When is a biopsy not a biopsy?

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When is a biopsy not a biopsy?

“When I use a word, it means just what I choose it to mean…” – Humpty Dumpty

Even after all these years, I’m still surprised to learn new ways the words we use every day can mean different things to patients to whom we say them.

Take the word “biopsy.” To a dermatologist, it means “a test of a piece of tissue” (in our case, of skin), to help find out what the problem is.

I’ve always known that to many patients, the word “biopsy” suggests cancer, or at least the concern that there may be cancer, because cancer is the context in which most people hear the word: breast biopsy, prostate biopsy, and so on. It can therefore be useful to point out to patients when a biopsy is performed for diagnostic purposes and cancer is not even on the list of possibilities.

Lately, though, I’ve had a few encounters that highlighted other interesting ways the word “biopsy” can be misunderstood.

Case 1: Arnold the Irritated

“Arnold,” I say. “I need to biopsy this. Based on the results, it may need further treatment, but I doubt it.”

“I thought you were taking it off now,” says Arnold.

“No, I’m testing it, “I say.

“But I want it off,” says Arnold. “It gets irritated when I shave over it, so I want it off.”

“Yes,” I say, “but in order to remove it properly, I need to know what it is.”

“What?”

We have to go around a few more times before Arnold catches on.

Case 2: Gaetano the Outraged

“Gaetano is on the phone,” says my billing clerk. “He says you told him you weren’t going to biopsy his spot, and then he got a bill from the pathology lab.”

I call Gaetano. “You said you weren’t going to biopsy this,” he says. “You said you were sure you knew what it was, so you didn’t have to biopsy it.”

“First of all,” I explain, “I’m never totally sure. Your spot looked like a basal cell skin cancer, and that’s what it turned out to be. But I’ve had cases where the pathology results surprised me, and it turned out to be something less – or something more. So I have to check the biopsy.”

“I understand, Doctor” says Gaetano.

“In addition,” I go on, “what I actually meant to say was that I was not going to only take a biopsy of the spot. I was going to remove it completely, so that if my diagnosis was confirmed, you wouldn’t have to come back and have more done. Sorry if I didn’t make that clear.”

“So you biopsied it,” says Gaetano, but you didn’t just biopsy it. I get it. I think.”

Good for you, Gaetano. Next time I am going to – actually, next time I don’t know what I’ll do.

Case 3: Melvin the Clueless

“I understand your former dermatologist removed something from your arm,” I say to Melvin.

“Yes, they took a biopsy, and then they removed it,” says Melvin. “I just have one question.”

“What is that?” I ask.

“Which was the biopsy?” asks Melvin, “the first or the second?”

I didn’t let on, but inside I was shaking my head.

Even with the best will on both sides – and even if both are native speakers of the same language – there are just so many ways people can misunderstand each other. Humpty Dumpty was wrong. Words can mean what both the talker and the listener think they mean. Humpty Dumpty probably didn’t get out much.

Never biopsy an egg. 

Dr. Rockoff practices dermatology in Brookline, Mass., and is a longtime contributor to Skin & Allergy News. He serves on the clinical faculty at Tufts University, Boston, and has taught senior medical students and other trainees for 30 years.

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“When I use a word, it means just what I choose it to mean…” – Humpty Dumpty

Even after all these years, I’m still surprised to learn new ways the words we use every day can mean different things to patients to whom we say them.

Take the word “biopsy.” To a dermatologist, it means “a test of a piece of tissue” (in our case, of skin), to help find out what the problem is.

I’ve always known that to many patients, the word “biopsy” suggests cancer, or at least the concern that there may be cancer, because cancer is the context in which most people hear the word: breast biopsy, prostate biopsy, and so on. It can therefore be useful to point out to patients when a biopsy is performed for diagnostic purposes and cancer is not even on the list of possibilities.

Lately, though, I’ve had a few encounters that highlighted other interesting ways the word “biopsy” can be misunderstood.

Case 1: Arnold the Irritated

“Arnold,” I say. “I need to biopsy this. Based on the results, it may need further treatment, but I doubt it.”

“I thought you were taking it off now,” says Arnold.

“No, I’m testing it, “I say.

“But I want it off,” says Arnold. “It gets irritated when I shave over it, so I want it off.”

“Yes,” I say, “but in order to remove it properly, I need to know what it is.”

“What?”

We have to go around a few more times before Arnold catches on.

Case 2: Gaetano the Outraged

“Gaetano is on the phone,” says my billing clerk. “He says you told him you weren’t going to biopsy his spot, and then he got a bill from the pathology lab.”

I call Gaetano. “You said you weren’t going to biopsy this,” he says. “You said you were sure you knew what it was, so you didn’t have to biopsy it.”

“First of all,” I explain, “I’m never totally sure. Your spot looked like a basal cell skin cancer, and that’s what it turned out to be. But I’ve had cases where the pathology results surprised me, and it turned out to be something less – or something more. So I have to check the biopsy.”

“I understand, Doctor” says Gaetano.

“In addition,” I go on, “what I actually meant to say was that I was not going to only take a biopsy of the spot. I was going to remove it completely, so that if my diagnosis was confirmed, you wouldn’t have to come back and have more done. Sorry if I didn’t make that clear.”

“So you biopsied it,” says Gaetano, but you didn’t just biopsy it. I get it. I think.”

Good for you, Gaetano. Next time I am going to – actually, next time I don’t know what I’ll do.

Case 3: Melvin the Clueless

“I understand your former dermatologist removed something from your arm,” I say to Melvin.

“Yes, they took a biopsy, and then they removed it,” says Melvin. “I just have one question.”

“What is that?” I ask.

“Which was the biopsy?” asks Melvin, “the first or the second?”

I didn’t let on, but inside I was shaking my head.

Even with the best will on both sides – and even if both are native speakers of the same language – there are just so many ways people can misunderstand each other. Humpty Dumpty was wrong. Words can mean what both the talker and the listener think they mean. Humpty Dumpty probably didn’t get out much.

Never biopsy an egg. 

Dr. Rockoff practices dermatology in Brookline, Mass., and is a longtime contributor to Skin & Allergy News. He serves on the clinical faculty at Tufts University, Boston, and has taught senior medical students and other trainees for 30 years.

“When I use a word, it means just what I choose it to mean…” – Humpty Dumpty

Even after all these years, I’m still surprised to learn new ways the words we use every day can mean different things to patients to whom we say them.

Take the word “biopsy.” To a dermatologist, it means “a test of a piece of tissue” (in our case, of skin), to help find out what the problem is.

I’ve always known that to many patients, the word “biopsy” suggests cancer, or at least the concern that there may be cancer, because cancer is the context in which most people hear the word: breast biopsy, prostate biopsy, and so on. It can therefore be useful to point out to patients when a biopsy is performed for diagnostic purposes and cancer is not even on the list of possibilities.

Lately, though, I’ve had a few encounters that highlighted other interesting ways the word “biopsy” can be misunderstood.

Case 1: Arnold the Irritated

“Arnold,” I say. “I need to biopsy this. Based on the results, it may need further treatment, but I doubt it.”

“I thought you were taking it off now,” says Arnold.

“No, I’m testing it, “I say.

“But I want it off,” says Arnold. “It gets irritated when I shave over it, so I want it off.”

“Yes,” I say, “but in order to remove it properly, I need to know what it is.”

“What?”

We have to go around a few more times before Arnold catches on.

Case 2: Gaetano the Outraged

“Gaetano is on the phone,” says my billing clerk. “He says you told him you weren’t going to biopsy his spot, and then he got a bill from the pathology lab.”

I call Gaetano. “You said you weren’t going to biopsy this,” he says. “You said you were sure you knew what it was, so you didn’t have to biopsy it.”

“First of all,” I explain, “I’m never totally sure. Your spot looked like a basal cell skin cancer, and that’s what it turned out to be. But I’ve had cases where the pathology results surprised me, and it turned out to be something less – or something more. So I have to check the biopsy.”

“I understand, Doctor” says Gaetano.

“In addition,” I go on, “what I actually meant to say was that I was not going to only take a biopsy of the spot. I was going to remove it completely, so that if my diagnosis was confirmed, you wouldn’t have to come back and have more done. Sorry if I didn’t make that clear.”

“So you biopsied it,” says Gaetano, but you didn’t just biopsy it. I get it. I think.”

Good for you, Gaetano. Next time I am going to – actually, next time I don’t know what I’ll do.

Case 3: Melvin the Clueless

“I understand your former dermatologist removed something from your arm,” I say to Melvin.

“Yes, they took a biopsy, and then they removed it,” says Melvin. “I just have one question.”

“What is that?” I ask.

“Which was the biopsy?” asks Melvin, “the first or the second?”

I didn’t let on, but inside I was shaking my head.

Even with the best will on both sides – and even if both are native speakers of the same language – there are just so many ways people can misunderstand each other. Humpty Dumpty was wrong. Words can mean what both the talker and the listener think they mean. Humpty Dumpty probably didn’t get out much.

Never biopsy an egg. 

Dr. Rockoff practices dermatology in Brookline, Mass., and is a longtime contributor to Skin & Allergy News. He serves on the clinical faculty at Tufts University, Boston, and has taught senior medical students and other trainees for 30 years.

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An overlooked laboratory report

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Question: Your office assistant misfiled a critical laboratory report showing dangerous hyperkalemia of 6.5 mEq/L. Unaware of the abnormality, you failed to notify the end-stage renal patient to return for treatment. In the meantime, the patient collapsed and died, and an autopsy revealed a fresh transmural myocardial infarct.

Which of the following statements is best?

A. You are negligent, because the standard of care is to promptly contact the patient.

B. Your office assistant is negligent, because she was the one who misfiled the report.

C. Liability rests with the laboratory, because it should have called the office immediately with the critical value.

D. Your lawyer will defend you on the legal theory that hyperkalemia was not the proximate cause of death.

E. All of the above.

Answer: E. In any negligence action, the plaintiff bears the burden of proof, on a balance of probabilities, that the defendant owes him/her a duty of care, the breach of which proximately caused the plaintiff’s injuries.

One begins with an inquiry into whether a duty exists and whether a breach has occurred. Generally, doctors owe a legal duty of due care to their patients arising out of the doctor-patient relationship. By “missing” the laboratory report, especially one of urgency, and not immediately notifying the patient, the doctor has likely breached his/her duty. Another way of putting it is to ask whether the conduct has fallen below what is ordinarily expected of a practitioner in a similar situation.

The doctor will likely blame the office assistant for misfiling the report, and the assistant is indeed liable, as he/she also owes a direct legal duty to the patient. However, such liability will then fall upon the doctor under “respondeat superior” or “let the master answer,” which is the legal doctrine underpinning vicarious liability. This is characteristically seen in an employer-employee situation, where liability is imputed to the employer despite the tortious act being committed only by the employee.

The idea behind this rule is to ensure that the employer, as supervisor, will enforce proper work conditions to avoid risk of harm. The employer also is better able to shoulder the cost of compensating the victim.

For vicarious liability to arise, the employee’s act must have occurred during and within the scope of employment, and the risk of harm must be foreseeable. Under the facts of this hypothetical scenario, it is easy to see that the doctor will be vicariously liable for the negligent act of the assistant.

The clinical laboratory also owes an independent duty to the patient, which includes, among other things, assuring the proper standards in specimen collection and test performance. The duty extends to timely and accurate reporting of the results, including calling the physician when there is a critically high or low value if that is the standard of care in the community, as it generally is.

Thus, the laboratory in this case will likely be named as a codefendant. This is called joint and several liability, where more than one defendant has concurrently or successively caused a plaintiff’s indivisible injury, and the latter can recover all damages from any of the wrongdoers irrespective of degree of fault, as long as causation is proven. However, the plaintiff is not entitled to double recovery, and a defendant can proceed against the other liable parties for contribution.

Proving existence and breach of duty are necessary but insufficient steps toward winning the lawsuit. The plaintiff must also establish causation, i.e., that the substandard care caused the injury.

Causation inquires into both cause-in-fact and cause-in-law, and the term “proximate cause” is used to cover both of these aspects of causation. Cause-in-fact is established with the “but for” test – whether it can be said that had it not been for the defendant’s actions, the plaintiff would not have suffered the injury.

In this scenario, the doctor’s attorney will argue that the cause of death, a myocardial infarct, was preexisting atherosclerotic heart disease, rather than hyperkalemia. Besides, the chronic renal patient typically adapts to hyperkalemia and can tolerate elevated levels better than nonrenal patients. Of course, the counterargument is that the patient’s cardiac injury was a likely consequence of hyperkalemia-induced ventricular arrhythmia.

The doctor, the nurse, and the laboratory will all be named as codefendants. However, the laboratory will attempt to escape liability by arguing that its negligence, if any, was superseded by the doctor’s own negligent failure to read the report. Cause-in-law analysis examines whether a new independent event has intervened between the negligent act and the outcome, which may have been aggravated by the new event.

 

 

It naturally raises the question whether the original wrongdoer – in this case, the laboratory – continues to be liable, or whether the chain of causation has been broken by the intervening cause (the doctor’s negligence).

In a federal case, the Florida District Court of Appeals found several doctors liable for missing the diagnosis of tuberculous meningitis (Hadley v. Terwilleger, 873 So.2d 378 (Fl. 2004)). The doctors had seen the patient at various times in a sequential manner. The court held that the plaintiff was entitled to concurring-cause, rather than superseding-cause, jury instructions. The purpose of such instruction was to negate the idea that a defendant is excused from the consequences of his or her negligence by reason of some other cause concurring in time and contributing to the same injury.

Overlooked, misfiled, or otherwise “missed” laboratory or x-ray reports are commonly encountered in medical practice, and may lead in some instances to serious patient injury. They are typically systems errors rather than the fault of any single individual, and like most medical errors, largely preventable.

Physicians and health care institutions should put in place tested protocols that protect patients from risk of harm, and, as the Institute of Medicine stated in its 2000 report, “To Err Is Human: Building a Safer Health System,” move away from “a culture of blame to a culture of safety.”

Dr. Tan is professor emeritus of medicine and former adjunct professor of law at the University of Hawaii, and currently directs the St. Francis International Center for Healthcare Ethics in Honolulu. This article is meant to be educational and does not constitute medical, ethical, or legal advice. Some of the articles in this series are adapted from the author’s 2006 book, “Medical Malpractice: Understanding the Law, Managing the Risk,” and his 2012 Halsbury treatise, “Medical Negligence and Professional Misconduct.” For additional information, readers may contact the author at s[email protected].

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Question: Your office assistant misfiled a critical laboratory report showing dangerous hyperkalemia of 6.5 mEq/L. Unaware of the abnormality, you failed to notify the end-stage renal patient to return for treatment. In the meantime, the patient collapsed and died, and an autopsy revealed a fresh transmural myocardial infarct.

Which of the following statements is best?

A. You are negligent, because the standard of care is to promptly contact the patient.

B. Your office assistant is negligent, because she was the one who misfiled the report.

C. Liability rests with the laboratory, because it should have called the office immediately with the critical value.

D. Your lawyer will defend you on the legal theory that hyperkalemia was not the proximate cause of death.

E. All of the above.

Answer: E. In any negligence action, the plaintiff bears the burden of proof, on a balance of probabilities, that the defendant owes him/her a duty of care, the breach of which proximately caused the plaintiff’s injuries.

One begins with an inquiry into whether a duty exists and whether a breach has occurred. Generally, doctors owe a legal duty of due care to their patients arising out of the doctor-patient relationship. By “missing” the laboratory report, especially one of urgency, and not immediately notifying the patient, the doctor has likely breached his/her duty. Another way of putting it is to ask whether the conduct has fallen below what is ordinarily expected of a practitioner in a similar situation.

The doctor will likely blame the office assistant for misfiling the report, and the assistant is indeed liable, as he/she also owes a direct legal duty to the patient. However, such liability will then fall upon the doctor under “respondeat superior” or “let the master answer,” which is the legal doctrine underpinning vicarious liability. This is characteristically seen in an employer-employee situation, where liability is imputed to the employer despite the tortious act being committed only by the employee.

The idea behind this rule is to ensure that the employer, as supervisor, will enforce proper work conditions to avoid risk of harm. The employer also is better able to shoulder the cost of compensating the victim.

For vicarious liability to arise, the employee’s act must have occurred during and within the scope of employment, and the risk of harm must be foreseeable. Under the facts of this hypothetical scenario, it is easy to see that the doctor will be vicariously liable for the negligent act of the assistant.

The clinical laboratory also owes an independent duty to the patient, which includes, among other things, assuring the proper standards in specimen collection and test performance. The duty extends to timely and accurate reporting of the results, including calling the physician when there is a critically high or low value if that is the standard of care in the community, as it generally is.

Thus, the laboratory in this case will likely be named as a codefendant. This is called joint and several liability, where more than one defendant has concurrently or successively caused a plaintiff’s indivisible injury, and the latter can recover all damages from any of the wrongdoers irrespective of degree of fault, as long as causation is proven. However, the plaintiff is not entitled to double recovery, and a defendant can proceed against the other liable parties for contribution.

Proving existence and breach of duty are necessary but insufficient steps toward winning the lawsuit. The plaintiff must also establish causation, i.e., that the substandard care caused the injury.

Causation inquires into both cause-in-fact and cause-in-law, and the term “proximate cause” is used to cover both of these aspects of causation. Cause-in-fact is established with the “but for” test – whether it can be said that had it not been for the defendant’s actions, the plaintiff would not have suffered the injury.

In this scenario, the doctor’s attorney will argue that the cause of death, a myocardial infarct, was preexisting atherosclerotic heart disease, rather than hyperkalemia. Besides, the chronic renal patient typically adapts to hyperkalemia and can tolerate elevated levels better than nonrenal patients. Of course, the counterargument is that the patient’s cardiac injury was a likely consequence of hyperkalemia-induced ventricular arrhythmia.

The doctor, the nurse, and the laboratory will all be named as codefendants. However, the laboratory will attempt to escape liability by arguing that its negligence, if any, was superseded by the doctor’s own negligent failure to read the report. Cause-in-law analysis examines whether a new independent event has intervened between the negligent act and the outcome, which may have been aggravated by the new event.

 

 

It naturally raises the question whether the original wrongdoer – in this case, the laboratory – continues to be liable, or whether the chain of causation has been broken by the intervening cause (the doctor’s negligence).

In a federal case, the Florida District Court of Appeals found several doctors liable for missing the diagnosis of tuberculous meningitis (Hadley v. Terwilleger, 873 So.2d 378 (Fl. 2004)). The doctors had seen the patient at various times in a sequential manner. The court held that the plaintiff was entitled to concurring-cause, rather than superseding-cause, jury instructions. The purpose of such instruction was to negate the idea that a defendant is excused from the consequences of his or her negligence by reason of some other cause concurring in time and contributing to the same injury.

Overlooked, misfiled, or otherwise “missed” laboratory or x-ray reports are commonly encountered in medical practice, and may lead in some instances to serious patient injury. They are typically systems errors rather than the fault of any single individual, and like most medical errors, largely preventable.

Physicians and health care institutions should put in place tested protocols that protect patients from risk of harm, and, as the Institute of Medicine stated in its 2000 report, “To Err Is Human: Building a Safer Health System,” move away from “a culture of blame to a culture of safety.”

Dr. Tan is professor emeritus of medicine and former adjunct professor of law at the University of Hawaii, and currently directs the St. Francis International Center for Healthcare Ethics in Honolulu. This article is meant to be educational and does not constitute medical, ethical, or legal advice. Some of the articles in this series are adapted from the author’s 2006 book, “Medical Malpractice: Understanding the Law, Managing the Risk,” and his 2012 Halsbury treatise, “Medical Negligence and Professional Misconduct.” For additional information, readers may contact the author at s[email protected].

Question: Your office assistant misfiled a critical laboratory report showing dangerous hyperkalemia of 6.5 mEq/L. Unaware of the abnormality, you failed to notify the end-stage renal patient to return for treatment. In the meantime, the patient collapsed and died, and an autopsy revealed a fresh transmural myocardial infarct.

Which of the following statements is best?

A. You are negligent, because the standard of care is to promptly contact the patient.

B. Your office assistant is negligent, because she was the one who misfiled the report.

C. Liability rests with the laboratory, because it should have called the office immediately with the critical value.

D. Your lawyer will defend you on the legal theory that hyperkalemia was not the proximate cause of death.

E. All of the above.

Answer: E. In any negligence action, the plaintiff bears the burden of proof, on a balance of probabilities, that the defendant owes him/her a duty of care, the breach of which proximately caused the plaintiff’s injuries.

One begins with an inquiry into whether a duty exists and whether a breach has occurred. Generally, doctors owe a legal duty of due care to their patients arising out of the doctor-patient relationship. By “missing” the laboratory report, especially one of urgency, and not immediately notifying the patient, the doctor has likely breached his/her duty. Another way of putting it is to ask whether the conduct has fallen below what is ordinarily expected of a practitioner in a similar situation.

The doctor will likely blame the office assistant for misfiling the report, and the assistant is indeed liable, as he/she also owes a direct legal duty to the patient. However, such liability will then fall upon the doctor under “respondeat superior” or “let the master answer,” which is the legal doctrine underpinning vicarious liability. This is characteristically seen in an employer-employee situation, where liability is imputed to the employer despite the tortious act being committed only by the employee.

The idea behind this rule is to ensure that the employer, as supervisor, will enforce proper work conditions to avoid risk of harm. The employer also is better able to shoulder the cost of compensating the victim.

For vicarious liability to arise, the employee’s act must have occurred during and within the scope of employment, and the risk of harm must be foreseeable. Under the facts of this hypothetical scenario, it is easy to see that the doctor will be vicariously liable for the negligent act of the assistant.

The clinical laboratory also owes an independent duty to the patient, which includes, among other things, assuring the proper standards in specimen collection and test performance. The duty extends to timely and accurate reporting of the results, including calling the physician when there is a critically high or low value if that is the standard of care in the community, as it generally is.

Thus, the laboratory in this case will likely be named as a codefendant. This is called joint and several liability, where more than one defendant has concurrently or successively caused a plaintiff’s indivisible injury, and the latter can recover all damages from any of the wrongdoers irrespective of degree of fault, as long as causation is proven. However, the plaintiff is not entitled to double recovery, and a defendant can proceed against the other liable parties for contribution.

Proving existence and breach of duty are necessary but insufficient steps toward winning the lawsuit. The plaintiff must also establish causation, i.e., that the substandard care caused the injury.

Causation inquires into both cause-in-fact and cause-in-law, and the term “proximate cause” is used to cover both of these aspects of causation. Cause-in-fact is established with the “but for” test – whether it can be said that had it not been for the defendant’s actions, the plaintiff would not have suffered the injury.

In this scenario, the doctor’s attorney will argue that the cause of death, a myocardial infarct, was preexisting atherosclerotic heart disease, rather than hyperkalemia. Besides, the chronic renal patient typically adapts to hyperkalemia and can tolerate elevated levels better than nonrenal patients. Of course, the counterargument is that the patient’s cardiac injury was a likely consequence of hyperkalemia-induced ventricular arrhythmia.

The doctor, the nurse, and the laboratory will all be named as codefendants. However, the laboratory will attempt to escape liability by arguing that its negligence, if any, was superseded by the doctor’s own negligent failure to read the report. Cause-in-law analysis examines whether a new independent event has intervened between the negligent act and the outcome, which may have been aggravated by the new event.

 

 

It naturally raises the question whether the original wrongdoer – in this case, the laboratory – continues to be liable, or whether the chain of causation has been broken by the intervening cause (the doctor’s negligence).

In a federal case, the Florida District Court of Appeals found several doctors liable for missing the diagnosis of tuberculous meningitis (Hadley v. Terwilleger, 873 So.2d 378 (Fl. 2004)). The doctors had seen the patient at various times in a sequential manner. The court held that the plaintiff was entitled to concurring-cause, rather than superseding-cause, jury instructions. The purpose of such instruction was to negate the idea that a defendant is excused from the consequences of his or her negligence by reason of some other cause concurring in time and contributing to the same injury.

Overlooked, misfiled, or otherwise “missed” laboratory or x-ray reports are commonly encountered in medical practice, and may lead in some instances to serious patient injury. They are typically systems errors rather than the fault of any single individual, and like most medical errors, largely preventable.

Physicians and health care institutions should put in place tested protocols that protect patients from risk of harm, and, as the Institute of Medicine stated in its 2000 report, “To Err Is Human: Building a Safer Health System,” move away from “a culture of blame to a culture of safety.”

Dr. Tan is professor emeritus of medicine and former adjunct professor of law at the University of Hawaii, and currently directs the St. Francis International Center for Healthcare Ethics in Honolulu. This article is meant to be educational and does not constitute medical, ethical, or legal advice. Some of the articles in this series are adapted from the author’s 2006 book, “Medical Malpractice: Understanding the Law, Managing the Risk,” and his 2012 Halsbury treatise, “Medical Negligence and Professional Misconduct.” For additional information, readers may contact the author at s[email protected].

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New evidence suggests 2014 hypertension guidelines could backfire

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CHICAGO – Nearly one in seven patients in U.S. ambulatory cardiology practices who would have been recommended for initiation or intensification of antihypertensive drug therapy under the 2003 Seventh Joint National Committee guidelines are no longer treatment candidates under the 2014 expert panel recommendations.

These patients who no longer qualify for antihypertensive therapy under the 2014 guidelines turn out to have a disturbingly high average estimated 10-year risk of cardiovascular events. As a result, widespread adoption of the 2014 expert panel recommendations could have major adverse consequences for cardiovascular health, Dr. William B. Borden cautioned at the American Heart Association scientific sessions.

“Given the size and underlying cardiovascular risk of the population affected by the changes in the 2014 panel recommendations, close monitoring will be required to assess changes in practice patterns, blood pressure control, and – importantly – any changes in cardiovascular morbidity and mortality,” said Dr. Borden, a cardiologist at George Washington University in Washington.

Because the 2014 expert panel guidelines represent a major shift in hypertension management, Dr. Borden and coinvestigators sought to quantify the potential cardiovascular health impact of this more lenient treatment approach. For this purpose they turned to the National Cardiovascular Data Registry Practice Innovation and Clinical Excellence (NCDR PINNACLE) Registry, a voluntary quality improvement project involving outpatient cardiology practices.

Of 1,185,253 patients with hypertension as identified in their chart by a recorded diagnosis or notation of blood pressure greater than 140/90 mm Hg, 60% met the 2003 JNC 7 goals (JAMA 2003;289:2560-72), meaning the other 40% were candidates for initiation or intensification of antihypertensive therapy in order to achieve those goals (see chart). In contrast, 74% of hypertensive patients in U.S. cardiology practices met the less aggressive targets recommended in the 2014 expert panel report (JAMA 2014;311:502-20).

Thus, fewer than two-thirds of hypertensive patients in outpatient cardiology practices met the 2003 JNC 7 blood pressure targets, while three-quarters met the liberalized 2014 targets.

Dr. Borden and coworkers zeroed in on the 15% of hypertensive patients – that’s fully 173,519 individuals in cardiology practices participating in the PINNACLE Registry – who would have been eligible for treatment under the JNC 7 recommendations but not the 2014 expert panel guidelines. Interestingly, that 15% figure was closely similar to the 17% rate reported by Dr. Michael D. Miedema of the Minneapolis Heart Institute in an analysis of a more primary care population of older patients in the Atherosclerosis Risk in Communities (ARIC) study he presented in the same session.

Dr. William B. Borden

Dr. Borden and coinvestigators determined from medical records that the PINNACLE Registry group whose antihypertensive therapy treatment status changed between the two guidelines was at substantial baseline cardiovascular risk: Nearly two-thirds had been diagnosed with CAD, 54% had diabetes, 27% had a history of heart failure, 25% had a prior MI, and 23% had a prior transient ischemic attack or stroke.

This large group of patients who fell through the cracks between two conflicting sets of guidelines turned out to have a mean 10-year Framingham Risk Score of 8.5%. Upon incorporating the patients’ stroke risk using the atherosclerotic cardiovascular disease (ASCVD) risk score embedded in the 2013 ACC/AHA cholesterol management guidelines, their 10-year risk shot up to 28%.

The investigators then conducted a modeling exercise aimed at estimating the clinical impact of lowering systolic blood pressure in the elderly from about 150 mm Hg, as recommended in the 2014 expert panel guidelines, to about 140 mm Hg, as was the goal in JNC 7. To do so they extrapolated from the results of two randomized controlled clinical trials: the Systolic Hypertension in the Elderly Program (SHEP) and the Hypertension in the Very Elderly Trial (HYVET).

The result? Extrapolating from SHEP data, the 10-year ASCVD risk in these real-world elderly hypertensive patients caught between two conflicting sets of guidelines would drop from 28% to 19%. Using HYVET data, the average 10-year ASCVD risk would fall to 18.4%.

“This is equivalent to a number-needed-to-treat of 10-11 patients for 10 years in order to prevent one cardiovascular event,” according to Dr. Borden.

For the more than 80,000 patients over age 60 in the study population, that works out to roughly 8,000 cardiovascular events averted over the course of 10 years, he added.

The 2014 expert panel recommendations were based on a strict evidence-based review of published randomized controlled trials. The guidelines are new enough that it remains unclear if they will be embraced by clinicians or incorporated into performance measures and value-based health care purchasing programs.

 

 

The 2014 guidelines are considered highly controversial. The guideline committee comprising some of the nation’s top hypertension researchers was initially convened to come up with what was intended to be the long-awaited JNC 8 report; however, in the midst of the process the sponsoring National Heart, Lung, and Blood Institute declared it was getting out of the guideline-writing business altogether. As a result, the guidelines ultimately published carried the imprimatur of “the 2014 expert panel,” rather than the more prestigious official stamp of JNC 8.

Indeed, five members of the guideline panel felt strongly enough to break away and issued a minority report (Ann. Intern. Med. 2014;160:499-503) in which they argued there is insufficient evidence of harm stemming from the JNC 7 goal of 140/90 mm Hg in patients over age 60 to justify revising the target to 150/90. They warned that this step could reverse the impressive reductions in cardiovascular and cerebrovascular morbidity and mortality realized in recent decades. And they concluded that the burden of proof should be on those who advocate raising the treatment threshold to 150/90 mm Hg to demonstrate that it has benefit in patients over age 60, which they haven’t done.

“I’m very concerned about the [2014 expert panel] guidelines. Older individuals have the highest prevalence of hypertension, they’re the least adequately controlled, and based on the available data I’m concerned that if people follow the new guidelines there’s going to be an increase in cardiovascular events,” said Dr. Wilbert F. Aronow of New York Medical College, Valhalla, who chaired the writing committee for the first-ever ACC/AHA clinical guidelines for controlling high blood pressure in the elderly (J. Am. Coll. Cardiol. 2011;57:2037-114).

The NCDR PINNACLE Registry and this study were supported by the American College of Cardiology Foundation. Dr. Borden and Dr. Aronow reported having no financial conflicts.

[email protected]

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CHICAGO – Nearly one in seven patients in U.S. ambulatory cardiology practices who would have been recommended for initiation or intensification of antihypertensive drug therapy under the 2003 Seventh Joint National Committee guidelines are no longer treatment candidates under the 2014 expert panel recommendations.

These patients who no longer qualify for antihypertensive therapy under the 2014 guidelines turn out to have a disturbingly high average estimated 10-year risk of cardiovascular events. As a result, widespread adoption of the 2014 expert panel recommendations could have major adverse consequences for cardiovascular health, Dr. William B. Borden cautioned at the American Heart Association scientific sessions.

“Given the size and underlying cardiovascular risk of the population affected by the changes in the 2014 panel recommendations, close monitoring will be required to assess changes in practice patterns, blood pressure control, and – importantly – any changes in cardiovascular morbidity and mortality,” said Dr. Borden, a cardiologist at George Washington University in Washington.

Because the 2014 expert panel guidelines represent a major shift in hypertension management, Dr. Borden and coinvestigators sought to quantify the potential cardiovascular health impact of this more lenient treatment approach. For this purpose they turned to the National Cardiovascular Data Registry Practice Innovation and Clinical Excellence (NCDR PINNACLE) Registry, a voluntary quality improvement project involving outpatient cardiology practices.

Of 1,185,253 patients with hypertension as identified in their chart by a recorded diagnosis or notation of blood pressure greater than 140/90 mm Hg, 60% met the 2003 JNC 7 goals (JAMA 2003;289:2560-72), meaning the other 40% were candidates for initiation or intensification of antihypertensive therapy in order to achieve those goals (see chart). In contrast, 74% of hypertensive patients in U.S. cardiology practices met the less aggressive targets recommended in the 2014 expert panel report (JAMA 2014;311:502-20).

Thus, fewer than two-thirds of hypertensive patients in outpatient cardiology practices met the 2003 JNC 7 blood pressure targets, while three-quarters met the liberalized 2014 targets.

Dr. Borden and coworkers zeroed in on the 15% of hypertensive patients – that’s fully 173,519 individuals in cardiology practices participating in the PINNACLE Registry – who would have been eligible for treatment under the JNC 7 recommendations but not the 2014 expert panel guidelines. Interestingly, that 15% figure was closely similar to the 17% rate reported by Dr. Michael D. Miedema of the Minneapolis Heart Institute in an analysis of a more primary care population of older patients in the Atherosclerosis Risk in Communities (ARIC) study he presented in the same session.

Dr. William B. Borden

Dr. Borden and coinvestigators determined from medical records that the PINNACLE Registry group whose antihypertensive therapy treatment status changed between the two guidelines was at substantial baseline cardiovascular risk: Nearly two-thirds had been diagnosed with CAD, 54% had diabetes, 27% had a history of heart failure, 25% had a prior MI, and 23% had a prior transient ischemic attack or stroke.

This large group of patients who fell through the cracks between two conflicting sets of guidelines turned out to have a mean 10-year Framingham Risk Score of 8.5%. Upon incorporating the patients’ stroke risk using the atherosclerotic cardiovascular disease (ASCVD) risk score embedded in the 2013 ACC/AHA cholesterol management guidelines, their 10-year risk shot up to 28%.

The investigators then conducted a modeling exercise aimed at estimating the clinical impact of lowering systolic blood pressure in the elderly from about 150 mm Hg, as recommended in the 2014 expert panel guidelines, to about 140 mm Hg, as was the goal in JNC 7. To do so they extrapolated from the results of two randomized controlled clinical trials: the Systolic Hypertension in the Elderly Program (SHEP) and the Hypertension in the Very Elderly Trial (HYVET).

The result? Extrapolating from SHEP data, the 10-year ASCVD risk in these real-world elderly hypertensive patients caught between two conflicting sets of guidelines would drop from 28% to 19%. Using HYVET data, the average 10-year ASCVD risk would fall to 18.4%.

“This is equivalent to a number-needed-to-treat of 10-11 patients for 10 years in order to prevent one cardiovascular event,” according to Dr. Borden.

For the more than 80,000 patients over age 60 in the study population, that works out to roughly 8,000 cardiovascular events averted over the course of 10 years, he added.

The 2014 expert panel recommendations were based on a strict evidence-based review of published randomized controlled trials. The guidelines are new enough that it remains unclear if they will be embraced by clinicians or incorporated into performance measures and value-based health care purchasing programs.

 

 

The 2014 guidelines are considered highly controversial. The guideline committee comprising some of the nation’s top hypertension researchers was initially convened to come up with what was intended to be the long-awaited JNC 8 report; however, in the midst of the process the sponsoring National Heart, Lung, and Blood Institute declared it was getting out of the guideline-writing business altogether. As a result, the guidelines ultimately published carried the imprimatur of “the 2014 expert panel,” rather than the more prestigious official stamp of JNC 8.

Indeed, five members of the guideline panel felt strongly enough to break away and issued a minority report (Ann. Intern. Med. 2014;160:499-503) in which they argued there is insufficient evidence of harm stemming from the JNC 7 goal of 140/90 mm Hg in patients over age 60 to justify revising the target to 150/90. They warned that this step could reverse the impressive reductions in cardiovascular and cerebrovascular morbidity and mortality realized in recent decades. And they concluded that the burden of proof should be on those who advocate raising the treatment threshold to 150/90 mm Hg to demonstrate that it has benefit in patients over age 60, which they haven’t done.

“I’m very concerned about the [2014 expert panel] guidelines. Older individuals have the highest prevalence of hypertension, they’re the least adequately controlled, and based on the available data I’m concerned that if people follow the new guidelines there’s going to be an increase in cardiovascular events,” said Dr. Wilbert F. Aronow of New York Medical College, Valhalla, who chaired the writing committee for the first-ever ACC/AHA clinical guidelines for controlling high blood pressure in the elderly (J. Am. Coll. Cardiol. 2011;57:2037-114).

The NCDR PINNACLE Registry and this study were supported by the American College of Cardiology Foundation. Dr. Borden and Dr. Aronow reported having no financial conflicts.

[email protected]

CHICAGO – Nearly one in seven patients in U.S. ambulatory cardiology practices who would have been recommended for initiation or intensification of antihypertensive drug therapy under the 2003 Seventh Joint National Committee guidelines are no longer treatment candidates under the 2014 expert panel recommendations.

These patients who no longer qualify for antihypertensive therapy under the 2014 guidelines turn out to have a disturbingly high average estimated 10-year risk of cardiovascular events. As a result, widespread adoption of the 2014 expert panel recommendations could have major adverse consequences for cardiovascular health, Dr. William B. Borden cautioned at the American Heart Association scientific sessions.

“Given the size and underlying cardiovascular risk of the population affected by the changes in the 2014 panel recommendations, close monitoring will be required to assess changes in practice patterns, blood pressure control, and – importantly – any changes in cardiovascular morbidity and mortality,” said Dr. Borden, a cardiologist at George Washington University in Washington.

Because the 2014 expert panel guidelines represent a major shift in hypertension management, Dr. Borden and coinvestigators sought to quantify the potential cardiovascular health impact of this more lenient treatment approach. For this purpose they turned to the National Cardiovascular Data Registry Practice Innovation and Clinical Excellence (NCDR PINNACLE) Registry, a voluntary quality improvement project involving outpatient cardiology practices.

Of 1,185,253 patients with hypertension as identified in their chart by a recorded diagnosis or notation of blood pressure greater than 140/90 mm Hg, 60% met the 2003 JNC 7 goals (JAMA 2003;289:2560-72), meaning the other 40% were candidates for initiation or intensification of antihypertensive therapy in order to achieve those goals (see chart). In contrast, 74% of hypertensive patients in U.S. cardiology practices met the less aggressive targets recommended in the 2014 expert panel report (JAMA 2014;311:502-20).

Thus, fewer than two-thirds of hypertensive patients in outpatient cardiology practices met the 2003 JNC 7 blood pressure targets, while three-quarters met the liberalized 2014 targets.

Dr. Borden and coworkers zeroed in on the 15% of hypertensive patients – that’s fully 173,519 individuals in cardiology practices participating in the PINNACLE Registry – who would have been eligible for treatment under the JNC 7 recommendations but not the 2014 expert panel guidelines. Interestingly, that 15% figure was closely similar to the 17% rate reported by Dr. Michael D. Miedema of the Minneapolis Heart Institute in an analysis of a more primary care population of older patients in the Atherosclerosis Risk in Communities (ARIC) study he presented in the same session.

Dr. William B. Borden

Dr. Borden and coinvestigators determined from medical records that the PINNACLE Registry group whose antihypertensive therapy treatment status changed between the two guidelines was at substantial baseline cardiovascular risk: Nearly two-thirds had been diagnosed with CAD, 54% had diabetes, 27% had a history of heart failure, 25% had a prior MI, and 23% had a prior transient ischemic attack or stroke.

This large group of patients who fell through the cracks between two conflicting sets of guidelines turned out to have a mean 10-year Framingham Risk Score of 8.5%. Upon incorporating the patients’ stroke risk using the atherosclerotic cardiovascular disease (ASCVD) risk score embedded in the 2013 ACC/AHA cholesterol management guidelines, their 10-year risk shot up to 28%.

The investigators then conducted a modeling exercise aimed at estimating the clinical impact of lowering systolic blood pressure in the elderly from about 150 mm Hg, as recommended in the 2014 expert panel guidelines, to about 140 mm Hg, as was the goal in JNC 7. To do so they extrapolated from the results of two randomized controlled clinical trials: the Systolic Hypertension in the Elderly Program (SHEP) and the Hypertension in the Very Elderly Trial (HYVET).

The result? Extrapolating from SHEP data, the 10-year ASCVD risk in these real-world elderly hypertensive patients caught between two conflicting sets of guidelines would drop from 28% to 19%. Using HYVET data, the average 10-year ASCVD risk would fall to 18.4%.

“This is equivalent to a number-needed-to-treat of 10-11 patients for 10 years in order to prevent one cardiovascular event,” according to Dr. Borden.

For the more than 80,000 patients over age 60 in the study population, that works out to roughly 8,000 cardiovascular events averted over the course of 10 years, he added.

The 2014 expert panel recommendations were based on a strict evidence-based review of published randomized controlled trials. The guidelines are new enough that it remains unclear if they will be embraced by clinicians or incorporated into performance measures and value-based health care purchasing programs.

 

 

The 2014 guidelines are considered highly controversial. The guideline committee comprising some of the nation’s top hypertension researchers was initially convened to come up with what was intended to be the long-awaited JNC 8 report; however, in the midst of the process the sponsoring National Heart, Lung, and Blood Institute declared it was getting out of the guideline-writing business altogether. As a result, the guidelines ultimately published carried the imprimatur of “the 2014 expert panel,” rather than the more prestigious official stamp of JNC 8.

Indeed, five members of the guideline panel felt strongly enough to break away and issued a minority report (Ann. Intern. Med. 2014;160:499-503) in which they argued there is insufficient evidence of harm stemming from the JNC 7 goal of 140/90 mm Hg in patients over age 60 to justify revising the target to 150/90. They warned that this step could reverse the impressive reductions in cardiovascular and cerebrovascular morbidity and mortality realized in recent decades. And they concluded that the burden of proof should be on those who advocate raising the treatment threshold to 150/90 mm Hg to demonstrate that it has benefit in patients over age 60, which they haven’t done.

“I’m very concerned about the [2014 expert panel] guidelines. Older individuals have the highest prevalence of hypertension, they’re the least adequately controlled, and based on the available data I’m concerned that if people follow the new guidelines there’s going to be an increase in cardiovascular events,” said Dr. Wilbert F. Aronow of New York Medical College, Valhalla, who chaired the writing committee for the first-ever ACC/AHA clinical guidelines for controlling high blood pressure in the elderly (J. Am. Coll. Cardiol. 2011;57:2037-114).

The NCDR PINNACLE Registry and this study were supported by the American College of Cardiology Foundation. Dr. Borden and Dr. Aronow reported having no financial conflicts.

[email protected]

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Key clinical point: Adoption of the less aggressive blood pressure goal of 150/90 mm Hg for patients age 60 and older as recommended in the 2014 expert panel guidelines could result in significantly more harm than good.

Major finding: Patients in cardiology practices who qualified for antihypertensive therapy under the 2003 JNC 7 guidelines but not under the 2014 expert panel guidelines have a baseline 10-year 28% risk of cardiovascular events or stroke using the risk calculator included in the 2013 ACC/AHA cholesterol management guidelines.

Data source: An analysis of 1,185,253 patients in U.S. ambulatory cardiology practices.

Disclosures: The NCDR PINNACLE Registry is supported by the American College of Cardiology Foundation. The presenter reported having no financial conflicts of interest.

Targeting enzyme can eliminate CSCs in AML

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Targeting enzyme can eliminate CSCs in AML

AML cells in the bone marrow

Inhibiting the enzyme 5-lipoxygenase (5-LO) can eradicate cancer stem cell-like cells (CSCs) in acute myeloid leukemia (AML), according to a preclinical study

published in Cancer Research.

Previous research suggested the enzyme is needed to maintain CSCs in chronic myeloid leukemia.

So investigators theorized that 5-LO could be a therapeutic target for AML, as CSCs are thought to cause the spread and relapse of this disease.

To test that theory, the team evaluated the effects of 5-LO inhibition in a PML/RARα-positive model of AML. As a model of CSCs, they used Sca-1+/lin murine hematopoietic stem and progenitor cells (HSPCs), which were retrovirally transduced with PML/RARα.

The researchers targeted 5-LO genetically and pharmacologically. And they found that 5-LO inhibition interfered with the aberrant stem cell capacity of PML/RARα-expressing HSPCs.

Inhibiting 5-LO also inhibited Wnt signaling, which has been shown to be critical for CSC maintenance.

Additional investigation revealed that inhibition of Wnt signaling and CSCs was due to the generation of a catalytically inactive form of 5-LO, which hindered nuclear translocation of β-catenin.

Considering these results together, as well as evidence that CSCs mediate AML relapse, the investigators concluded that eradicating CSCs via 5-LO inhibition may offer a new treatment approach for AML.

“These results form the basis for a possible use of the 5-lipoxygenase inhibitors as stem cell therapy for a sustainable cure for acute myeloid leukemia,” said Martin Ruthardt, MD, of Goethe University in Frankfurt, Germany. “But this must firstly be studied further in preclinical and clinical studies in humans.”

“We are now in the process of examining the molecular mechanism in more detail in order to find out how the inhibitors precisely work on the leukemia stem cells,” added Thorsten Jürgen Maier, MD, PhD, of Goethe University and Aarhus University in Denmark. “We very much hope that our results will be of benefit for leukemia patients.”

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AML cells in the bone marrow

Inhibiting the enzyme 5-lipoxygenase (5-LO) can eradicate cancer stem cell-like cells (CSCs) in acute myeloid leukemia (AML), according to a preclinical study

published in Cancer Research.

Previous research suggested the enzyme is needed to maintain CSCs in chronic myeloid leukemia.

So investigators theorized that 5-LO could be a therapeutic target for AML, as CSCs are thought to cause the spread and relapse of this disease.

To test that theory, the team evaluated the effects of 5-LO inhibition in a PML/RARα-positive model of AML. As a model of CSCs, they used Sca-1+/lin murine hematopoietic stem and progenitor cells (HSPCs), which were retrovirally transduced with PML/RARα.

The researchers targeted 5-LO genetically and pharmacologically. And they found that 5-LO inhibition interfered with the aberrant stem cell capacity of PML/RARα-expressing HSPCs.

Inhibiting 5-LO also inhibited Wnt signaling, which has been shown to be critical for CSC maintenance.

Additional investigation revealed that inhibition of Wnt signaling and CSCs was due to the generation of a catalytically inactive form of 5-LO, which hindered nuclear translocation of β-catenin.

Considering these results together, as well as evidence that CSCs mediate AML relapse, the investigators concluded that eradicating CSCs via 5-LO inhibition may offer a new treatment approach for AML.

“These results form the basis for a possible use of the 5-lipoxygenase inhibitors as stem cell therapy for a sustainable cure for acute myeloid leukemia,” said Martin Ruthardt, MD, of Goethe University in Frankfurt, Germany. “But this must firstly be studied further in preclinical and clinical studies in humans.”

“We are now in the process of examining the molecular mechanism in more detail in order to find out how the inhibitors precisely work on the leukemia stem cells,” added Thorsten Jürgen Maier, MD, PhD, of Goethe University and Aarhus University in Denmark. “We very much hope that our results will be of benefit for leukemia patients.”

AML cells in the bone marrow

Inhibiting the enzyme 5-lipoxygenase (5-LO) can eradicate cancer stem cell-like cells (CSCs) in acute myeloid leukemia (AML), according to a preclinical study

published in Cancer Research.

Previous research suggested the enzyme is needed to maintain CSCs in chronic myeloid leukemia.

So investigators theorized that 5-LO could be a therapeutic target for AML, as CSCs are thought to cause the spread and relapse of this disease.

To test that theory, the team evaluated the effects of 5-LO inhibition in a PML/RARα-positive model of AML. As a model of CSCs, they used Sca-1+/lin murine hematopoietic stem and progenitor cells (HSPCs), which were retrovirally transduced with PML/RARα.

The researchers targeted 5-LO genetically and pharmacologically. And they found that 5-LO inhibition interfered with the aberrant stem cell capacity of PML/RARα-expressing HSPCs.

Inhibiting 5-LO also inhibited Wnt signaling, which has been shown to be critical for CSC maintenance.

Additional investigation revealed that inhibition of Wnt signaling and CSCs was due to the generation of a catalytically inactive form of 5-LO, which hindered nuclear translocation of β-catenin.

Considering these results together, as well as evidence that CSCs mediate AML relapse, the investigators concluded that eradicating CSCs via 5-LO inhibition may offer a new treatment approach for AML.

“These results form the basis for a possible use of the 5-lipoxygenase inhibitors as stem cell therapy for a sustainable cure for acute myeloid leukemia,” said Martin Ruthardt, MD, of Goethe University in Frankfurt, Germany. “But this must firstly be studied further in preclinical and clinical studies in humans.”

“We are now in the process of examining the molecular mechanism in more detail in order to find out how the inhibitors precisely work on the leukemia stem cells,” added Thorsten Jürgen Maier, MD, PhD, of Goethe University and Aarhus University in Denmark. “We very much hope that our results will be of benefit for leukemia patients.”

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HHS and NIH aim to make more trial results public

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HHS and NIH aim to make more trial results public

Preparing for a clinical trial

Credit: Esther Dyson

The US Department of Health and Human Services (HHS) has proposed a rule that would require more public disclosure of clinical trial results.

The Notice of Proposed Rulemaking (NPRM) adds to current requirements for submitting trial information to ClinicalTrials.gov.

Most notably, the rule would require the submission of summary results from studies of products not yet approved by the US Food and Drug Administration

(FDA).

The National Institutes of Health (NIH) have created a draft policy that would extend similar reporting requirements to all clinical trials funded by NIH.

About the NPRM: Who, what, and when

The NPRM details new procedures for meeting the requirements established by the Food and Drug Administration Amendments Act of 2007 (FDAAA) to improve public access to clinical trial information.

The proposed rule specifies how information about a clinical trial would need to be submitted to ClinicalTrials.gov. It would not affect requirements for the design or conduct of clinical trials or for the data that must be collected during these trials.

The rule would apply to controlled, interventional studies of drugs, biological products, and devices that are regulated by the FDA. This excludes phase 1 studies of drugs and biological products and feasibility studies of devices.

In general, clinical trials of products regulated by the FDA will meet one or more of the following criteria: include one or more sites in the US; study a product manufactured in the US or its territories and exported for use in a trial outside the US; or be conducted under an FDA investigational new drug application or investigational device exemption.

The NPRM would require the parties responsible for applicable clinical trials—such as the sponsor or a designated principal investigator—to register the trial at ClinicalTrials.gov no later than 21 days after enrolling the first participant.

Registration consists of submitting 4 categories of data elements that are specified in the NPRM: 1) descriptive information, 2) recruitment information, 3) location and contact information, and 4) administrative information.

The parties responsible for the trial would also be required to submit a summary of the study’s results to ClinicalTrials.gov, generally no later than 12 months after trial completion.

However, the NPRM includes procedures for delaying results submission and for requesting extensions to the results submission deadline for good cause.

NIH policy: Extending the NPRM

The proposed NIH policy would make requirements in the NPRM applicable to all NIH-funded awardees and investigators conducting clinical trials, regardless of study phase, type of intervention, or whether they are subject to the rules proposed in the NPRM.

NIH awardees would be expected to ensure submission to ClinicalTrials.gov of the same type of registration and results information, and in the same timeframes, as responsible parties whose trials are subject to the FDAAA and the regulations proposed in the NPRM.

For clinical trials subject to only the proposed NIH policy (not the FDAAA), the NIH would post submitted information, in general, no later than 30 days after it is submitted.

An NIH-funded clinical trial that is also subject to FDAAA would need to have only one entry in ClinicalTrials.gov containing its registration and results information.

Open for comment

The public may comment on any aspect of the NPRM or the proposed NIH policy.

Written comments on the NPRM should be submitted to docket number NIH-2011-0003 at www.regulations.gov. Commenters should indicate the specific section of the NPRM to which each comment refers.

Written comments on the proposed NIH policy should be submitted to the Office of Clinical Research and Bioethics Policy, Office of Science Policy, NIH, via email at [email protected], mail at 6705 Rockledge Drive, Suite 750, Bethesda, MD 20892, or fax at 301-496-9839.

Publications
Topics

Preparing for a clinical trial

Credit: Esther Dyson

The US Department of Health and Human Services (HHS) has proposed a rule that would require more public disclosure of clinical trial results.

The Notice of Proposed Rulemaking (NPRM) adds to current requirements for submitting trial information to ClinicalTrials.gov.

Most notably, the rule would require the submission of summary results from studies of products not yet approved by the US Food and Drug Administration

(FDA).

The National Institutes of Health (NIH) have created a draft policy that would extend similar reporting requirements to all clinical trials funded by NIH.

About the NPRM: Who, what, and when

The NPRM details new procedures for meeting the requirements established by the Food and Drug Administration Amendments Act of 2007 (FDAAA) to improve public access to clinical trial information.

The proposed rule specifies how information about a clinical trial would need to be submitted to ClinicalTrials.gov. It would not affect requirements for the design or conduct of clinical trials or for the data that must be collected during these trials.

The rule would apply to controlled, interventional studies of drugs, biological products, and devices that are regulated by the FDA. This excludes phase 1 studies of drugs and biological products and feasibility studies of devices.

In general, clinical trials of products regulated by the FDA will meet one or more of the following criteria: include one or more sites in the US; study a product manufactured in the US or its territories and exported for use in a trial outside the US; or be conducted under an FDA investigational new drug application or investigational device exemption.

The NPRM would require the parties responsible for applicable clinical trials—such as the sponsor or a designated principal investigator—to register the trial at ClinicalTrials.gov no later than 21 days after enrolling the first participant.

Registration consists of submitting 4 categories of data elements that are specified in the NPRM: 1) descriptive information, 2) recruitment information, 3) location and contact information, and 4) administrative information.

The parties responsible for the trial would also be required to submit a summary of the study’s results to ClinicalTrials.gov, generally no later than 12 months after trial completion.

However, the NPRM includes procedures for delaying results submission and for requesting extensions to the results submission deadline for good cause.

NIH policy: Extending the NPRM

The proposed NIH policy would make requirements in the NPRM applicable to all NIH-funded awardees and investigators conducting clinical trials, regardless of study phase, type of intervention, or whether they are subject to the rules proposed in the NPRM.

NIH awardees would be expected to ensure submission to ClinicalTrials.gov of the same type of registration and results information, and in the same timeframes, as responsible parties whose trials are subject to the FDAAA and the regulations proposed in the NPRM.

For clinical trials subject to only the proposed NIH policy (not the FDAAA), the NIH would post submitted information, in general, no later than 30 days after it is submitted.

An NIH-funded clinical trial that is also subject to FDAAA would need to have only one entry in ClinicalTrials.gov containing its registration and results information.

Open for comment

The public may comment on any aspect of the NPRM or the proposed NIH policy.

Written comments on the NPRM should be submitted to docket number NIH-2011-0003 at www.regulations.gov. Commenters should indicate the specific section of the NPRM to which each comment refers.

Written comments on the proposed NIH policy should be submitted to the Office of Clinical Research and Bioethics Policy, Office of Science Policy, NIH, via email at [email protected], mail at 6705 Rockledge Drive, Suite 750, Bethesda, MD 20892, or fax at 301-496-9839.

Preparing for a clinical trial

Credit: Esther Dyson

The US Department of Health and Human Services (HHS) has proposed a rule that would require more public disclosure of clinical trial results.

The Notice of Proposed Rulemaking (NPRM) adds to current requirements for submitting trial information to ClinicalTrials.gov.

Most notably, the rule would require the submission of summary results from studies of products not yet approved by the US Food and Drug Administration

(FDA).

The National Institutes of Health (NIH) have created a draft policy that would extend similar reporting requirements to all clinical trials funded by NIH.

About the NPRM: Who, what, and when

The NPRM details new procedures for meeting the requirements established by the Food and Drug Administration Amendments Act of 2007 (FDAAA) to improve public access to clinical trial information.

The proposed rule specifies how information about a clinical trial would need to be submitted to ClinicalTrials.gov. It would not affect requirements for the design or conduct of clinical trials or for the data that must be collected during these trials.

The rule would apply to controlled, interventional studies of drugs, biological products, and devices that are regulated by the FDA. This excludes phase 1 studies of drugs and biological products and feasibility studies of devices.

In general, clinical trials of products regulated by the FDA will meet one or more of the following criteria: include one or more sites in the US; study a product manufactured in the US or its territories and exported for use in a trial outside the US; or be conducted under an FDA investigational new drug application or investigational device exemption.

The NPRM would require the parties responsible for applicable clinical trials—such as the sponsor or a designated principal investigator—to register the trial at ClinicalTrials.gov no later than 21 days after enrolling the first participant.

Registration consists of submitting 4 categories of data elements that are specified in the NPRM: 1) descriptive information, 2) recruitment information, 3) location and contact information, and 4) administrative information.

The parties responsible for the trial would also be required to submit a summary of the study’s results to ClinicalTrials.gov, generally no later than 12 months after trial completion.

However, the NPRM includes procedures for delaying results submission and for requesting extensions to the results submission deadline for good cause.

NIH policy: Extending the NPRM

The proposed NIH policy would make requirements in the NPRM applicable to all NIH-funded awardees and investigators conducting clinical trials, regardless of study phase, type of intervention, or whether they are subject to the rules proposed in the NPRM.

NIH awardees would be expected to ensure submission to ClinicalTrials.gov of the same type of registration and results information, and in the same timeframes, as responsible parties whose trials are subject to the FDAAA and the regulations proposed in the NPRM.

For clinical trials subject to only the proposed NIH policy (not the FDAAA), the NIH would post submitted information, in general, no later than 30 days after it is submitted.

An NIH-funded clinical trial that is also subject to FDAAA would need to have only one entry in ClinicalTrials.gov containing its registration and results information.

Open for comment

The public may comment on any aspect of the NPRM or the proposed NIH policy.

Written comments on the NPRM should be submitted to docket number NIH-2011-0003 at www.regulations.gov. Commenters should indicate the specific section of the NPRM to which each comment refers.

Written comments on the proposed NIH policy should be submitted to the Office of Clinical Research and Bioethics Policy, Office of Science Policy, NIH, via email at [email protected], mail at 6705 Rockledge Drive, Suite 750, Bethesda, MD 20892, or fax at 301-496-9839.

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Drug dubbed ‘breakthrough’ for AL amyloidosis

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Drug dubbed ‘breakthrough’ for AL amyloidosis

Micrograph showing amyloidosis

The US Food and Drug Administration (FDA) has granted breakthrough therapy designation for the oral proteasome inhibitor ixazomib (MLN9708) to treat relapsed or refractory systemic light-chain (AL) amyloidosis.

This is the first proteasome inhibitor and the first investigational therapy for AL amyloidosis to receive breakthrough designation.

Ixazomib already has orphan drug designation in the US and the European Union for this indication and to treat multiple myeloma (MM).

The FDA’s breakthrough therapy designation is intended to expedite the development and review of new medicines to treat serious or life-threatening conditions. Compounds given the designation receive more intensive FDA guidance on an efficient drug development program and an enhanced agency commitment of senior personnel.

Breakthrough therapy designation requires preliminary clinical evidence indicating the drug may demonstrate substantial improvement on a clinically significant endpoint (or endpoints) over available therapies.

The data used to support this designation for ixazomib came from a phase 1 trial that is set to be presented at the 2014 ASH Annual Meeting as abstract 3450.

The development program for ixazomib in AL amyloidosis progressed directly from a phase 1 to a phase 3 clinical trial, TOURMALINE-AL1. Ixazomib is the first oral proteasome inhibitor to enter phase 3 clinical trials, and 4 global phase 3 trials are ongoing:

  • TOURMALINE-MM1, an investigation of ixazomib vs placebo in combination with lenalidomide and dexamethasone in relapsed and/or refractory MM
  • TOURMALINE-AL1, an investigation of ixazomib plus dexamethasone in patients with relapsed or refractory AL amyloidosis
  • TOURMALINE-MM2, an investigation of ixazomib vs placebo in combination with lenalidomide and dexamethasone in patients with newly diagnosed MM
  • TOURMALINE-MM3, an investigation of ixazomib vs placebo as maintenance therapy in patients with newly diagnosed MM following induction therapy and autologous stem cell transplant.

For additional information on the ongoing phase 3 studies, visit www.tourmalinetrials.com or www.clinicaltrials.gov. Ixazomib is under development by Millennium: the Takeda Oncology Company.

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Micrograph showing amyloidosis

The US Food and Drug Administration (FDA) has granted breakthrough therapy designation for the oral proteasome inhibitor ixazomib (MLN9708) to treat relapsed or refractory systemic light-chain (AL) amyloidosis.

This is the first proteasome inhibitor and the first investigational therapy for AL amyloidosis to receive breakthrough designation.

Ixazomib already has orphan drug designation in the US and the European Union for this indication and to treat multiple myeloma (MM).

The FDA’s breakthrough therapy designation is intended to expedite the development and review of new medicines to treat serious or life-threatening conditions. Compounds given the designation receive more intensive FDA guidance on an efficient drug development program and an enhanced agency commitment of senior personnel.

Breakthrough therapy designation requires preliminary clinical evidence indicating the drug may demonstrate substantial improvement on a clinically significant endpoint (or endpoints) over available therapies.

The data used to support this designation for ixazomib came from a phase 1 trial that is set to be presented at the 2014 ASH Annual Meeting as abstract 3450.

The development program for ixazomib in AL amyloidosis progressed directly from a phase 1 to a phase 3 clinical trial, TOURMALINE-AL1. Ixazomib is the first oral proteasome inhibitor to enter phase 3 clinical trials, and 4 global phase 3 trials are ongoing:

  • TOURMALINE-MM1, an investigation of ixazomib vs placebo in combination with lenalidomide and dexamethasone in relapsed and/or refractory MM
  • TOURMALINE-AL1, an investigation of ixazomib plus dexamethasone in patients with relapsed or refractory AL amyloidosis
  • TOURMALINE-MM2, an investigation of ixazomib vs placebo in combination with lenalidomide and dexamethasone in patients with newly diagnosed MM
  • TOURMALINE-MM3, an investigation of ixazomib vs placebo as maintenance therapy in patients with newly diagnosed MM following induction therapy and autologous stem cell transplant.

For additional information on the ongoing phase 3 studies, visit www.tourmalinetrials.com or www.clinicaltrials.gov. Ixazomib is under development by Millennium: the Takeda Oncology Company.

Micrograph showing amyloidosis

The US Food and Drug Administration (FDA) has granted breakthrough therapy designation for the oral proteasome inhibitor ixazomib (MLN9708) to treat relapsed or refractory systemic light-chain (AL) amyloidosis.

This is the first proteasome inhibitor and the first investigational therapy for AL amyloidosis to receive breakthrough designation.

Ixazomib already has orphan drug designation in the US and the European Union for this indication and to treat multiple myeloma (MM).

The FDA’s breakthrough therapy designation is intended to expedite the development and review of new medicines to treat serious or life-threatening conditions. Compounds given the designation receive more intensive FDA guidance on an efficient drug development program and an enhanced agency commitment of senior personnel.

Breakthrough therapy designation requires preliminary clinical evidence indicating the drug may demonstrate substantial improvement on a clinically significant endpoint (or endpoints) over available therapies.

The data used to support this designation for ixazomib came from a phase 1 trial that is set to be presented at the 2014 ASH Annual Meeting as abstract 3450.

The development program for ixazomib in AL amyloidosis progressed directly from a phase 1 to a phase 3 clinical trial, TOURMALINE-AL1. Ixazomib is the first oral proteasome inhibitor to enter phase 3 clinical trials, and 4 global phase 3 trials are ongoing:

  • TOURMALINE-MM1, an investigation of ixazomib vs placebo in combination with lenalidomide and dexamethasone in relapsed and/or refractory MM
  • TOURMALINE-AL1, an investigation of ixazomib plus dexamethasone in patients with relapsed or refractory AL amyloidosis
  • TOURMALINE-MM2, an investigation of ixazomib vs placebo in combination with lenalidomide and dexamethasone in patients with newly diagnosed MM
  • TOURMALINE-MM3, an investigation of ixazomib vs placebo as maintenance therapy in patients with newly diagnosed MM following induction therapy and autologous stem cell transplant.

For additional information on the ongoing phase 3 studies, visit www.tourmalinetrials.com or www.clinicaltrials.gov. Ixazomib is under development by Millennium: the Takeda Oncology Company.

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NICE expands use of ESAs in cancer patients

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Cancer patient receiving

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Credit: Rhoda Baer

The UK’s National Institute for Health and Care Excellence (NICE) has updated its guidance to expand the use of erythropoiesis-stimulating agents (ESAs) in cancer patients.

In 2008, NICE issued a guidance recommending ESAs as a possible treatment for certain patients with anemia caused by cancer treatment.

Now, NICE has updated the recommendations to expand the use of ESAs—epoetin alfa, beta, theta, and zeta, as well as darbepoetin alfa—to all other indications within their UK marketing authorizations.

“A lot of people with cancer having chemotherapy will become anemic,” noted Carole Longson, director of the Centre for Health Technology Evaluation at NICE.

“Managing anemia often requires extra trips to the hospital and can significantly affect a person’s quality of life. This updated final guidance recommends more options, epoetin and darbepoetin, that are both clinically and cost-effective and which also significantly improve quality of life for people who develop anemia whilst having cancer therapy.”

The 2008 NICE guidance recommended erythropoietin analogues with iron injections as a possible treatment for anemia caused by cancer treatment only in:

  • Women receiving platinum-based chemotherapy for cancer of the ovaries who have a blood hemoglobin level of 8 g/100 mL or lower
  • Patients who have very severe anemia and cannot receive blood transfusions.

NICE’s updated final guidance recommends using darbepoetin alfa and epoetin alfa, beta, theta, and zeta within their marketing authorizations as an option for treating anemia in cancer patients undergoing chemotherapy.

Epoetin alfa (Eprex, Janssen-Cilag, and Binocrit, Sandoz), and epoetin zeta (Retacrit, Hospira UK) have UK marketing authorization to treat anemia and to reduce transfusion requirements in adult patients receiving chemotherapy for solid tumors, malignant lymphoma, or multiple myeloma, who are at risk of transfusion as assessed by the patients’ general status (eg, cardiovascular status, pre-existing anemia at the start of chemotherapy).

Binocrit and Retacrit are both biosimilar medicines referenced to Eprex. Eprex, Binocrit, and Retacrit are available in pre-filled syringes at net prices of £5.53, £4.33, and £5.66 per 1000 units, respectively.

Epoetin beta (NeoRecormon, Roche Products) and epoetin theta (Eporatio, Teva UK) have UK marketing authorization to treat symptomatic anemia in adult patients with non-myeloid malignancies who are receiving chemotherapy.

NeoRecormon is available in a pre-filled syringe at a net price of £3.51 per 500 units, and Eporatio is available in a pre-filled syringe at a net price of £5.99 per 1000 units.

Darbepoetin alfa (Aranesp, Amgen) has UK marketing authorization to treat symptomatic anemia in adult cancer patients with non-myeloid malignancies who are receiving chemotherapy. Aranesp is available in a pre-filled syringe at a net price of £14.68 per 10 micrograms.

Costs (excluding value-added tax) may vary in different settings because of negotiated procurement discounts.

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Cancer patient receiving

chemotherapy

Credit: Rhoda Baer

The UK’s National Institute for Health and Care Excellence (NICE) has updated its guidance to expand the use of erythropoiesis-stimulating agents (ESAs) in cancer patients.

In 2008, NICE issued a guidance recommending ESAs as a possible treatment for certain patients with anemia caused by cancer treatment.

Now, NICE has updated the recommendations to expand the use of ESAs—epoetin alfa, beta, theta, and zeta, as well as darbepoetin alfa—to all other indications within their UK marketing authorizations.

“A lot of people with cancer having chemotherapy will become anemic,” noted Carole Longson, director of the Centre for Health Technology Evaluation at NICE.

“Managing anemia often requires extra trips to the hospital and can significantly affect a person’s quality of life. This updated final guidance recommends more options, epoetin and darbepoetin, that are both clinically and cost-effective and which also significantly improve quality of life for people who develop anemia whilst having cancer therapy.”

The 2008 NICE guidance recommended erythropoietin analogues with iron injections as a possible treatment for anemia caused by cancer treatment only in:

  • Women receiving platinum-based chemotherapy for cancer of the ovaries who have a blood hemoglobin level of 8 g/100 mL or lower
  • Patients who have very severe anemia and cannot receive blood transfusions.

NICE’s updated final guidance recommends using darbepoetin alfa and epoetin alfa, beta, theta, and zeta within their marketing authorizations as an option for treating anemia in cancer patients undergoing chemotherapy.

Epoetin alfa (Eprex, Janssen-Cilag, and Binocrit, Sandoz), and epoetin zeta (Retacrit, Hospira UK) have UK marketing authorization to treat anemia and to reduce transfusion requirements in adult patients receiving chemotherapy for solid tumors, malignant lymphoma, or multiple myeloma, who are at risk of transfusion as assessed by the patients’ general status (eg, cardiovascular status, pre-existing anemia at the start of chemotherapy).

Binocrit and Retacrit are both biosimilar medicines referenced to Eprex. Eprex, Binocrit, and Retacrit are available in pre-filled syringes at net prices of £5.53, £4.33, and £5.66 per 1000 units, respectively.

Epoetin beta (NeoRecormon, Roche Products) and epoetin theta (Eporatio, Teva UK) have UK marketing authorization to treat symptomatic anemia in adult patients with non-myeloid malignancies who are receiving chemotherapy.

NeoRecormon is available in a pre-filled syringe at a net price of £3.51 per 500 units, and Eporatio is available in a pre-filled syringe at a net price of £5.99 per 1000 units.

Darbepoetin alfa (Aranesp, Amgen) has UK marketing authorization to treat symptomatic anemia in adult cancer patients with non-myeloid malignancies who are receiving chemotherapy. Aranesp is available in a pre-filled syringe at a net price of £14.68 per 10 micrograms.

Costs (excluding value-added tax) may vary in different settings because of negotiated procurement discounts.

Cancer patient receiving

chemotherapy

Credit: Rhoda Baer

The UK’s National Institute for Health and Care Excellence (NICE) has updated its guidance to expand the use of erythropoiesis-stimulating agents (ESAs) in cancer patients.

In 2008, NICE issued a guidance recommending ESAs as a possible treatment for certain patients with anemia caused by cancer treatment.

Now, NICE has updated the recommendations to expand the use of ESAs—epoetin alfa, beta, theta, and zeta, as well as darbepoetin alfa—to all other indications within their UK marketing authorizations.

“A lot of people with cancer having chemotherapy will become anemic,” noted Carole Longson, director of the Centre for Health Technology Evaluation at NICE.

“Managing anemia often requires extra trips to the hospital and can significantly affect a person’s quality of life. This updated final guidance recommends more options, epoetin and darbepoetin, that are both clinically and cost-effective and which also significantly improve quality of life for people who develop anemia whilst having cancer therapy.”

The 2008 NICE guidance recommended erythropoietin analogues with iron injections as a possible treatment for anemia caused by cancer treatment only in:

  • Women receiving platinum-based chemotherapy for cancer of the ovaries who have a blood hemoglobin level of 8 g/100 mL or lower
  • Patients who have very severe anemia and cannot receive blood transfusions.

NICE’s updated final guidance recommends using darbepoetin alfa and epoetin alfa, beta, theta, and zeta within their marketing authorizations as an option for treating anemia in cancer patients undergoing chemotherapy.

Epoetin alfa (Eprex, Janssen-Cilag, and Binocrit, Sandoz), and epoetin zeta (Retacrit, Hospira UK) have UK marketing authorization to treat anemia and to reduce transfusion requirements in adult patients receiving chemotherapy for solid tumors, malignant lymphoma, or multiple myeloma, who are at risk of transfusion as assessed by the patients’ general status (eg, cardiovascular status, pre-existing anemia at the start of chemotherapy).

Binocrit and Retacrit are both biosimilar medicines referenced to Eprex. Eprex, Binocrit, and Retacrit are available in pre-filled syringes at net prices of £5.53, £4.33, and £5.66 per 1000 units, respectively.

Epoetin beta (NeoRecormon, Roche Products) and epoetin theta (Eporatio, Teva UK) have UK marketing authorization to treat symptomatic anemia in adult patients with non-myeloid malignancies who are receiving chemotherapy.

NeoRecormon is available in a pre-filled syringe at a net price of £3.51 per 500 units, and Eporatio is available in a pre-filled syringe at a net price of £5.99 per 1000 units.

Darbepoetin alfa (Aranesp, Amgen) has UK marketing authorization to treat symptomatic anemia in adult cancer patients with non-myeloid malignancies who are receiving chemotherapy. Aranesp is available in a pre-filled syringe at a net price of £14.68 per 10 micrograms.

Costs (excluding value-added tax) may vary in different settings because of negotiated procurement discounts.

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In‐Hospital Asthma Resource Utilization

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Pediatric hospitalizations for obesity‐related conditions have doubled in the last decade, mirroring the trend of higher levels of childhood obesity in the United States.[1, 2, 3] Recent studies have demonstrated worsened pediatric in‐hospital outcomes, including mortality and increased resource utilization, for children with obesity across a range of diagnoses.[4, 5, 6, 7, 8, 9, 10] Although the mechanisms driving the association between obesity and in‐hospital outcomes are not fully known, for asthma it is believed that adipocytes expressing inflammatory markers create a low level of systemic inflammation, thereby increasing the severity of allergic‐type illnesses and decreasing the response to anti‐inflammatory medications, such as steroids.[11, 12, 13, 14, 15, 16, 17, 18] The relationship of obesity and in‐hospital asthma outcomes is of particular interest because status asthmaticus is the most common reason for admission in children aged 3 to 12 years, accounting for approximately 150,000 admissions (7.4% of all hospitalizations for children and adolescents) and $835 million in hospital costs annually.[19]

Few prior studies have examined the association of obesity and asthma outcomes in the in‐hospital setting. The studies examining this association have found patients with obesity to have a longer hospital length of stay (LOS) and increased hospital costs.[8, 9, 20] Obesity has also been associated with increased respiratory treatments and supplemental oxygen requirements.[20] Associations between obesity and admission rates from the emergency department (ED) for pediatric asthma have been inconsistent.[21, 22] Most of these prior studies had several limitations in identifying patients with obesity, including using weight‐for‐age percentiles or International Classification of Diseases, Ninth Revision (ICD‐9) codes, rather than body mass index (BMI) percentile for age, the currently recommended method.[23, 24, 25] Methods other than BMI have the potential to either underestimate obesity (ie, ICD‐9 codes)[26] or to confound weight with adiposity (ie, weight‐for‐age percentiles),[27] thereby skewing the primary exposure of interest.

In the present study, we sought to examine associations between obesity and in‐hospital outcomes for pediatric status asthmaticus using the currently endorsed method for identifying obesity in children, BMI percentile for age.[23, 24, 25] The outcomes of interest included a broad range of in‐hospital measures, including resource utilization (medication and radiology use), readmission rates, billed charges, and LOS. We hypothesize that obesity, due to its proinflammatory state, would result in increased LOS, increased resource utilization, and an increased readmission rate for children admitted with status asthmaticus.

METHODS

Data Sources

Data for this retrospective cross‐sectional study were obtained from 2 sources. First, we queried the Pediatric Health Information System (PHIS) administrative database, which draws information from multiple children's hospitals to identify patients at our 2 institutions of interest who met study criteria. The PHIS database also was used to collect patient demographic data. PHIS is an administrative database operated by Children's Hospital Association (Overland Park, KS) containing clinical and billing data from 43 tertiary care, freestanding children's hospitals, including data on 41 ICD‐9 diagnoses, billed charges, and LOS. Based on the primary diagnosis, PHIS assigns each discharge to an All Patient Refined‐Diagnosis Related Group (APR‐DRG v.24) (3M Health information Systems, St. Paul, MN). APR‐DRGs allow similar diagnoses to be grouped together.[28, 29] PHIS also uses ICD‐9 codes to identify patients with a complex chronic condition (CCC).[30, 31] CCCs are those conditions that can be reasonably expected to last at least 12 months (unless death intervenes) and to involve either several different organ systems or one system severely enough to require specialty pediatric care and probably some period of hospitalization in a tertiary care center.[30, 31] PHIS data quality is ensured through a collaborative effort of the participating hospitals, the Children's Hospital Association, and Truven Healthcare.

Second, standardized chart reviews were then performed to collect clinical data not found in PHIS: BMI, LOS in hours, and medications administered, including total number of albuterol treatments administered during both the admission and the associated preceding ED visit.

Study Setting and Participants

All admissions examined in this study were at Children's Mercy Hospitals. Children's Mercy Hospitals includes 2 separate hospitals: 1 hospital is a 354‐bed academic, tertiary care freestanding children's hospital located in Kansas City, Missouri; a second, smaller, 50‐bed freestanding hospital is located in Overland Park, Kansas. Both hospitals have pediatric emergency departments. Inclusion criteria included patients aged 5 to 17 years discharged for status asthmaticus (APR‐DRG 141) at Children's Mercy Hospital from October 1, 2011 to September 30, 2012, with a recorded BMI during the admission or within 30 days of the admission. Patients between the ages of 2 and 5 years old were not included because of the incidence of viral‐induced wheezing in this age group and therefore possible miscoding of the asthma diagnosis. Exclusion criteria included a concurrent diagnosis of a CCC or bacterial pneumonia because these conditions could alter LOS, resource utilization, and readmission rates independent of the subject's status asthmaticus. In addition, to account for differences in the amount of treatment given in the pre‐inpatient setting, patients not initially treated through the hospital's ED were excluded. For patients with multiple admissions during the study period for the same diagnosis, only the index admission was examined. The institutional review board at Children's Mercy Hospital approved this study with waiver of informed consent.

Study Definitions

BMI percentile for age was used as both a continuous and categorical predictor variable. As a categorical variable it was divided into 4 categories: underweight (BMI <5%), normal weight (BMI 5%84%), overweight (BMI 85%94%), and obese (BMI 95%).[23] Race was categorized non‐Hispanic white, non‐Hispanic black, and other. Other included Asian, Pacific Islander, American Indian, and other. Ethnicity was categorized as Hispanic and non‐Hispanic. Insurance categories included private (commercial or TRICARE), public (Medicaid and Title V), and other (uninsured, self‐pay, and other). Adjusted billed charges were calculated for each hospitalization. Adjusted billed charges are the billed charges adjusted by the US Centers of Medicare and Medicaid Services' price/wage index for the study site's location.[32, 33]

To compare albuterol of different delivery methods, albuterol equivalents were calculated. Based upon prior research demonstrating equal efficacy between albuterol administered by nebulizer and metered‐dose inhaler (MDI),[34] every 2.5 mg of albuterol administered by nebulizer was treated as equivalent to 2 sprays of albuterol (90 g/spray) administered by MDI. Therefore, albuterol 2.5 mg nebulized and 2 sprays of albuterol (90 g/spray) were each defined as 1 albuterol equivalent. To compare continuous administration of nebulized albuterol with intermittent administration of albuterol, the total milligrams of continuously nebulized albuterol were examined. Per protocol at the study site, 10 mg per hour of continuous albuterol are administered for patients 5 years and younger and, for children 6 years and older, 15 mg per hour of continuous albuterol are administered. Based upon milligrams of albuterol nebulized, 5‐year‐old subjects receiving an hour of continuous albuterol would equal 4 albuterol equivalents (or 4 treatments of nebulized albuterol 2.5 mg/treatment or 4 treatments of albuterol 90 g/spray 2 sprays/treatment); for patients 6 years and older, an hour of continuous albuterol would equal 6 albuterol equivalents (or 6 treatments of nebulized albuterol 2.5 mg/treatment or 6 treatments of albuterol 90 g/spray 2 sprays/treatment). The variable total albuterol was then created to include albuterol equivalents delivered by metered dose inhaler and as both single and continuous nebulized treatments.

Main Exposure

The main exposure of interest was BMI percentile for age.

Outcome Measures

The main outcome measure was inpatient LOS measured in hours. Secondary outcome measures included the total albuterol (in the inpatient setting as well as combined inpatient and ED settings) and the administration of intravenous IV fluids and intramuscular (IM) or IV systemic steroids. Other secondary measures included readmission for status asthmaticus during the study period, adjusted billed charges, and inpatient chest radiograph utilization.

Statistical Analyses

We summarized categorical variables with frequencies and percentages, and used [2] test across BMI categories. The non‐normal distribution of continuous dependent variables (LOS, number of albuterol treatments, billed charges) were summarized with medians and interquartile ranges (IQRs). Kruskal‐Wallis test was used to examine outcomes across BMI categories. For regression models, BMI percentile for age was divided into deciles and treated as a continuous predictor. Factors used in the regression models included age, gender, race, ethnicity, and insurance. Total albuterol received in the ED was also included in the model to adjust for differences in the amount of treatment received prior to admission. Incidence rate ratios were created using Poisson regression for continuous outcomes (LOS, billed charges, and number of albuterol equivalent treatments administered), and odds ratios were created using logistic regression for dichotomous outcomes. All statistical analyses were performed using IBM SPSS Statistics version 20 (IBM, Armonk, NY), and P values <0.05 were considered statistically significant.

RESULTS

Patient Characteristics

Of 788 patients admitted for status asthmaticus during the study period, 518 (65.7%) met inclusion criteria; 42 (5.3%) did not meet inclusion criteria due to lack of a documented BMI (Table 1). Most patients were normal weight (59.7%). Approximately one‐third (36.7%) were either overweight or obese. The median age was 8 years, with patients with obesity being significantly older than underweight patients (9 vs 7.5 years, P<0.001). The majority of patients were black/African American (56.9%) and non‐Hispanic (88.6%). The percentage of patients who were obese was higher in patients of other race (29.3%) than whites (20.2%) or blacks (16.3%) (P<0.05). Patients of Hispanic ethnicity had a higher rate of obesity compared to non‐Hispanic patients (37.3% vs 17.4%, P<0.01). There were no differences in BMI categories for insurance.

Patient Characteristics by Body Mass Index Category
Patient CharacteristicsTotalCategory of Body Mass Index Percentile for Age
UnderweightNormalOverweightObeseP*
  • NOTE: Abbreviations: IQR, interquartile range. *Categorical variables were compared by 2 test, and continuous variables were compared by Kruskall‐Wallis test.

Total patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7) 
Age, y, median (IQR)8 (611)7.5 (5.89)8 (610)8 (610)9 (712)<0.001
Gender, n (%)      
Male30912 (3.9)184 (59.5)46 (14.9)67 (21.7)0.27
Female2096 (2.9)126 (60.3)42 (20.1)35 (16.7) 
Race, n (%)      
Non‐Hispanic white1248 (6.5)76 (61.3)15 (12.1)25 (20.2)0.021
Non‐Hispanic black2957 (2.4)182 (61.7)58 (19.7)48 (16.3) 
Other993 (3.0)52 (52.5)15 (15.2)29 (29.3) 
Ethnicity, n (%)      
Hispanic591 (1.7)25 (42.4)11 (18.6)22 (37.3)0.002
Non‐Hispanic45917 (3.7)285 (62.1)77 (16.8)80 (17.4) 
Insurance, n (%)      
Private16310 (6.1)97 (59.5)28 (17.2)28 (17.2)0.48
Public3137 (2.2)190 (60.7)51 (16.3)65 (20.8) 
Other421 (2.4)23 (54.8)9 (21.4)9 (21.4) 

LOS and Resource Utilization

The median LOS for all patients was approximately 1 day (Table 2). The median number of albuterol treatments in the inpatient setting was 14 (IQR, 824). When albuterol treatments given in the ED were included, the median number of treatments increased to 38 (IQR, 2848). Approximately one‐half of patients required supplemental oxygen, one‐third received IV fluids, and one‐fifth received either IV or IM steroids (with all but 1.6% of the remaining patients receiving oral steroids). Less than 5% of the study population received magnesium sulfate, epinephrine, required intensive care unit (ICU) admission, or were readmitted for status asthmaticus within 30 days. Approximately 15% of patients received a chest radiograph. The median adjusted billed charge was approximately $7,000. There were no differences in any of these outcomes by BMI category (P>0.05).

Resource Utilization, Readmissions, Length of Stay, and Billed Charges for In‐Hospital Status Asthmaticus by Body Mass Index Category
 TotalBody Mass Index Category
UnderweightNormalOverweightObese
  • NOTE: Abbreviations: ICU, intensive care unit; IM, intramuscular; IQR, interquartile range; IV, intravenous. *All differences between body mass index categories were nonsignificant (P>0.05).

Total Patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7)
LOS, h, median (IQR)26 (1841)41 (19.560.5)26 (1841)26 (19.2540)31 (1942)
Inpatient albuterol equivalents, median (IQR)14(824)19 (9.528)14 (824)14 (8.522)16 (824)
Total albuterol equivalents, median (IQR)38 (2848)34 (2734)36 (2848)37 (2849.5)40 (3052)
Adjusted billed charges, $, median (IQR)6,999.5 (52929258)7,457 (56048536)6876 (52379390)7056 (54099061)7198 (53319306)
All readmits, n (%)44 (8.5)2 (11.1)29 (9.4)7 (8.0)6 (5.9)
Readmits within 30 days, n (%)11 (2.1)1 (5.6)7 (2.3)1 (1.1)2 (2.0)
ICU admissions, n (%)24 (4.6)0 (0)13 (4.2)7 (8.0)4 (3.9)
Chest radiograph, n (%)64 (12.4)5 (27.8)34 (11.0)12 (13.6)13 (12.7)
Oxygen, n (%)255 (49.2)11 (61.1)157 (50.6)42 (47.7)45 (44.1)
IV/IM steroid, n (%)93 (18.0)2 (11.1)53 (17.1)18 (20.5)20 (19.6)
Epinephrine, n (%)2 (0.4)0 (0)2 (0.6)0 (0)0 (0)
Magnesium, n (%)15 (2.9)0 (0)8 (2.6)3 (3.4)4 (3.9)
IV fluids, n (%)152 (29.3)4 (22.2)85 (27.4)31 (35.2)32 (31.4)

Multivariable Results

After adjusting for age, gender, race, ethnicity, and insurance, the decile of BMI percentile for age showed a small negative association with LOS. Specifically, for each decile increase for BMI percentile for age, LOS decreased by approximately 2%. BMI percentile for age was not associated with other measures of resource utilization including total albuterol use, adjusted billed charges, readmission, ICU care, receipt of supplemental oxygen or a chest radiograph, IV fluids, or other medications (IV/IM steroids, epinephrine, or magnesium sulfate).

DISCUSSION

Our study suggests that the decile of BMI percentile for age is inversely associated with LOS but did not have a clinically meaningful effect. Secondary measures, such as total albuterol needs and adjusted billed charges, did not show an association with BMI percentile for age. There were also no associations between BMI percentile for age and other resource utilization outcomes.

Our findings differ from previous studies examining in‐hospital status asthmaticus in children who are overweight or obese. In addition, the present study was able to adjust for therapies received prior to admission. Carroll et al. demonstrated an increased LOS of approximately 3 days for overweight or obese asthmatics admitted to the ICU with status asthmaticus as well as increased duration of supplemental oxygen, continuous albuterol, and intravenous steroids.[20] It is possible that differences in methodology (ie, weight‐for‐age percentile vs BMI percentile for age, inclusion of ED treatments), different thresholds for treatment of status asthmaticus outside the ICU, or differences in patient populations studied (ie, only ICU patients vs all in‐hospital patients) explain the difference between their findings and the present study. The present study's use of BMI percentile for age follows current recommendations for classifying a patient as obese or overweight.[23, 24, 25] However, the use of classifications other than BMI percentile for age would tend to bias toward the null hypothesis, whereas in Carroll's study children who were overweight or obese had increased resource utilization. Additionally, in the time frame between this publication and the current study, many hospitals worked to standardize asthma hospitalizations by creating weaning protocols for albuterol, thereby decreasing LOS for all asthmatics, which may also affect the differences in LOS between groups of obese and nonobese patients.[35]

Woolford et al. found approximately a one‐half‐day increase in LOS and $2,000 higher mean charges for patients admitted with status asthmaticus and a secondary diagnosis of obesity.[8, 9] Study location and differing methods for defining obesity may account for the discrepancy between Woolford's findings and our study. We examined children admitted to the inpatient floor of a tertiary care children's hospital compared to Woolford et al.'s examination of pediatric patients admitted to all hospitals via the Kids' Inpatient Database (Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality). That study also relied on the coding of obesity as an ICD‐9 diagnosis, rather than examining the BMI of all admitted patients. Previous research has demonstrated that relying on a coded diagnosis of obesity is not as sensitive as measurement.[26] By relying on ICD‐9 diagnosis coding, only patients with very high BMIs may be diagnosed with obesity during the admission and therefore only associations between very high BMI and status asthmaticus will be examined.

There are several limitations to our findings. First, our study was limited to a single, tertiary care children's hospital and may not be generalizable to other hospitals. Our hospital standardizes the treatment of inpatient status asthmatics by formation of a respiratory care plan, involving interval scoring of respiratory symptoms and automatic spacing of albuterol treatments. This likely minimizes physician‐to‐physician variation. Second, we included only those patients who were initially treated within the ED associated with the admitting hospital to minimize the effects of timing for treatments prior to admittance. This excluded those patients first cared for by their primary care physician or by an outlying ED. Therefore, our sample may be biased toward a study population less connected to a medical home and therefore possibly poorer asthma control. Third, to utilize the most accurate method to define obesity, we excluded approximately 5% of eligible patients because BMI was unavailable. This may have included children with more severe asthma symptoms, as a height measurement may have been deferred due to their higher acuity. Asthma severity or chronicity would be associated with our outcomes of interest. However, we were unable to collect reliable data on severity or chronicity. Finally, to measure the amount of total albuterol needed by a patient during the ED and inpatient admissions, albuterol treatments delivered by MDI, nebulizer, or continuously were converted into total albuterol. Although based upon total milligram dosing and studies comparing routes of albuterol administration,[34] the validity of this conversion is unknown.

CONCLUSION

Although BMI percentile for age is inversely associated with LOS for in‐hospital pediatric status asthmaticus, the impact of BMI on this outcome likely is not clinically meaningful. Future investigations should examine other elements of BMI and in‐hospital status asthmaticus, such as any associations between BMI and admission rates.

Acknowledgements

The authors offer their appreciation to their research assistant, Amy Lee, for her support and dedication to this project.

Disclosures

Internal funds from Children's Mercy Hospital and Clinics supported the conduct of this work. The authors report no conflicts of interest.

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References
  1. Cunningham SA, Kramer MR, Narayan KMV. Incidence of childhood obesity in the United States. N Engl J Med. 2014;370(5):403411.
  2. Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA Pediatr. 2014;168(6):561566.
  3. Trasande L, Liu Y, Fryer G, Weitzman M. Effects of childhood obesity on hospital care and costs, 1999–2005. Health Affairs. 2009;28(4):w751w760.
  4. Bechard LJ, Rothpletz‐Puglia P, Touger‐Decker R, Duggan C, Mehta NM. Influence of obesity on clinical outcomes in hospitalized children: a systematic review. JAMA Pediatr. 2013;167(5):476482.
  5. Davies DA, Yanchar NL. Appendicitis in the obese child. J Pediatr Surg. 2007;42(5):857861.
  6. Patel L, Cowden JD, Dowd D, Hampl S, Felich N. Obesity: influence on length of hospital stay for the pediatric burn patient. J Burn Care Res. 2010;31(2):251256.
  7. Brown CVR, Neville AL, Salim A, Rhee P, Cologne K, Demetriades D. The impact of obesity on severely injured children and adolescents. J Pediatr Surg. 2006;41(1):8891.
  8. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Incremental hospital charges associated with obesity as a secondary diagnosis in children. Obesity (Silver Spring). 2007;15(7):18951901.
  9. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Persistent gap of incremental charges for obesity as a secondary diagnosis in common pediatric hospitalizations. J Hosp Med. 2009;4(3):149156.
  10. Hampl SE, Carroll CA, Simon SD, Sharma V. Resource utilization and expenditures for overweight and obese children. Arch Pediatr Adolesc Med. 2007;161(1):1114.
  11. Forno E, Lescher R, Strunk R, Weiss S, Fuhlbrigge A, Celedon JC. Decreased response to inhaled steroids in overweight and obese asthmatic children. J Allergy Clin Immunol. 2011;127(3):741749.
  12. Sutherland ER, Goleva E, Strand M, Beuther DA, Leung DYM. Body mass and glucocorticoid response in asthma. Am J Respir Crit Care Med. 2008;178(7):682687.
  13. Sutherland ER, Lehman EB, Teodorescu M, Wechsler ME; National Heart, Lung, and Blood Institute's Asthma Clinical Research Network. Body mass index and phenotype in subjects with mild‐to‐moderate persistent asthma. J Allergy Clin Immunol. 2009;123(6):13281334.e1.
  14. Stream AR, Sutherland ER. Obesity and asthma disease phenotypes. Curr Opin Allergy Clin Immunol. 2012;12(1):7681.
  15. Sin DD, Sutherland ER. Obesity and the lung: 4. Obesity and asthma. Thorax. 2008;63(11):10181023.
  16. Camargo CA, Boulet L‐P, Sutherland ER, et al. Body mass index and response to asthma therapy: fluticasone propionate/salmeterol versus montelukast. J Asthma. 2010;47(1):7682.
  17. Dixon AE, Shade DM, Cohen RI, et al. Effect of obesity on clinical presentation and response to treatment in asthma. J Asthma. 2006;43(7):553558.
  18. Suglia SF, Chambers EC, Rosario A, Duarte CS. Asthma and obesity in three‐year‐old urban children: role of sex and home environment. J Pediatr. 2011;159(1):1420.
  19. Owens PL, Thompson J, Elixhauser A, Ryan K. Care of Children and Adolescents in U.S. Hospitals. Rockville, MD: Agency for Healthcare Research and Quality; 2003. Available at: http://archive.ahrq.gov/data/hcup/factbk4/factbk4.pdf. Accessed February 12, 2014.
  20. Carroll CL, Bhandari A, Zucker AR, Schramm CM. Childhood obesity increases duration of therapy during severe asthma exacerbations. Pediatr Crit Care Med. 2006;7(6):527531.
  21. Carroll CL, Stoltz P, Raykov N, Smith SR, Zucker AR. Childhood overweight increases hospital admission rates for asthma. Pediatr. 2007;120(4):734740.
  22. Ginde AA, Santillan AA, Clark S, Camargo CA. Body mass index and acute asthma severity among children presenting to the emergency department. Pediatr Allergy Immunol. 2009;21(3):480488.
  23. Centers for Disease Control and Prevention. Basics about childhood obesity. Available at: http://www.cdc.gov/obesity/childhood/basics.html. Accessed February 12, 2014.
  24. Whitlock EP. Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. Pediatrics. 2005;116(1):e125e144.
  25. Barlow SE; Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164S192.
  26. Kuhle S, Kirk SFL, Ohinmaa A, Veugelers PJ. Comparison of ICD code‐based diagnosis of obesity with measured obesity in children and the implications for health care cost estimates. BMC Med Res Methodol. 2011;11(1):173.
  27. Krebs NF, Jacobson MS; American Academy of Pediatrics Committee on Nutrition. Prevention of pediatric overweight and obesity. Pediatrics. 2003;112(2):424430.
  28. Hughes J. Development of the 3M all patient‐refined diagnosis‐related groups (APR DRGs). Available at: http//www.ahrq.gov/legacy/qual/mortality/Hughes3.htm. Accessed March 1, 2014.
  29. Hughes J. 3M Health Information Systems (HIS) APR‐DRG classification software: overview. Available at: http://www.ahrq.gov/legacy/qual/mortality/Hughessumm.htm. Accessed March 1, 2014.
  30. Feudtner C, Feinstein JA, Satchell M, Zhao H, Kang TI. Shifting place of death among children with complex chronic conditions in the United States, 1989–2003. JAMA. 2007;297(24):27252732.
  31. Feudtner C, Christakis DA, Connell FA. Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997. Pediatrics. 2000;106(1 pt 2):205209.
  32. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256263.
  33. Weiss AK, Hall M, Lee GE, Kronman MP, Sheffler‐Collins S, Shah SS. Adjunct corticosteroids in children hospitalized with community‐acquired pneumonia. Pediatrics. 2011;127(2):e255e263.
  34. Cates CJ, Welsh EJ, Rowe BH. Holding chambers (spacers) versus nebulisers for beta‐agonist treatment of acute asthma. Cochrane Database Syst Rev. 2013;9:CD000052.
  35. Johnson KB, Blaisdell CJ, Walker A, Eggleston P. Effectiveness of a clinical pathway for inpatient asthma management. Pediatrics. 2000;106(5):10061012.
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Pediatric hospitalizations for obesity‐related conditions have doubled in the last decade, mirroring the trend of higher levels of childhood obesity in the United States.[1, 2, 3] Recent studies have demonstrated worsened pediatric in‐hospital outcomes, including mortality and increased resource utilization, for children with obesity across a range of diagnoses.[4, 5, 6, 7, 8, 9, 10] Although the mechanisms driving the association between obesity and in‐hospital outcomes are not fully known, for asthma it is believed that adipocytes expressing inflammatory markers create a low level of systemic inflammation, thereby increasing the severity of allergic‐type illnesses and decreasing the response to anti‐inflammatory medications, such as steroids.[11, 12, 13, 14, 15, 16, 17, 18] The relationship of obesity and in‐hospital asthma outcomes is of particular interest because status asthmaticus is the most common reason for admission in children aged 3 to 12 years, accounting for approximately 150,000 admissions (7.4% of all hospitalizations for children and adolescents) and $835 million in hospital costs annually.[19]

Few prior studies have examined the association of obesity and asthma outcomes in the in‐hospital setting. The studies examining this association have found patients with obesity to have a longer hospital length of stay (LOS) and increased hospital costs.[8, 9, 20] Obesity has also been associated with increased respiratory treatments and supplemental oxygen requirements.[20] Associations between obesity and admission rates from the emergency department (ED) for pediatric asthma have been inconsistent.[21, 22] Most of these prior studies had several limitations in identifying patients with obesity, including using weight‐for‐age percentiles or International Classification of Diseases, Ninth Revision (ICD‐9) codes, rather than body mass index (BMI) percentile for age, the currently recommended method.[23, 24, 25] Methods other than BMI have the potential to either underestimate obesity (ie, ICD‐9 codes)[26] or to confound weight with adiposity (ie, weight‐for‐age percentiles),[27] thereby skewing the primary exposure of interest.

In the present study, we sought to examine associations between obesity and in‐hospital outcomes for pediatric status asthmaticus using the currently endorsed method for identifying obesity in children, BMI percentile for age.[23, 24, 25] The outcomes of interest included a broad range of in‐hospital measures, including resource utilization (medication and radiology use), readmission rates, billed charges, and LOS. We hypothesize that obesity, due to its proinflammatory state, would result in increased LOS, increased resource utilization, and an increased readmission rate for children admitted with status asthmaticus.

METHODS

Data Sources

Data for this retrospective cross‐sectional study were obtained from 2 sources. First, we queried the Pediatric Health Information System (PHIS) administrative database, which draws information from multiple children's hospitals to identify patients at our 2 institutions of interest who met study criteria. The PHIS database also was used to collect patient demographic data. PHIS is an administrative database operated by Children's Hospital Association (Overland Park, KS) containing clinical and billing data from 43 tertiary care, freestanding children's hospitals, including data on 41 ICD‐9 diagnoses, billed charges, and LOS. Based on the primary diagnosis, PHIS assigns each discharge to an All Patient Refined‐Diagnosis Related Group (APR‐DRG v.24) (3M Health information Systems, St. Paul, MN). APR‐DRGs allow similar diagnoses to be grouped together.[28, 29] PHIS also uses ICD‐9 codes to identify patients with a complex chronic condition (CCC).[30, 31] CCCs are those conditions that can be reasonably expected to last at least 12 months (unless death intervenes) and to involve either several different organ systems or one system severely enough to require specialty pediatric care and probably some period of hospitalization in a tertiary care center.[30, 31] PHIS data quality is ensured through a collaborative effort of the participating hospitals, the Children's Hospital Association, and Truven Healthcare.

Second, standardized chart reviews were then performed to collect clinical data not found in PHIS: BMI, LOS in hours, and medications administered, including total number of albuterol treatments administered during both the admission and the associated preceding ED visit.

Study Setting and Participants

All admissions examined in this study were at Children's Mercy Hospitals. Children's Mercy Hospitals includes 2 separate hospitals: 1 hospital is a 354‐bed academic, tertiary care freestanding children's hospital located in Kansas City, Missouri; a second, smaller, 50‐bed freestanding hospital is located in Overland Park, Kansas. Both hospitals have pediatric emergency departments. Inclusion criteria included patients aged 5 to 17 years discharged for status asthmaticus (APR‐DRG 141) at Children's Mercy Hospital from October 1, 2011 to September 30, 2012, with a recorded BMI during the admission or within 30 days of the admission. Patients between the ages of 2 and 5 years old were not included because of the incidence of viral‐induced wheezing in this age group and therefore possible miscoding of the asthma diagnosis. Exclusion criteria included a concurrent diagnosis of a CCC or bacterial pneumonia because these conditions could alter LOS, resource utilization, and readmission rates independent of the subject's status asthmaticus. In addition, to account for differences in the amount of treatment given in the pre‐inpatient setting, patients not initially treated through the hospital's ED were excluded. For patients with multiple admissions during the study period for the same diagnosis, only the index admission was examined. The institutional review board at Children's Mercy Hospital approved this study with waiver of informed consent.

Study Definitions

BMI percentile for age was used as both a continuous and categorical predictor variable. As a categorical variable it was divided into 4 categories: underweight (BMI <5%), normal weight (BMI 5%84%), overweight (BMI 85%94%), and obese (BMI 95%).[23] Race was categorized non‐Hispanic white, non‐Hispanic black, and other. Other included Asian, Pacific Islander, American Indian, and other. Ethnicity was categorized as Hispanic and non‐Hispanic. Insurance categories included private (commercial or TRICARE), public (Medicaid and Title V), and other (uninsured, self‐pay, and other). Adjusted billed charges were calculated for each hospitalization. Adjusted billed charges are the billed charges adjusted by the US Centers of Medicare and Medicaid Services' price/wage index for the study site's location.[32, 33]

To compare albuterol of different delivery methods, albuterol equivalents were calculated. Based upon prior research demonstrating equal efficacy between albuterol administered by nebulizer and metered‐dose inhaler (MDI),[34] every 2.5 mg of albuterol administered by nebulizer was treated as equivalent to 2 sprays of albuterol (90 g/spray) administered by MDI. Therefore, albuterol 2.5 mg nebulized and 2 sprays of albuterol (90 g/spray) were each defined as 1 albuterol equivalent. To compare continuous administration of nebulized albuterol with intermittent administration of albuterol, the total milligrams of continuously nebulized albuterol were examined. Per protocol at the study site, 10 mg per hour of continuous albuterol are administered for patients 5 years and younger and, for children 6 years and older, 15 mg per hour of continuous albuterol are administered. Based upon milligrams of albuterol nebulized, 5‐year‐old subjects receiving an hour of continuous albuterol would equal 4 albuterol equivalents (or 4 treatments of nebulized albuterol 2.5 mg/treatment or 4 treatments of albuterol 90 g/spray 2 sprays/treatment); for patients 6 years and older, an hour of continuous albuterol would equal 6 albuterol equivalents (or 6 treatments of nebulized albuterol 2.5 mg/treatment or 6 treatments of albuterol 90 g/spray 2 sprays/treatment). The variable total albuterol was then created to include albuterol equivalents delivered by metered dose inhaler and as both single and continuous nebulized treatments.

Main Exposure

The main exposure of interest was BMI percentile for age.

Outcome Measures

The main outcome measure was inpatient LOS measured in hours. Secondary outcome measures included the total albuterol (in the inpatient setting as well as combined inpatient and ED settings) and the administration of intravenous IV fluids and intramuscular (IM) or IV systemic steroids. Other secondary measures included readmission for status asthmaticus during the study period, adjusted billed charges, and inpatient chest radiograph utilization.

Statistical Analyses

We summarized categorical variables with frequencies and percentages, and used [2] test across BMI categories. The non‐normal distribution of continuous dependent variables (LOS, number of albuterol treatments, billed charges) were summarized with medians and interquartile ranges (IQRs). Kruskal‐Wallis test was used to examine outcomes across BMI categories. For regression models, BMI percentile for age was divided into deciles and treated as a continuous predictor. Factors used in the regression models included age, gender, race, ethnicity, and insurance. Total albuterol received in the ED was also included in the model to adjust for differences in the amount of treatment received prior to admission. Incidence rate ratios were created using Poisson regression for continuous outcomes (LOS, billed charges, and number of albuterol equivalent treatments administered), and odds ratios were created using logistic regression for dichotomous outcomes. All statistical analyses were performed using IBM SPSS Statistics version 20 (IBM, Armonk, NY), and P values <0.05 were considered statistically significant.

RESULTS

Patient Characteristics

Of 788 patients admitted for status asthmaticus during the study period, 518 (65.7%) met inclusion criteria; 42 (5.3%) did not meet inclusion criteria due to lack of a documented BMI (Table 1). Most patients were normal weight (59.7%). Approximately one‐third (36.7%) were either overweight or obese. The median age was 8 years, with patients with obesity being significantly older than underweight patients (9 vs 7.5 years, P<0.001). The majority of patients were black/African American (56.9%) and non‐Hispanic (88.6%). The percentage of patients who were obese was higher in patients of other race (29.3%) than whites (20.2%) or blacks (16.3%) (P<0.05). Patients of Hispanic ethnicity had a higher rate of obesity compared to non‐Hispanic patients (37.3% vs 17.4%, P<0.01). There were no differences in BMI categories for insurance.

Patient Characteristics by Body Mass Index Category
Patient CharacteristicsTotalCategory of Body Mass Index Percentile for Age
UnderweightNormalOverweightObeseP*
  • NOTE: Abbreviations: IQR, interquartile range. *Categorical variables were compared by 2 test, and continuous variables were compared by Kruskall‐Wallis test.

Total patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7) 
Age, y, median (IQR)8 (611)7.5 (5.89)8 (610)8 (610)9 (712)<0.001
Gender, n (%)      
Male30912 (3.9)184 (59.5)46 (14.9)67 (21.7)0.27
Female2096 (2.9)126 (60.3)42 (20.1)35 (16.7) 
Race, n (%)      
Non‐Hispanic white1248 (6.5)76 (61.3)15 (12.1)25 (20.2)0.021
Non‐Hispanic black2957 (2.4)182 (61.7)58 (19.7)48 (16.3) 
Other993 (3.0)52 (52.5)15 (15.2)29 (29.3) 
Ethnicity, n (%)      
Hispanic591 (1.7)25 (42.4)11 (18.6)22 (37.3)0.002
Non‐Hispanic45917 (3.7)285 (62.1)77 (16.8)80 (17.4) 
Insurance, n (%)      
Private16310 (6.1)97 (59.5)28 (17.2)28 (17.2)0.48
Public3137 (2.2)190 (60.7)51 (16.3)65 (20.8) 
Other421 (2.4)23 (54.8)9 (21.4)9 (21.4) 

LOS and Resource Utilization

The median LOS for all patients was approximately 1 day (Table 2). The median number of albuterol treatments in the inpatient setting was 14 (IQR, 824). When albuterol treatments given in the ED were included, the median number of treatments increased to 38 (IQR, 2848). Approximately one‐half of patients required supplemental oxygen, one‐third received IV fluids, and one‐fifth received either IV or IM steroids (with all but 1.6% of the remaining patients receiving oral steroids). Less than 5% of the study population received magnesium sulfate, epinephrine, required intensive care unit (ICU) admission, or were readmitted for status asthmaticus within 30 days. Approximately 15% of patients received a chest radiograph. The median adjusted billed charge was approximately $7,000. There were no differences in any of these outcomes by BMI category (P>0.05).

Resource Utilization, Readmissions, Length of Stay, and Billed Charges for In‐Hospital Status Asthmaticus by Body Mass Index Category
 TotalBody Mass Index Category
UnderweightNormalOverweightObese
  • NOTE: Abbreviations: ICU, intensive care unit; IM, intramuscular; IQR, interquartile range; IV, intravenous. *All differences between body mass index categories were nonsignificant (P>0.05).

Total Patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7)
LOS, h, median (IQR)26 (1841)41 (19.560.5)26 (1841)26 (19.2540)31 (1942)
Inpatient albuterol equivalents, median (IQR)14(824)19 (9.528)14 (824)14 (8.522)16 (824)
Total albuterol equivalents, median (IQR)38 (2848)34 (2734)36 (2848)37 (2849.5)40 (3052)
Adjusted billed charges, $, median (IQR)6,999.5 (52929258)7,457 (56048536)6876 (52379390)7056 (54099061)7198 (53319306)
All readmits, n (%)44 (8.5)2 (11.1)29 (9.4)7 (8.0)6 (5.9)
Readmits within 30 days, n (%)11 (2.1)1 (5.6)7 (2.3)1 (1.1)2 (2.0)
ICU admissions, n (%)24 (4.6)0 (0)13 (4.2)7 (8.0)4 (3.9)
Chest radiograph, n (%)64 (12.4)5 (27.8)34 (11.0)12 (13.6)13 (12.7)
Oxygen, n (%)255 (49.2)11 (61.1)157 (50.6)42 (47.7)45 (44.1)
IV/IM steroid, n (%)93 (18.0)2 (11.1)53 (17.1)18 (20.5)20 (19.6)
Epinephrine, n (%)2 (0.4)0 (0)2 (0.6)0 (0)0 (0)
Magnesium, n (%)15 (2.9)0 (0)8 (2.6)3 (3.4)4 (3.9)
IV fluids, n (%)152 (29.3)4 (22.2)85 (27.4)31 (35.2)32 (31.4)

Multivariable Results

After adjusting for age, gender, race, ethnicity, and insurance, the decile of BMI percentile for age showed a small negative association with LOS. Specifically, for each decile increase for BMI percentile for age, LOS decreased by approximately 2%. BMI percentile for age was not associated with other measures of resource utilization including total albuterol use, adjusted billed charges, readmission, ICU care, receipt of supplemental oxygen or a chest radiograph, IV fluids, or other medications (IV/IM steroids, epinephrine, or magnesium sulfate).

DISCUSSION

Our study suggests that the decile of BMI percentile for age is inversely associated with LOS but did not have a clinically meaningful effect. Secondary measures, such as total albuterol needs and adjusted billed charges, did not show an association with BMI percentile for age. There were also no associations between BMI percentile for age and other resource utilization outcomes.

Our findings differ from previous studies examining in‐hospital status asthmaticus in children who are overweight or obese. In addition, the present study was able to adjust for therapies received prior to admission. Carroll et al. demonstrated an increased LOS of approximately 3 days for overweight or obese asthmatics admitted to the ICU with status asthmaticus as well as increased duration of supplemental oxygen, continuous albuterol, and intravenous steroids.[20] It is possible that differences in methodology (ie, weight‐for‐age percentile vs BMI percentile for age, inclusion of ED treatments), different thresholds for treatment of status asthmaticus outside the ICU, or differences in patient populations studied (ie, only ICU patients vs all in‐hospital patients) explain the difference between their findings and the present study. The present study's use of BMI percentile for age follows current recommendations for classifying a patient as obese or overweight.[23, 24, 25] However, the use of classifications other than BMI percentile for age would tend to bias toward the null hypothesis, whereas in Carroll's study children who were overweight or obese had increased resource utilization. Additionally, in the time frame between this publication and the current study, many hospitals worked to standardize asthma hospitalizations by creating weaning protocols for albuterol, thereby decreasing LOS for all asthmatics, which may also affect the differences in LOS between groups of obese and nonobese patients.[35]

Woolford et al. found approximately a one‐half‐day increase in LOS and $2,000 higher mean charges for patients admitted with status asthmaticus and a secondary diagnosis of obesity.[8, 9] Study location and differing methods for defining obesity may account for the discrepancy between Woolford's findings and our study. We examined children admitted to the inpatient floor of a tertiary care children's hospital compared to Woolford et al.'s examination of pediatric patients admitted to all hospitals via the Kids' Inpatient Database (Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality). That study also relied on the coding of obesity as an ICD‐9 diagnosis, rather than examining the BMI of all admitted patients. Previous research has demonstrated that relying on a coded diagnosis of obesity is not as sensitive as measurement.[26] By relying on ICD‐9 diagnosis coding, only patients with very high BMIs may be diagnosed with obesity during the admission and therefore only associations between very high BMI and status asthmaticus will be examined.

There are several limitations to our findings. First, our study was limited to a single, tertiary care children's hospital and may not be generalizable to other hospitals. Our hospital standardizes the treatment of inpatient status asthmatics by formation of a respiratory care plan, involving interval scoring of respiratory symptoms and automatic spacing of albuterol treatments. This likely minimizes physician‐to‐physician variation. Second, we included only those patients who were initially treated within the ED associated with the admitting hospital to minimize the effects of timing for treatments prior to admittance. This excluded those patients first cared for by their primary care physician or by an outlying ED. Therefore, our sample may be biased toward a study population less connected to a medical home and therefore possibly poorer asthma control. Third, to utilize the most accurate method to define obesity, we excluded approximately 5% of eligible patients because BMI was unavailable. This may have included children with more severe asthma symptoms, as a height measurement may have been deferred due to their higher acuity. Asthma severity or chronicity would be associated with our outcomes of interest. However, we were unable to collect reliable data on severity or chronicity. Finally, to measure the amount of total albuterol needed by a patient during the ED and inpatient admissions, albuterol treatments delivered by MDI, nebulizer, or continuously were converted into total albuterol. Although based upon total milligram dosing and studies comparing routes of albuterol administration,[34] the validity of this conversion is unknown.

CONCLUSION

Although BMI percentile for age is inversely associated with LOS for in‐hospital pediatric status asthmaticus, the impact of BMI on this outcome likely is not clinically meaningful. Future investigations should examine other elements of BMI and in‐hospital status asthmaticus, such as any associations between BMI and admission rates.

Acknowledgements

The authors offer their appreciation to their research assistant, Amy Lee, for her support and dedication to this project.

Disclosures

Internal funds from Children's Mercy Hospital and Clinics supported the conduct of this work. The authors report no conflicts of interest.

Pediatric hospitalizations for obesity‐related conditions have doubled in the last decade, mirroring the trend of higher levels of childhood obesity in the United States.[1, 2, 3] Recent studies have demonstrated worsened pediatric in‐hospital outcomes, including mortality and increased resource utilization, for children with obesity across a range of diagnoses.[4, 5, 6, 7, 8, 9, 10] Although the mechanisms driving the association between obesity and in‐hospital outcomes are not fully known, for asthma it is believed that adipocytes expressing inflammatory markers create a low level of systemic inflammation, thereby increasing the severity of allergic‐type illnesses and decreasing the response to anti‐inflammatory medications, such as steroids.[11, 12, 13, 14, 15, 16, 17, 18] The relationship of obesity and in‐hospital asthma outcomes is of particular interest because status asthmaticus is the most common reason for admission in children aged 3 to 12 years, accounting for approximately 150,000 admissions (7.4% of all hospitalizations for children and adolescents) and $835 million in hospital costs annually.[19]

Few prior studies have examined the association of obesity and asthma outcomes in the in‐hospital setting. The studies examining this association have found patients with obesity to have a longer hospital length of stay (LOS) and increased hospital costs.[8, 9, 20] Obesity has also been associated with increased respiratory treatments and supplemental oxygen requirements.[20] Associations between obesity and admission rates from the emergency department (ED) for pediatric asthma have been inconsistent.[21, 22] Most of these prior studies had several limitations in identifying patients with obesity, including using weight‐for‐age percentiles or International Classification of Diseases, Ninth Revision (ICD‐9) codes, rather than body mass index (BMI) percentile for age, the currently recommended method.[23, 24, 25] Methods other than BMI have the potential to either underestimate obesity (ie, ICD‐9 codes)[26] or to confound weight with adiposity (ie, weight‐for‐age percentiles),[27] thereby skewing the primary exposure of interest.

In the present study, we sought to examine associations between obesity and in‐hospital outcomes for pediatric status asthmaticus using the currently endorsed method for identifying obesity in children, BMI percentile for age.[23, 24, 25] The outcomes of interest included a broad range of in‐hospital measures, including resource utilization (medication and radiology use), readmission rates, billed charges, and LOS. We hypothesize that obesity, due to its proinflammatory state, would result in increased LOS, increased resource utilization, and an increased readmission rate for children admitted with status asthmaticus.

METHODS

Data Sources

Data for this retrospective cross‐sectional study were obtained from 2 sources. First, we queried the Pediatric Health Information System (PHIS) administrative database, which draws information from multiple children's hospitals to identify patients at our 2 institutions of interest who met study criteria. The PHIS database also was used to collect patient demographic data. PHIS is an administrative database operated by Children's Hospital Association (Overland Park, KS) containing clinical and billing data from 43 tertiary care, freestanding children's hospitals, including data on 41 ICD‐9 diagnoses, billed charges, and LOS. Based on the primary diagnosis, PHIS assigns each discharge to an All Patient Refined‐Diagnosis Related Group (APR‐DRG v.24) (3M Health information Systems, St. Paul, MN). APR‐DRGs allow similar diagnoses to be grouped together.[28, 29] PHIS also uses ICD‐9 codes to identify patients with a complex chronic condition (CCC).[30, 31] CCCs are those conditions that can be reasonably expected to last at least 12 months (unless death intervenes) and to involve either several different organ systems or one system severely enough to require specialty pediatric care and probably some period of hospitalization in a tertiary care center.[30, 31] PHIS data quality is ensured through a collaborative effort of the participating hospitals, the Children's Hospital Association, and Truven Healthcare.

Second, standardized chart reviews were then performed to collect clinical data not found in PHIS: BMI, LOS in hours, and medications administered, including total number of albuterol treatments administered during both the admission and the associated preceding ED visit.

Study Setting and Participants

All admissions examined in this study were at Children's Mercy Hospitals. Children's Mercy Hospitals includes 2 separate hospitals: 1 hospital is a 354‐bed academic, tertiary care freestanding children's hospital located in Kansas City, Missouri; a second, smaller, 50‐bed freestanding hospital is located in Overland Park, Kansas. Both hospitals have pediatric emergency departments. Inclusion criteria included patients aged 5 to 17 years discharged for status asthmaticus (APR‐DRG 141) at Children's Mercy Hospital from October 1, 2011 to September 30, 2012, with a recorded BMI during the admission or within 30 days of the admission. Patients between the ages of 2 and 5 years old were not included because of the incidence of viral‐induced wheezing in this age group and therefore possible miscoding of the asthma diagnosis. Exclusion criteria included a concurrent diagnosis of a CCC or bacterial pneumonia because these conditions could alter LOS, resource utilization, and readmission rates independent of the subject's status asthmaticus. In addition, to account for differences in the amount of treatment given in the pre‐inpatient setting, patients not initially treated through the hospital's ED were excluded. For patients with multiple admissions during the study period for the same diagnosis, only the index admission was examined. The institutional review board at Children's Mercy Hospital approved this study with waiver of informed consent.

Study Definitions

BMI percentile for age was used as both a continuous and categorical predictor variable. As a categorical variable it was divided into 4 categories: underweight (BMI <5%), normal weight (BMI 5%84%), overweight (BMI 85%94%), and obese (BMI 95%).[23] Race was categorized non‐Hispanic white, non‐Hispanic black, and other. Other included Asian, Pacific Islander, American Indian, and other. Ethnicity was categorized as Hispanic and non‐Hispanic. Insurance categories included private (commercial or TRICARE), public (Medicaid and Title V), and other (uninsured, self‐pay, and other). Adjusted billed charges were calculated for each hospitalization. Adjusted billed charges are the billed charges adjusted by the US Centers of Medicare and Medicaid Services' price/wage index for the study site's location.[32, 33]

To compare albuterol of different delivery methods, albuterol equivalents were calculated. Based upon prior research demonstrating equal efficacy between albuterol administered by nebulizer and metered‐dose inhaler (MDI),[34] every 2.5 mg of albuterol administered by nebulizer was treated as equivalent to 2 sprays of albuterol (90 g/spray) administered by MDI. Therefore, albuterol 2.5 mg nebulized and 2 sprays of albuterol (90 g/spray) were each defined as 1 albuterol equivalent. To compare continuous administration of nebulized albuterol with intermittent administration of albuterol, the total milligrams of continuously nebulized albuterol were examined. Per protocol at the study site, 10 mg per hour of continuous albuterol are administered for patients 5 years and younger and, for children 6 years and older, 15 mg per hour of continuous albuterol are administered. Based upon milligrams of albuterol nebulized, 5‐year‐old subjects receiving an hour of continuous albuterol would equal 4 albuterol equivalents (or 4 treatments of nebulized albuterol 2.5 mg/treatment or 4 treatments of albuterol 90 g/spray 2 sprays/treatment); for patients 6 years and older, an hour of continuous albuterol would equal 6 albuterol equivalents (or 6 treatments of nebulized albuterol 2.5 mg/treatment or 6 treatments of albuterol 90 g/spray 2 sprays/treatment). The variable total albuterol was then created to include albuterol equivalents delivered by metered dose inhaler and as both single and continuous nebulized treatments.

Main Exposure

The main exposure of interest was BMI percentile for age.

Outcome Measures

The main outcome measure was inpatient LOS measured in hours. Secondary outcome measures included the total albuterol (in the inpatient setting as well as combined inpatient and ED settings) and the administration of intravenous IV fluids and intramuscular (IM) or IV systemic steroids. Other secondary measures included readmission for status asthmaticus during the study period, adjusted billed charges, and inpatient chest radiograph utilization.

Statistical Analyses

We summarized categorical variables with frequencies and percentages, and used [2] test across BMI categories. The non‐normal distribution of continuous dependent variables (LOS, number of albuterol treatments, billed charges) were summarized with medians and interquartile ranges (IQRs). Kruskal‐Wallis test was used to examine outcomes across BMI categories. For regression models, BMI percentile for age was divided into deciles and treated as a continuous predictor. Factors used in the regression models included age, gender, race, ethnicity, and insurance. Total albuterol received in the ED was also included in the model to adjust for differences in the amount of treatment received prior to admission. Incidence rate ratios were created using Poisson regression for continuous outcomes (LOS, billed charges, and number of albuterol equivalent treatments administered), and odds ratios were created using logistic regression for dichotomous outcomes. All statistical analyses were performed using IBM SPSS Statistics version 20 (IBM, Armonk, NY), and P values <0.05 were considered statistically significant.

RESULTS

Patient Characteristics

Of 788 patients admitted for status asthmaticus during the study period, 518 (65.7%) met inclusion criteria; 42 (5.3%) did not meet inclusion criteria due to lack of a documented BMI (Table 1). Most patients were normal weight (59.7%). Approximately one‐third (36.7%) were either overweight or obese. The median age was 8 years, with patients with obesity being significantly older than underweight patients (9 vs 7.5 years, P<0.001). The majority of patients were black/African American (56.9%) and non‐Hispanic (88.6%). The percentage of patients who were obese was higher in patients of other race (29.3%) than whites (20.2%) or blacks (16.3%) (P<0.05). Patients of Hispanic ethnicity had a higher rate of obesity compared to non‐Hispanic patients (37.3% vs 17.4%, P<0.01). There were no differences in BMI categories for insurance.

Patient Characteristics by Body Mass Index Category
Patient CharacteristicsTotalCategory of Body Mass Index Percentile for Age
UnderweightNormalOverweightObeseP*
  • NOTE: Abbreviations: IQR, interquartile range. *Categorical variables were compared by 2 test, and continuous variables were compared by Kruskall‐Wallis test.

Total patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7) 
Age, y, median (IQR)8 (611)7.5 (5.89)8 (610)8 (610)9 (712)<0.001
Gender, n (%)      
Male30912 (3.9)184 (59.5)46 (14.9)67 (21.7)0.27
Female2096 (2.9)126 (60.3)42 (20.1)35 (16.7) 
Race, n (%)      
Non‐Hispanic white1248 (6.5)76 (61.3)15 (12.1)25 (20.2)0.021
Non‐Hispanic black2957 (2.4)182 (61.7)58 (19.7)48 (16.3) 
Other993 (3.0)52 (52.5)15 (15.2)29 (29.3) 
Ethnicity, n (%)      
Hispanic591 (1.7)25 (42.4)11 (18.6)22 (37.3)0.002
Non‐Hispanic45917 (3.7)285 (62.1)77 (16.8)80 (17.4) 
Insurance, n (%)      
Private16310 (6.1)97 (59.5)28 (17.2)28 (17.2)0.48
Public3137 (2.2)190 (60.7)51 (16.3)65 (20.8) 
Other421 (2.4)23 (54.8)9 (21.4)9 (21.4) 

LOS and Resource Utilization

The median LOS for all patients was approximately 1 day (Table 2). The median number of albuterol treatments in the inpatient setting was 14 (IQR, 824). When albuterol treatments given in the ED were included, the median number of treatments increased to 38 (IQR, 2848). Approximately one‐half of patients required supplemental oxygen, one‐third received IV fluids, and one‐fifth received either IV or IM steroids (with all but 1.6% of the remaining patients receiving oral steroids). Less than 5% of the study population received magnesium sulfate, epinephrine, required intensive care unit (ICU) admission, or were readmitted for status asthmaticus within 30 days. Approximately 15% of patients received a chest radiograph. The median adjusted billed charge was approximately $7,000. There were no differences in any of these outcomes by BMI category (P>0.05).

Resource Utilization, Readmissions, Length of Stay, and Billed Charges for In‐Hospital Status Asthmaticus by Body Mass Index Category
 TotalBody Mass Index Category
UnderweightNormalOverweightObese
  • NOTE: Abbreviations: ICU, intensive care unit; IM, intramuscular; IQR, interquartile range; IV, intravenous. *All differences between body mass index categories were nonsignificant (P>0.05).

Total Patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7)
LOS, h, median (IQR)26 (1841)41 (19.560.5)26 (1841)26 (19.2540)31 (1942)
Inpatient albuterol equivalents, median (IQR)14(824)19 (9.528)14 (824)14 (8.522)16 (824)
Total albuterol equivalents, median (IQR)38 (2848)34 (2734)36 (2848)37 (2849.5)40 (3052)
Adjusted billed charges, $, median (IQR)6,999.5 (52929258)7,457 (56048536)6876 (52379390)7056 (54099061)7198 (53319306)
All readmits, n (%)44 (8.5)2 (11.1)29 (9.4)7 (8.0)6 (5.9)
Readmits within 30 days, n (%)11 (2.1)1 (5.6)7 (2.3)1 (1.1)2 (2.0)
ICU admissions, n (%)24 (4.6)0 (0)13 (4.2)7 (8.0)4 (3.9)
Chest radiograph, n (%)64 (12.4)5 (27.8)34 (11.0)12 (13.6)13 (12.7)
Oxygen, n (%)255 (49.2)11 (61.1)157 (50.6)42 (47.7)45 (44.1)
IV/IM steroid, n (%)93 (18.0)2 (11.1)53 (17.1)18 (20.5)20 (19.6)
Epinephrine, n (%)2 (0.4)0 (0)2 (0.6)0 (0)0 (0)
Magnesium, n (%)15 (2.9)0 (0)8 (2.6)3 (3.4)4 (3.9)
IV fluids, n (%)152 (29.3)4 (22.2)85 (27.4)31 (35.2)32 (31.4)

Multivariable Results

After adjusting for age, gender, race, ethnicity, and insurance, the decile of BMI percentile for age showed a small negative association with LOS. Specifically, for each decile increase for BMI percentile for age, LOS decreased by approximately 2%. BMI percentile for age was not associated with other measures of resource utilization including total albuterol use, adjusted billed charges, readmission, ICU care, receipt of supplemental oxygen or a chest radiograph, IV fluids, or other medications (IV/IM steroids, epinephrine, or magnesium sulfate).

DISCUSSION

Our study suggests that the decile of BMI percentile for age is inversely associated with LOS but did not have a clinically meaningful effect. Secondary measures, such as total albuterol needs and adjusted billed charges, did not show an association with BMI percentile for age. There were also no associations between BMI percentile for age and other resource utilization outcomes.

Our findings differ from previous studies examining in‐hospital status asthmaticus in children who are overweight or obese. In addition, the present study was able to adjust for therapies received prior to admission. Carroll et al. demonstrated an increased LOS of approximately 3 days for overweight or obese asthmatics admitted to the ICU with status asthmaticus as well as increased duration of supplemental oxygen, continuous albuterol, and intravenous steroids.[20] It is possible that differences in methodology (ie, weight‐for‐age percentile vs BMI percentile for age, inclusion of ED treatments), different thresholds for treatment of status asthmaticus outside the ICU, or differences in patient populations studied (ie, only ICU patients vs all in‐hospital patients) explain the difference between their findings and the present study. The present study's use of BMI percentile for age follows current recommendations for classifying a patient as obese or overweight.[23, 24, 25] However, the use of classifications other than BMI percentile for age would tend to bias toward the null hypothesis, whereas in Carroll's study children who were overweight or obese had increased resource utilization. Additionally, in the time frame between this publication and the current study, many hospitals worked to standardize asthma hospitalizations by creating weaning protocols for albuterol, thereby decreasing LOS for all asthmatics, which may also affect the differences in LOS between groups of obese and nonobese patients.[35]

Woolford et al. found approximately a one‐half‐day increase in LOS and $2,000 higher mean charges for patients admitted with status asthmaticus and a secondary diagnosis of obesity.[8, 9] Study location and differing methods for defining obesity may account for the discrepancy between Woolford's findings and our study. We examined children admitted to the inpatient floor of a tertiary care children's hospital compared to Woolford et al.'s examination of pediatric patients admitted to all hospitals via the Kids' Inpatient Database (Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality). That study also relied on the coding of obesity as an ICD‐9 diagnosis, rather than examining the BMI of all admitted patients. Previous research has demonstrated that relying on a coded diagnosis of obesity is not as sensitive as measurement.[26] By relying on ICD‐9 diagnosis coding, only patients with very high BMIs may be diagnosed with obesity during the admission and therefore only associations between very high BMI and status asthmaticus will be examined.

There are several limitations to our findings. First, our study was limited to a single, tertiary care children's hospital and may not be generalizable to other hospitals. Our hospital standardizes the treatment of inpatient status asthmatics by formation of a respiratory care plan, involving interval scoring of respiratory symptoms and automatic spacing of albuterol treatments. This likely minimizes physician‐to‐physician variation. Second, we included only those patients who were initially treated within the ED associated with the admitting hospital to minimize the effects of timing for treatments prior to admittance. This excluded those patients first cared for by their primary care physician or by an outlying ED. Therefore, our sample may be biased toward a study population less connected to a medical home and therefore possibly poorer asthma control. Third, to utilize the most accurate method to define obesity, we excluded approximately 5% of eligible patients because BMI was unavailable. This may have included children with more severe asthma symptoms, as a height measurement may have been deferred due to their higher acuity. Asthma severity or chronicity would be associated with our outcomes of interest. However, we were unable to collect reliable data on severity or chronicity. Finally, to measure the amount of total albuterol needed by a patient during the ED and inpatient admissions, albuterol treatments delivered by MDI, nebulizer, or continuously were converted into total albuterol. Although based upon total milligram dosing and studies comparing routes of albuterol administration,[34] the validity of this conversion is unknown.

CONCLUSION

Although BMI percentile for age is inversely associated with LOS for in‐hospital pediatric status asthmaticus, the impact of BMI on this outcome likely is not clinically meaningful. Future investigations should examine other elements of BMI and in‐hospital status asthmaticus, such as any associations between BMI and admission rates.

Acknowledgements

The authors offer their appreciation to their research assistant, Amy Lee, for her support and dedication to this project.

Disclosures

Internal funds from Children's Mercy Hospital and Clinics supported the conduct of this work. The authors report no conflicts of interest.

References
  1. Cunningham SA, Kramer MR, Narayan KMV. Incidence of childhood obesity in the United States. N Engl J Med. 2014;370(5):403411.
  2. Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA Pediatr. 2014;168(6):561566.
  3. Trasande L, Liu Y, Fryer G, Weitzman M. Effects of childhood obesity on hospital care and costs, 1999–2005. Health Affairs. 2009;28(4):w751w760.
  4. Bechard LJ, Rothpletz‐Puglia P, Touger‐Decker R, Duggan C, Mehta NM. Influence of obesity on clinical outcomes in hospitalized children: a systematic review. JAMA Pediatr. 2013;167(5):476482.
  5. Davies DA, Yanchar NL. Appendicitis in the obese child. J Pediatr Surg. 2007;42(5):857861.
  6. Patel L, Cowden JD, Dowd D, Hampl S, Felich N. Obesity: influence on length of hospital stay for the pediatric burn patient. J Burn Care Res. 2010;31(2):251256.
  7. Brown CVR, Neville AL, Salim A, Rhee P, Cologne K, Demetriades D. The impact of obesity on severely injured children and adolescents. J Pediatr Surg. 2006;41(1):8891.
  8. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Incremental hospital charges associated with obesity as a secondary diagnosis in children. Obesity (Silver Spring). 2007;15(7):18951901.
  9. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Persistent gap of incremental charges for obesity as a secondary diagnosis in common pediatric hospitalizations. J Hosp Med. 2009;4(3):149156.
  10. Hampl SE, Carroll CA, Simon SD, Sharma V. Resource utilization and expenditures for overweight and obese children. Arch Pediatr Adolesc Med. 2007;161(1):1114.
  11. Forno E, Lescher R, Strunk R, Weiss S, Fuhlbrigge A, Celedon JC. Decreased response to inhaled steroids in overweight and obese asthmatic children. J Allergy Clin Immunol. 2011;127(3):741749.
  12. Sutherland ER, Goleva E, Strand M, Beuther DA, Leung DYM. Body mass and glucocorticoid response in asthma. Am J Respir Crit Care Med. 2008;178(7):682687.
  13. Sutherland ER, Lehman EB, Teodorescu M, Wechsler ME; National Heart, Lung, and Blood Institute's Asthma Clinical Research Network. Body mass index and phenotype in subjects with mild‐to‐moderate persistent asthma. J Allergy Clin Immunol. 2009;123(6):13281334.e1.
  14. Stream AR, Sutherland ER. Obesity and asthma disease phenotypes. Curr Opin Allergy Clin Immunol. 2012;12(1):7681.
  15. Sin DD, Sutherland ER. Obesity and the lung: 4. Obesity and asthma. Thorax. 2008;63(11):10181023.
  16. Camargo CA, Boulet L‐P, Sutherland ER, et al. Body mass index and response to asthma therapy: fluticasone propionate/salmeterol versus montelukast. J Asthma. 2010;47(1):7682.
  17. Dixon AE, Shade DM, Cohen RI, et al. Effect of obesity on clinical presentation and response to treatment in asthma. J Asthma. 2006;43(7):553558.
  18. Suglia SF, Chambers EC, Rosario A, Duarte CS. Asthma and obesity in three‐year‐old urban children: role of sex and home environment. J Pediatr. 2011;159(1):1420.
  19. Owens PL, Thompson J, Elixhauser A, Ryan K. Care of Children and Adolescents in U.S. Hospitals. Rockville, MD: Agency for Healthcare Research and Quality; 2003. Available at: http://archive.ahrq.gov/data/hcup/factbk4/factbk4.pdf. Accessed February 12, 2014.
  20. Carroll CL, Bhandari A, Zucker AR, Schramm CM. Childhood obesity increases duration of therapy during severe asthma exacerbations. Pediatr Crit Care Med. 2006;7(6):527531.
  21. Carroll CL, Stoltz P, Raykov N, Smith SR, Zucker AR. Childhood overweight increases hospital admission rates for asthma. Pediatr. 2007;120(4):734740.
  22. Ginde AA, Santillan AA, Clark S, Camargo CA. Body mass index and acute asthma severity among children presenting to the emergency department. Pediatr Allergy Immunol. 2009;21(3):480488.
  23. Centers for Disease Control and Prevention. Basics about childhood obesity. Available at: http://www.cdc.gov/obesity/childhood/basics.html. Accessed February 12, 2014.
  24. Whitlock EP. Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. Pediatrics. 2005;116(1):e125e144.
  25. Barlow SE; Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164S192.
  26. Kuhle S, Kirk SFL, Ohinmaa A, Veugelers PJ. Comparison of ICD code‐based diagnosis of obesity with measured obesity in children and the implications for health care cost estimates. BMC Med Res Methodol. 2011;11(1):173.
  27. Krebs NF, Jacobson MS; American Academy of Pediatrics Committee on Nutrition. Prevention of pediatric overweight and obesity. Pediatrics. 2003;112(2):424430.
  28. Hughes J. Development of the 3M all patient‐refined diagnosis‐related groups (APR DRGs). Available at: http//www.ahrq.gov/legacy/qual/mortality/Hughes3.htm. Accessed March 1, 2014.
  29. Hughes J. 3M Health Information Systems (HIS) APR‐DRG classification software: overview. Available at: http://www.ahrq.gov/legacy/qual/mortality/Hughessumm.htm. Accessed March 1, 2014.
  30. Feudtner C, Feinstein JA, Satchell M, Zhao H, Kang TI. Shifting place of death among children with complex chronic conditions in the United States, 1989–2003. JAMA. 2007;297(24):27252732.
  31. Feudtner C, Christakis DA, Connell FA. Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997. Pediatrics. 2000;106(1 pt 2):205209.
  32. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256263.
  33. Weiss AK, Hall M, Lee GE, Kronman MP, Sheffler‐Collins S, Shah SS. Adjunct corticosteroids in children hospitalized with community‐acquired pneumonia. Pediatrics. 2011;127(2):e255e263.
  34. Cates CJ, Welsh EJ, Rowe BH. Holding chambers (spacers) versus nebulisers for beta‐agonist treatment of acute asthma. Cochrane Database Syst Rev. 2013;9:CD000052.
  35. Johnson KB, Blaisdell CJ, Walker A, Eggleston P. Effectiveness of a clinical pathway for inpatient asthma management. Pediatrics. 2000;106(5):10061012.
References
  1. Cunningham SA, Kramer MR, Narayan KMV. Incidence of childhood obesity in the United States. N Engl J Med. 2014;370(5):403411.
  2. Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA Pediatr. 2014;168(6):561566.
  3. Trasande L, Liu Y, Fryer G, Weitzman M. Effects of childhood obesity on hospital care and costs, 1999–2005. Health Affairs. 2009;28(4):w751w760.
  4. Bechard LJ, Rothpletz‐Puglia P, Touger‐Decker R, Duggan C, Mehta NM. Influence of obesity on clinical outcomes in hospitalized children: a systematic review. JAMA Pediatr. 2013;167(5):476482.
  5. Davies DA, Yanchar NL. Appendicitis in the obese child. J Pediatr Surg. 2007;42(5):857861.
  6. Patel L, Cowden JD, Dowd D, Hampl S, Felich N. Obesity: influence on length of hospital stay for the pediatric burn patient. J Burn Care Res. 2010;31(2):251256.
  7. Brown CVR, Neville AL, Salim A, Rhee P, Cologne K, Demetriades D. The impact of obesity on severely injured children and adolescents. J Pediatr Surg. 2006;41(1):8891.
  8. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Incremental hospital charges associated with obesity as a secondary diagnosis in children. Obesity (Silver Spring). 2007;15(7):18951901.
  9. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Persistent gap of incremental charges for obesity as a secondary diagnosis in common pediatric hospitalizations. J Hosp Med. 2009;4(3):149156.
  10. Hampl SE, Carroll CA, Simon SD, Sharma V. Resource utilization and expenditures for overweight and obese children. Arch Pediatr Adolesc Med. 2007;161(1):1114.
  11. Forno E, Lescher R, Strunk R, Weiss S, Fuhlbrigge A, Celedon JC. Decreased response to inhaled steroids in overweight and obese asthmatic children. J Allergy Clin Immunol. 2011;127(3):741749.
  12. Sutherland ER, Goleva E, Strand M, Beuther DA, Leung DYM. Body mass and glucocorticoid response in asthma. Am J Respir Crit Care Med. 2008;178(7):682687.
  13. Sutherland ER, Lehman EB, Teodorescu M, Wechsler ME; National Heart, Lung, and Blood Institute's Asthma Clinical Research Network. Body mass index and phenotype in subjects with mild‐to‐moderate persistent asthma. J Allergy Clin Immunol. 2009;123(6):13281334.e1.
  14. Stream AR, Sutherland ER. Obesity and asthma disease phenotypes. Curr Opin Allergy Clin Immunol. 2012;12(1):7681.
  15. Sin DD, Sutherland ER. Obesity and the lung: 4. Obesity and asthma. Thorax. 2008;63(11):10181023.
  16. Camargo CA, Boulet L‐P, Sutherland ER, et al. Body mass index and response to asthma therapy: fluticasone propionate/salmeterol versus montelukast. J Asthma. 2010;47(1):7682.
  17. Dixon AE, Shade DM, Cohen RI, et al. Effect of obesity on clinical presentation and response to treatment in asthma. J Asthma. 2006;43(7):553558.
  18. Suglia SF, Chambers EC, Rosario A, Duarte CS. Asthma and obesity in three‐year‐old urban children: role of sex and home environment. J Pediatr. 2011;159(1):1420.
  19. Owens PL, Thompson J, Elixhauser A, Ryan K. Care of Children and Adolescents in U.S. Hospitals. Rockville, MD: Agency for Healthcare Research and Quality; 2003. Available at: http://archive.ahrq.gov/data/hcup/factbk4/factbk4.pdf. Accessed February 12, 2014.
  20. Carroll CL, Bhandari A, Zucker AR, Schramm CM. Childhood obesity increases duration of therapy during severe asthma exacerbations. Pediatr Crit Care Med. 2006;7(6):527531.
  21. Carroll CL, Stoltz P, Raykov N, Smith SR, Zucker AR. Childhood overweight increases hospital admission rates for asthma. Pediatr. 2007;120(4):734740.
  22. Ginde AA, Santillan AA, Clark S, Camargo CA. Body mass index and acute asthma severity among children presenting to the emergency department. Pediatr Allergy Immunol. 2009;21(3):480488.
  23. Centers for Disease Control and Prevention. Basics about childhood obesity. Available at: http://www.cdc.gov/obesity/childhood/basics.html. Accessed February 12, 2014.
  24. Whitlock EP. Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. Pediatrics. 2005;116(1):e125e144.
  25. Barlow SE; Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164S192.
  26. Kuhle S, Kirk SFL, Ohinmaa A, Veugelers PJ. Comparison of ICD code‐based diagnosis of obesity with measured obesity in children and the implications for health care cost estimates. BMC Med Res Methodol. 2011;11(1):173.
  27. Krebs NF, Jacobson MS; American Academy of Pediatrics Committee on Nutrition. Prevention of pediatric overweight and obesity. Pediatrics. 2003;112(2):424430.
  28. Hughes J. Development of the 3M all patient‐refined diagnosis‐related groups (APR DRGs). Available at: http//www.ahrq.gov/legacy/qual/mortality/Hughes3.htm. Accessed March 1, 2014.
  29. Hughes J. 3M Health Information Systems (HIS) APR‐DRG classification software: overview. Available at: http://www.ahrq.gov/legacy/qual/mortality/Hughessumm.htm. Accessed March 1, 2014.
  30. Feudtner C, Feinstein JA, Satchell M, Zhao H, Kang TI. Shifting place of death among children with complex chronic conditions in the United States, 1989–2003. JAMA. 2007;297(24):27252732.
  31. Feudtner C, Christakis DA, Connell FA. Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997. Pediatrics. 2000;106(1 pt 2):205209.
  32. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256263.
  33. Weiss AK, Hall M, Lee GE, Kronman MP, Sheffler‐Collins S, Shah SS. Adjunct corticosteroids in children hospitalized with community‐acquired pneumonia. Pediatrics. 2011;127(2):e255e263.
  34. Cates CJ, Welsh EJ, Rowe BH. Holding chambers (spacers) versus nebulisers for beta‐agonist treatment of acute asthma. Cochrane Database Syst Rev. 2013;9:CD000052.
  35. Johnson KB, Blaisdell CJ, Walker A, Eggleston P. Effectiveness of a clinical pathway for inpatient asthma management. Pediatrics. 2000;106(5):10061012.
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Address for correspondence and reprint requests: Jessica Bettenhausen, MD, Department of Pediatrics, Children's Mercy Hospitals and Clinics, 2401 Gillham Road, Kansas City, MO 64108; Telephone: 816‐802‐1493; Fax: 816‐559‐9530; E‐mail: [email protected]
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Statins don’t cut fracture risk

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Statins don’t cut fracture risk

Daily rosuvastatin did not decrease fracture risk in a large international clinical trial involving older men and women who had elevated CRP levels, according to a report published online Dec. 1 in JAMA Internal Medicine.

Statins are thought to stimulate bone formation and increase bone mineral density, suggesting that they may exert clinical benefits beyond cardiovascular disease (CVD) prevention. Several observational studies have reported that statin users show a decreased risk of osteoporotic fractures, compared with nonusers. To examine this possible benefit, the JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin) trial enrolled 17,802 men older than 50 years and women older than 60 years to receive either rosuvastatin or matching placebo and be followed for up to 5 years (median follow-up, 2 years) for both CVD and fracture events. The study was conducted at 1,315 medical centers in 26 countries, said Dr. Jessica M. Peña of the division of cardiology, Montefiore Medical Center, New York, and her associates.

Dr. Jessica Pena

A total of 431 participants sustained fractures: 221 in the rosuvastatin group and 210 in the placebo group, a nonsignificant difference. The corresponding rate of fracture was 1.20 per 100 person-years with the statin and 1.14 per 100 person-years with placebo, also a nonsignificant difference. The lack of protection associated with the active drug was consistent between men and women, across all fracture sites, and regardless of the participants’ fracture history. It also persisted through several sensitivity analyses, the investigators said (JAMA Intern. Med. 2014 Dec. 1 [doi:10.1001/jamainternmed.2014.6388]).

“Our study does not support the use of statins in doses used for cardiovascular disease prevention to reduce the risk of fracture,” the researchers noted.

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Daily rosuvastatin did not decrease fracture risk in a large international clinical trial involving older men and women who had elevated CRP levels, according to a report published online Dec. 1 in JAMA Internal Medicine.

Statins are thought to stimulate bone formation and increase bone mineral density, suggesting that they may exert clinical benefits beyond cardiovascular disease (CVD) prevention. Several observational studies have reported that statin users show a decreased risk of osteoporotic fractures, compared with nonusers. To examine this possible benefit, the JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin) trial enrolled 17,802 men older than 50 years and women older than 60 years to receive either rosuvastatin or matching placebo and be followed for up to 5 years (median follow-up, 2 years) for both CVD and fracture events. The study was conducted at 1,315 medical centers in 26 countries, said Dr. Jessica M. Peña of the division of cardiology, Montefiore Medical Center, New York, and her associates.

Dr. Jessica Pena

A total of 431 participants sustained fractures: 221 in the rosuvastatin group and 210 in the placebo group, a nonsignificant difference. The corresponding rate of fracture was 1.20 per 100 person-years with the statin and 1.14 per 100 person-years with placebo, also a nonsignificant difference. The lack of protection associated with the active drug was consistent between men and women, across all fracture sites, and regardless of the participants’ fracture history. It also persisted through several sensitivity analyses, the investigators said (JAMA Intern. Med. 2014 Dec. 1 [doi:10.1001/jamainternmed.2014.6388]).

“Our study does not support the use of statins in doses used for cardiovascular disease prevention to reduce the risk of fracture,” the researchers noted.

Daily rosuvastatin did not decrease fracture risk in a large international clinical trial involving older men and women who had elevated CRP levels, according to a report published online Dec. 1 in JAMA Internal Medicine.

Statins are thought to stimulate bone formation and increase bone mineral density, suggesting that they may exert clinical benefits beyond cardiovascular disease (CVD) prevention. Several observational studies have reported that statin users show a decreased risk of osteoporotic fractures, compared with nonusers. To examine this possible benefit, the JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin) trial enrolled 17,802 men older than 50 years and women older than 60 years to receive either rosuvastatin or matching placebo and be followed for up to 5 years (median follow-up, 2 years) for both CVD and fracture events. The study was conducted at 1,315 medical centers in 26 countries, said Dr. Jessica M. Peña of the division of cardiology, Montefiore Medical Center, New York, and her associates.

Dr. Jessica Pena

A total of 431 participants sustained fractures: 221 in the rosuvastatin group and 210 in the placebo group, a nonsignificant difference. The corresponding rate of fracture was 1.20 per 100 person-years with the statin and 1.14 per 100 person-years with placebo, also a nonsignificant difference. The lack of protection associated with the active drug was consistent between men and women, across all fracture sites, and regardless of the participants’ fracture history. It also persisted through several sensitivity analyses, the investigators said (JAMA Intern. Med. 2014 Dec. 1 [doi:10.1001/jamainternmed.2014.6388]).

“Our study does not support the use of statins in doses used for cardiovascular disease prevention to reduce the risk of fracture,” the researchers noted.

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Key clinical point: Rosuvastatin didn’t lower the risk of bone fracture, compared with placebo.

Major finding: 221 participants given rosuvastatin and 210 given placebo sustained fractures, a nonsignificant difference.

Data source: An international randomized double-blind trial in which 17,802 older adults with elevated CRP received either rosuvastatin or placebo and were followed for a median of 2 years.

Disclosures: The JUPITER trial was supported by AstraZeneca, and Dr. Pena was supported by the National Heart, Lung, and Blood Institute. She reported having no financial disclosures; her associates reported numerous ties to industry sources.

It takes work-arounds to make EHRs “work”

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It takes work-arounds to make EHRs “work”

Dr. Hickner’s editorial “EHRs: Something’s gotta give” (J Fam Pract. 2014;63:558) prompted me to reflect on the elements of electronic health records (EHRs) that cannot change and the ones that can.

The EHR system I use allows the EHR to serve as a 
quality recorder, and it appears 
this is the most important part,
 because the reminders of what
 needs to be documented come first and are color-coded. From a reimbursement point of view, what is important is not the narrative, but the expanded “elements” that make it a billing document. I believe this will not change.

What can change is how the note information is organized, and I think the organization should be different for specific roles. At intake, a medical assistant can review allergies, medication lists, and preventive services; update family history; and take vital signs and history of present illness (HPI). As the physician, I want the note to show the information in the order that I process it during the visit: 1) allergies/medication list, 2) concerns/complaints with brief documentation, 3) vitals, 4) physical, 5) assessment, and 6) plan.

After the note is signed off on, I want a different format for review purposes: 1) assessment/plan (because this is what I look at first for follow-up), 2) HPI/review of systems, 3) physical, 4) allergies, 5) medication list, 6) past medical history, and 7) quality reminders (if they show up at all after the visit is complete).

Is it asking too much for a programmer to make the EHR organize information in this manner?

Edward Friedler, MD
Annandale, Va


I still dictate my notes and they very much tell a story that an EHR cannot. I have been audited repeatedly and I always have all the bullet points and essentials that the insurance company wants, but this information is in a format that everyone—including patients—can read and appreciate.

The move to APSO (assessment, plan, subjective, objective) from SOAP (subjective, objective, assessment, plan) is an example of the tail wagging the dog. Rather than fix the note so the time-honored SOAP format works, we acknowledge that no one actually reads the long template notes and they want to get to the bottom line (ie, the assessment and plan).

My dream is to return to the days when we only listed the positive findings, the assumption being that a competent physician did the exam that was required and it’s unnecessary to state that the examined anatomy was normal. Unfortunately, so much of what we must do is driven by lawyers and insurance companies—not by doctors.

David M. Brill, DO
Rocky River, Ohio


I now take photos of all of the ludicrous choices our EHR tosses at me, such as “laceration of third eyelid” or “injury, crushed by falling aircraft due to terrorist.” Most of my EHR entries now say, “See scanned handwritten note for accuracy.”

The issue of EHRs needs to be kept on the front burner. It is destroying doctor/patient relationships and quality diagnostic care while hiding the important findings in the garbage.

Jay Hammett, MD
Knoxville, Tenn


I’m in a group practice of 10 family physicians and in a typical workday, each of us sees 23 to 25 patients, answers e-mails/phone calls, and reviews labs/studies, which leaves no time for anything else. There’s a constant struggle to stay on top of the quality of the notes. I have preserved the quality of my own notes by free typing. I free type a differential next to my assessment or on the first line of the plan. I don’t use templates; they slow me down too much.

Kelly Luba, DO
Phoenix, Ariz


I was a civil service physician working for the Department of the Navy in 2005 when EHRs were thrust upon me. The system was not particularly user-friendly. Free texting was highly discouraged and it was strongly preferred that we used structured text embedded in the program.

I couldn’t use the program as envisioned, so I found a work-around. I would paste the 4 sections of the SOAP note directly into the appropriate free text sections of the electronic record. My assessment included the correct diagnosis, and I would pick a general EHR diagnosis from the dropdown list. Visually, my records did not look any different from those of other health care providers who used structured text.

I used this method until my civil service retirement in 2014. All of my record peer reviews were outstanding, and I was told that my records were easy to understand. I finally let on to all that I never used structured text and that all of my records were really written the old-fashioned way. I still used a clipboard during the patient visit, and completed all records after the patient left.

 

 

David F. Scaccia, DO, MPH
Kittery, Maine

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Dr. Hickner’s editorial “EHRs: Something’s gotta give” (J Fam Pract. 2014;63:558) prompted me to reflect on the elements of electronic health records (EHRs) that cannot change and the ones that can.

The EHR system I use allows the EHR to serve as a 
quality recorder, and it appears 
this is the most important part,
 because the reminders of what
 needs to be documented come first and are color-coded. From a reimbursement point of view, what is important is not the narrative, but the expanded “elements” that make it a billing document. I believe this will not change.

What can change is how the note information is organized, and I think the organization should be different for specific roles. At intake, a medical assistant can review allergies, medication lists, and preventive services; update family history; and take vital signs and history of present illness (HPI). As the physician, I want the note to show the information in the order that I process it during the visit: 1) allergies/medication list, 2) concerns/complaints with brief documentation, 3) vitals, 4) physical, 5) assessment, and 6) plan.

After the note is signed off on, I want a different format for review purposes: 1) assessment/plan (because this is what I look at first for follow-up), 2) HPI/review of systems, 3) physical, 4) allergies, 5) medication list, 6) past medical history, and 7) quality reminders (if they show up at all after the visit is complete).

Is it asking too much for a programmer to make the EHR organize information in this manner?

Edward Friedler, MD
Annandale, Va


I still dictate my notes and they very much tell a story that an EHR cannot. I have been audited repeatedly and I always have all the bullet points and essentials that the insurance company wants, but this information is in a format that everyone—including patients—can read and appreciate.

The move to APSO (assessment, plan, subjective, objective) from SOAP (subjective, objective, assessment, plan) is an example of the tail wagging the dog. Rather than fix the note so the time-honored SOAP format works, we acknowledge that no one actually reads the long template notes and they want to get to the bottom line (ie, the assessment and plan).

My dream is to return to the days when we only listed the positive findings, the assumption being that a competent physician did the exam that was required and it’s unnecessary to state that the examined anatomy was normal. Unfortunately, so much of what we must do is driven by lawyers and insurance companies—not by doctors.

David M. Brill, DO
Rocky River, Ohio


I now take photos of all of the ludicrous choices our EHR tosses at me, such as “laceration of third eyelid” or “injury, crushed by falling aircraft due to terrorist.” Most of my EHR entries now say, “See scanned handwritten note for accuracy.”

The issue of EHRs needs to be kept on the front burner. It is destroying doctor/patient relationships and quality diagnostic care while hiding the important findings in the garbage.

Jay Hammett, MD
Knoxville, Tenn


I’m in a group practice of 10 family physicians and in a typical workday, each of us sees 23 to 25 patients, answers e-mails/phone calls, and reviews labs/studies, which leaves no time for anything else. There’s a constant struggle to stay on top of the quality of the notes. I have preserved the quality of my own notes by free typing. I free type a differential next to my assessment or on the first line of the plan. I don’t use templates; they slow me down too much.

Kelly Luba, DO
Phoenix, Ariz


I was a civil service physician working for the Department of the Navy in 2005 when EHRs were thrust upon me. The system was not particularly user-friendly. Free texting was highly discouraged and it was strongly preferred that we used structured text embedded in the program.

I couldn’t use the program as envisioned, so I found a work-around. I would paste the 4 sections of the SOAP note directly into the appropriate free text sections of the electronic record. My assessment included the correct diagnosis, and I would pick a general EHR diagnosis from the dropdown list. Visually, my records did not look any different from those of other health care providers who used structured text.

I used this method until my civil service retirement in 2014. All of my record peer reviews were outstanding, and I was told that my records were easy to understand. I finally let on to all that I never used structured text and that all of my records were really written the old-fashioned way. I still used a clipboard during the patient visit, and completed all records after the patient left.

 

 

David F. Scaccia, DO, MPH
Kittery, Maine

Dr. Hickner’s editorial “EHRs: Something’s gotta give” (J Fam Pract. 2014;63:558) prompted me to reflect on the elements of electronic health records (EHRs) that cannot change and the ones that can.

The EHR system I use allows the EHR to serve as a 
quality recorder, and it appears 
this is the most important part,
 because the reminders of what
 needs to be documented come first and are color-coded. From a reimbursement point of view, what is important is not the narrative, but the expanded “elements” that make it a billing document. I believe this will not change.

What can change is how the note information is organized, and I think the organization should be different for specific roles. At intake, a medical assistant can review allergies, medication lists, and preventive services; update family history; and take vital signs and history of present illness (HPI). As the physician, I want the note to show the information in the order that I process it during the visit: 1) allergies/medication list, 2) concerns/complaints with brief documentation, 3) vitals, 4) physical, 5) assessment, and 6) plan.

After the note is signed off on, I want a different format for review purposes: 1) assessment/plan (because this is what I look at first for follow-up), 2) HPI/review of systems, 3) physical, 4) allergies, 5) medication list, 6) past medical history, and 7) quality reminders (if they show up at all after the visit is complete).

Is it asking too much for a programmer to make the EHR organize information in this manner?

Edward Friedler, MD
Annandale, Va


I still dictate my notes and they very much tell a story that an EHR cannot. I have been audited repeatedly and I always have all the bullet points and essentials that the insurance company wants, but this information is in a format that everyone—including patients—can read and appreciate.

The move to APSO (assessment, plan, subjective, objective) from SOAP (subjective, objective, assessment, plan) is an example of the tail wagging the dog. Rather than fix the note so the time-honored SOAP format works, we acknowledge that no one actually reads the long template notes and they want to get to the bottom line (ie, the assessment and plan).

My dream is to return to the days when we only listed the positive findings, the assumption being that a competent physician did the exam that was required and it’s unnecessary to state that the examined anatomy was normal. Unfortunately, so much of what we must do is driven by lawyers and insurance companies—not by doctors.

David M. Brill, DO
Rocky River, Ohio


I now take photos of all of the ludicrous choices our EHR tosses at me, such as “laceration of third eyelid” or “injury, crushed by falling aircraft due to terrorist.” Most of my EHR entries now say, “See scanned handwritten note for accuracy.”

The issue of EHRs needs to be kept on the front burner. It is destroying doctor/patient relationships and quality diagnostic care while hiding the important findings in the garbage.

Jay Hammett, MD
Knoxville, Tenn


I’m in a group practice of 10 family physicians and in a typical workday, each of us sees 23 to 25 patients, answers e-mails/phone calls, and reviews labs/studies, which leaves no time for anything else. There’s a constant struggle to stay on top of the quality of the notes. I have preserved the quality of my own notes by free typing. I free type a differential next to my assessment or on the first line of the plan. I don’t use templates; they slow me down too much.

Kelly Luba, DO
Phoenix, Ariz


I was a civil service physician working for the Department of the Navy in 2005 when EHRs were thrust upon me. The system was not particularly user-friendly. Free texting was highly discouraged and it was strongly preferred that we used structured text embedded in the program.

I couldn’t use the program as envisioned, so I found a work-around. I would paste the 4 sections of the SOAP note directly into the appropriate free text sections of the electronic record. My assessment included the correct diagnosis, and I would pick a general EHR diagnosis from the dropdown list. Visually, my records did not look any different from those of other health care providers who used structured text.

I used this method until my civil service retirement in 2014. All of my record peer reviews were outstanding, and I was told that my records were easy to understand. I finally let on to all that I never used structured text and that all of my records were really written the old-fashioned way. I still used a clipboard during the patient visit, and completed all records after the patient left.

 

 

David F. Scaccia, DO, MPH
Kittery, Maine

References

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