethnicity included as a co-variate.

Given well-established discrepancies in spirometry, it should come as no surprise that applying the race/ethnicity-neutral GLI equations to non-White populations increases the percentage of patients with pulmonary defects (Moffett AT, et al. Am J Respir Crit Care Med. 2021; A1030). Other data suggest that elimination of race/ethnicity as a co-variate improves the association between percent predicted lung function and important outcomes like mortality (McCormack MC, et al. Am J Respir Crit Care Med. 2022;205:723-724). The first analysis implies that by adjusting for race/ethnicity we may be missing abnormalities, and the second suggests accuracy for outcomes is lost. So case closed, right? Let’s abandon race/ethnicity as a co- variate for our spirometry reference equations.

Perhaps, but a few caveats are in order. It’s important to note that doing so would result in a dramatic increase in abnormal findings in otherwise healthy and asymptomatic non-White individuals. This could negatively affect eligibility for employment and military service (Townsend MC, et al. Am J Respir Crit Care Med. 2022;789-790). We’ve also yet to fully explain the factors driving differences in lung function between races. If socioeconomic factors explained the entirety of the difference, it would be easier to argue for elimination of using race/ethnicity in our equations. Currently, the etiology is thought to be multifactorial and is yet to be fully explained (Braun L, et al. Eur Respir J. 2013;41:1362-1370).

The more we look for institutional racism, the more we will find it. As we realize that attaining health and wellness is more difficult for the disenfranchised, we need to ensure our current practices are part of the solution.

The ERS/ATS guidelines suggest eliminating fixed correction factors for race but do not require elimination of race/ethnicity as a co-variate in the equations selected for use. This seems very reasonable given what we know now. As pulmonary medicine academics and researchers, we need to continue to study the impact integrating race/ethnicity has on precision, accuracy, and clinical outcomes. As pulmonary medicine clinicians, we need to be aware of the reference equations being used in our lab, understand how inclusion of race/ethnicity affects findings, and act accordingly, depending on the clinical situation.
 

Dr. Ghionni is a Pulmonary/Critical Care Fellow, and Dr. Woods is Program Director – PCCM Fellowship and Associate Program Director – IM Residency, Medstar Washington Hospital Center; Dr. Woods is Associate Professor of Medicine, Georgetown University School of Medicine, Washington, DC.