Vascular surgery is the most morbid of the noncardiac surgeries, with a 30‐day mortality estimated to be 3% to 10% and 6‐month mortality estimated to be 10% to 30%.14 Adverse outcomes are highly correlated with the presence of perioperative ischemia and infarction. Perioperative ischemia is associated with a 9‐fold increase in the odds of unstable angina, nonfatal myocardial infarction, and cardiac death, while a perioperative myocardial infarction increases the odds of death 20‐fold up to 2 years after surgery.57 Prior research has centered on the single or combination use of perioperative beta‐blockers and statins, which has been associated with decreased short‐term and long‐term mortality after vascular surgery,814 with the exceptions of the Metoprolol After Vascular Surgery (MAVS)15 and the Perioperative Beta‐Blockade (POBBLE) studies,16 which were negative beta‐blocker randomized controlled trials exclusively in vascular surgery patients, and the Perioperative Ischemic Evaluation (POISE) study,17 which was the largest perioperative beta‐blocker trial to date in noncardiac surgery, with 41% of the patients undergoing vascular surgery.

There have been few studies assessing clinical outcomes in patients taking multiple concurrent cardioprotective medications. Clinicians are challenged to apply research results to their patients, who generally take multiple drugs. A retrospective cohort study of acute coronary syndrome patients did assess the use of evidence‐based, combination therapies, including aspirin, ACE inhibitors, beta‐blockers, and statins, compared to the use of none of these agents and found an association with decreased 6‐month mortality.18 There are no prior noncardiac surgery studies assessing the concurrent use of multiple possibly cardioprotective drugs. There is 1 cohort study of coronary artery bypass graft surgery patients that assessed aspirin, ACE inhibitor, beta‐blocker, and statin use and found associations with decreased mortality.19 As preoperative coronary revascularization has not been found to produce improved survival after vascular surgery, clarifying which perioperative medicines alone or in combination may improve outcomes becomes even more important.20 We sought to ascertain if the use of concurrent combination aspirin, ACE inhibitors, beta‐blockers, and statins compared to nonuse was associated with a decrease in 6‐month mortality after vascular surgery.

Patients and Methods

Results

Patient Characteristics

There were 3020 patients with a median age of 67 years, and interquartile range of 59 to 75 years. Ninety‐nine percent were male, and all patients were assessed for death at 6 months after surgery (Table 1). Ten percent (304) had combination all‐4‐drug exposure, 22% (652) had 3‐drug exposure, 24% (736) had 2‐drug exposure, 26% (783) had 1‐drug exposure, and 18% (545) had no study drug exposures. Eight percent (229) of surgeries were aortic, 28% (861) were carotid, 28% (852) were lower extremity amputation, and 36% (1078) were lower extremity bypass. Twenty‐two percent (665) of patients were low risk, with a RCRI of 0, 60% (1822) were moderate risk with a RCRI of 1 to 2, and 18% (553) were high risk with a RCRI of 3. Overall the 6‐month mortality was 9.7% (294). The 6‐month mortality for carotid endarterectomy was 5.0% (43/861), for lower extremity bypass 7.6% (82/1078), for aorta repair 9.2% (21/229), and for lower extremity amputation 17.4% (148/852).

Table 1.Patient Demographics and Unadjusted Relative Risk of 6‐month Mortality

Variable	Level	N (%) Overall N = 3020	Relative Risk (95% CI)	Chi Square P‐Value
NOTE: Overall 6 month mortality: 9.7% (294). Abbreviations: Ace, angiotensin‐converting enzyme; CA, cancer; CAD, coronary artery disease; CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; CVA, cerebral vascular disease; DM, diabetes mellitus; HTN, hypertension; IQR, interquartile range; Lipid, hyperlipidemia; RCRI, Revised cardiac risk index; TIA, transient ischemic attack. * Age was continuous. P for linear trend. Chi‐square for overall group effect.
Age: year, median (IQR)		67 (59, 75)	1.04 (1.031.06)	<0.001*
Sex	Female	44 (1.5)	1	0.490
	Male	2976 (98.5)	1.48 (0.464.81)
Preoperative medical conditions	HTN	2388 (79.1)	1.40 (0.011.93)	0.036
	DM	1455 (48.2)	1.45 (1.131.84)	0.003
COPD	912 (30.2)	1.71 (1.342.19)	<0.001
CA	674 (22.3)	1.42 (1.091.86)	0.012
CKD	344 (11.4)	2.04 (1.492.80)	<0.001
CAD	1479 (49.0)	1.51 (1.181.92)	0.001
CHF	911 (30.2)	2.41 (1.893.08)	<0.001
CVA/TIA	802 (26.6)	1.08 (0.821.41)	0.587
Lipid	865 (28.6)	0.81 (0.611.06)	0.123
Blood chemistry	Creatinine > 2	228 (7.5)	3.11 (2.224.36)	<0.001
	Albumin 3.5	629 (20.8)	3.60 (2.804.62)	<0.001
Medication use	Aspirin	1773 (58.7)	1.12 (0.881.44)	0.355
	ACE, inhibitor	1238 (41.0)	0.81 (0.631.04)	0.090
Statin	1214 (40.2)	0.66 (0.510.86)	0.001
Beta blocker	1202 (39.8)	0.76 (0.590.98)	0.031
Clonidine	115 (3.8)	1.65 (0.972.80)	0.080
Insulin	474 (15.7)	1.47 (1.091.98)	0.013
Number of study drugs used	None	545 (18.0)	1	0.018
	One of 4	783 (25.9)	1.06 (0.751.51)
Two of 4	736 (24.4)	0.94 (0.651.35)
Three of 4	652 (21.6)	0.73 (0.491.08)
All four	304 (10.1)	0.66 (0.391.09)
Type of surgery	Carotid	861 (28.5)	1	<0.001
	Bypass	1078 (35.7)	1.57 (1.072.29)
Aorta	229 (7.6)	1.92 (1.123.31)
Amputation	852 (28.2)	4.00 (2.815.70)
RCRI category	0	665 (22.0)	1	<0.001
	1	976 (32.3)	1.12 (0.761.66)
2	846 (28.0)	1.66 (1.142.42)
3	553 (17.6)	2.83 (1.934.14)
Surgery year	1998	539 (17.8)	1	0.804
	1999	463 (15.3)	1.36 (0.892.07)
2000	418 (13.8)	1.07 (0.681.68)
2001	407 (13.5)	1.23 (0.791.92)
2002	368 (12.2)	1.34 (0.962.10)
2003	371 (12.3)	1.25 (0.801.97)
2004	395 (13.1)	1.17 (0.741.84)
2005	59 (2.0)	0.80 (0.282.30)

The most common single‐drug exposure was aspirin, 14% (416), followed by ACE inhibitors, 5% (163) (Table 2). The more common 2‐drug exposures included ACE inhibitors and aspirin, 7% (203), aspirin and beta‐blockers, 5% (161), and aspirin and statins, 5% (141). The common 3‐drug combinations included aspirin, beta‐blockers, and statins, 8% (229); ACE inhibitors, aspirin, and statins, 6% (167); and ACE inhibitors, aspirin, and beta‐blockers, 5% (152). ACE inhibitor exposure was common in all combinations, eg, 20.8% of the 1‐drug group had exposure to an ACE inhibitor, 40.5% in the 2‐drug group, 64.9% in the 3‐drug group, and all patients in the 4‐drug group. Overall, 39.3% of patients in the study had ACE inhibitor exposure. The gross unadjusted mortality for each drug exposure group was 10.6% for the no drug group, 11.2% for the 1‐drug group, 10.1% for the 2‐drug group, 8% for the 3‐drug group, and 7.2% for the 4‐drug group.

Table 2.Frequencies of Combination Drug Exposure Classes Before and 6 Months After Surgery

Drugs Used	Presurgery		6 Months Postsurgery
	Frequency	%	Frequency	%
* There were 294 deaths. Abbreviation: ACE, angiotensin‐converting enzyme.
None	545	18.1	669	24.5
1 Drug
Aspirin	416	53.1	169	28.3
ACE inhibitor	163	20.8	135	22.6
Beta‐blocker	110	14.1	163	27.2
Statin	94	12.0	131	21.9
All 1 drug	783	100.0	598	100.0
2 Drugs
Aspirin + ACE inhibitor	203	27.6	102	14.4
Aspirin + Beta‐blocker	161	21.8	117	16.5
Aspirin + Statin	141	19.2	86	12.1
ACE inhibitor + Beta‐blocker	56	7.6	103	14.5
ACE inhibitor + Statin	89	12.1	126	17.7
Beta‐blocker + Statin	86	11.7	176	24.8
All 2 drugs	36	100.0	710	100.0
3 Drugs
Aspirin + ACE inhibitor + Beta‐blocker	152	23.3	96	16.5
Aspirin + ACE inhibitor + Statin	167	25.6	103	17.7
Aspirin + Beta‐ blocker + Statin	229	35.1	165	28.4
ACE inhibitor + Beta‐blocker Statin	104	16.0	218	37.4
All 3 drugs	652	100.0	582	100.0
All 4 drugs	304	10.1	167	6.1
Total	3020	100.0	2726*	100.0

During the 6 complete years of the study (1998‐2004) the frequency of combination exposure for all 4 study drugs increased from 3.5% to 13.4%; 3‐drug exposure also increased, 14.7% to 27.8%; 2‐drug exposure remained relatively stable, 24.5% to 22%; and single‐drug exposure declined, 24.9% to 12.7% (Figure 1). Individual study drug exposures over the 6 years of the study generally also increased with respect to the other combinations: ACE inhibitor use increased, 34.5% to 42.5%; beta‐blocker, 27.8% to 53.4%; statin, 22.6% to 52.2%. The exception was aspirin, which was relatively stable, 54.5% in 1998, and 57.2% in 2004 (Figure 2).

Figure 1

Figure 2

We also compared the use of the study drug exposures at 6 months after surgery to use within 30 days before surgery (Table 2). In the VA healthcare system aspirin is cheaper for some patients to purchase over‐the‐counter. Aspirin is likely underestimated in this dataset. The frequency of follow‐up drug exposure at 6 months was overall similar to the drug exposure within 30 days before surgery. When aspirin was 1 of the combination exposures, the frequencies declined, and when aspirin was not 1 of the exposures, the frequencies generally increased. The frequency of no‐drug exposures increased from 18.1% before surgery to 24.5% 6 months after surgery, and the frequency of all 4 drug exposures decreased from 10.1% to 6.1%, respectively.

Discussion

This retrospective cohort study has demonstrated that the combination use of 4 drugs (aspirin, beta‐blockers, statins, and ACE inhibitors) compared to the use of none of these drugs had a trend toward decreased mortality, with a 49% decrease in propensity‐adjusted 6‐month mortality after vascular surgery and an NNT of 19. In addition, the combination use of 3 drug exposures was significantly associated with a 40% decrease in mortality, with propensity adjustment and NNT of 38; and the 2‐drug combination exposure showed a significant association, with a propensity‐adjusted 32% decreased mortality, and an NNT of 170. Both the unadjusted and adjusted analyses showed a linear trend, suggesting a dose‐response effect of more study‐drug exposure association with less 6‐month mortality and smaller NNT.

The lack of statistical significance for the 4‐drug exposure group is likely due to few patients and events in this group, and the exclusion of the first 2 quintiles (n = 339) due to having zero deaths with which to compare. It is not unusual to exclude patients from analyses in propensity methods. The patients we excluded were low‐risk who had survived to 6‐months after surgery, so they would have also been excluded in a propensity‐matched analysis. We did not perform propensity matching, as we had adequate homogeneity between our quintile strata, and were not powered to perform matching.

This is the first evidence of which we are aware of an association with decreased mortality for the combination perioperative use of aspirin, beta‐blockers, statins, and ACE inhibitors in vascular surgery patients. Aspirin has been associated with decreased mortality in patients undergoing coronary artery bypass graft surgery,25 but the effects of aspirin on noncardiac surgery outcomes is less clear.26

Beta‐blockers and statins have been associated with decreased short‐term and long‐term mortality after vascular surgery in the past,814 but more recent beta‐blocker studies have been negative, introducing controversy for the topic.1517, 27 Beta‐blockers are currently recommended as: Class I (should be used), Evidence Level B (limited population risk strata evaluated) for vascular surgery patients already taking a beta‐blocker or with positive ischemia on stress testing; Class IIa (reasonable to use), Evidence Level B for 1 or more clinical risk factors; or Class IIb (may be considered), Evidence Level B for no clinical risk factors, in the 2007 American College of Cardiology/American Heart Association (ACC/AHA) guidelines for perioperative evaluation.28 Perioperative beta‐blocker trials that have titrated the dose to a goal heart rate have consistently been associated with improved outcomes after vascular surgery,10, 12, 29, 30 and perioperative beta‐blocker trials that have used fixed dosing after surgery have been negative,1517, 27 including the POISE trial, which was associated with increased strokes and mortality.

This is also the first evidence of which we are aware that ACE inhibitors in combination with other drugs may be associated with decreased mortality after vascular surgery. While our study design does not support a causal relationship between ACE inhibitor exposure and decreased mortality, the increasing exposure in each drug exposure group for ACE inhibitors and correlated decreasing mortality is of sufficient interest to warrant further study. The use of ACE inhibitors has been associated with decreased mortality in patients with atherosclerotic vascular disease and CAD.31 There has been a concern expressed in the literature about the perioperative use of ACE inhibitors due to the potential for intraoperative hypotension.3236 Many centers advise patients to discontinue ACE inhibitor use the day before surgery. The number of patients studied remains small. More research is needed to clarify this issue. Use of angiotensin‐receptor blockers was not assessed; their use was considered to be rare, because use was restricted to patients intolerant of ACE inhibitors during the study period.

The 2005 ACC/AHA guideline for patients with peripheral arterial disease recommends the use of aspirin and statins.37 ACE inhibitors are recommended for both asymptomatic and symptomatic peripheral artery disease patients. The 2006 ACC/AHA guidelines for secondary prevention for patients with coronary or other atherosclerotic vascular disease recommends the use of chronic beta‐blockers.38 There appears to be some benefit in mortality from the combination aspirin, beta‐blocker, statin, and ACE inhibitor drug regimen in patients with established atherosclerotic vascular disease.

We expect the frequency of aspirin exposure to be underestimated in this study population (due to over‐the‐counter undocumented use), so our findings may be somewhat underestimated as well. This may also explain why the frequency of aspirin remained constant over time while the other drug exposures increased over time.

Our study has several limitations. First, our design was a retrospective cohort. Propensity analysis attempts to correct for confounding by indication in nonrandomized studies as patients that are exposed to a study drug are different from patients that are not exposed to the same study drug. For example, without adjustment for the propensity scores, the drug exposure classes were significantly associated with demographic and clinical characteristics when compare to the no‐drug‐exposure patients. However, with the propensity score adjustment, these associations were no longer statistically significant, with the exception of hyperlipidemia in patients taking all 4 drugs, which supports a rigorous propensity adjustment. We also controlled for the use of clonidine and serum albumin, both strong predictors of death after noncardiac surgery.22, 39 Second, we utilized administrative ICD‐9 code data for abstraction, and utilized only documented and coded comorbidities in the VA database. Unmeasured confounders may exist. Further, we cannot identify which combinations of specific study drugs were most associated with a reduction in 6‐month mortality, but we believe our data supports the case that all 4 of the study drugs be considered for each patient undergoing vascular surgery. It is important to also note that patient baseline risk, which can be difficult to clarify in retrospective cohort studies, will have a large impact on the results of the NNT. Lastly, this study needs to be repeated in a population that includes a greater number of female participants.

The combination exposure of 2 to 3 study drugs: aspirin, beta‐blockers, statins, and ACE inhibitors was consistently associated with decreased 6‐month mortality after vascular surgery, with a high prevalence of ACE inhibitor use, and the combination exposure of all 4 study drugs was marginally associated with decreased mortality. Consideration for the individual patient undergoing vascular surgery should include whether or not the patient may benefit from these 4 drugs. Further research with prospective and randomized studies is needed to clarify the optimum timing of these drugs and their combination efficacy in vascular surgery patients with attention to patient‐specific risk.

Vascular surgery is the most morbid of the noncardiac surgeries, with a 30‐day mortality estimated to be 3% to 10% and 6‐month mortality estimated to be 10% to 30%.14 Adverse outcomes are highly correlated with the presence of perioperative ischemia and infarction. Perioperative ischemia is associated with a 9‐fold increase in the odds of unstable angina, nonfatal myocardial infarction, and cardiac death, while a perioperative myocardial infarction increases the odds of death 20‐fold up to 2 years after surgery.57 Prior research has centered on the single or combination use of perioperative beta‐blockers and statins, which has been associated with decreased short‐term and long‐term mortality after vascular surgery,814 with the exceptions of the Metoprolol After Vascular Surgery (MAVS)15 and the Perioperative Beta‐Blockade (POBBLE) studies,16 which were negative beta‐blocker randomized controlled trials exclusively in vascular surgery patients, and the Perioperative Ischemic Evaluation (POISE) study,17 which was the largest perioperative beta‐blocker trial to date in noncardiac surgery, with 41% of the patients undergoing vascular surgery.

There have been few studies assessing clinical outcomes in patients taking multiple concurrent cardioprotective medications. Clinicians are challenged to apply research results to their patients, who generally take multiple drugs. A retrospective cohort study of acute coronary syndrome patients did assess the use of evidence‐based, combination therapies, including aspirin, ACE inhibitors, beta‐blockers, and statins, compared to the use of none of these agents and found an association with decreased 6‐month mortality.18 There are no prior noncardiac surgery studies assessing the concurrent use of multiple possibly cardioprotective drugs. There is 1 cohort study of coronary artery bypass graft surgery patients that assessed aspirin, ACE inhibitor, beta‐blocker, and statin use and found associations with decreased mortality.19 As preoperative coronary revascularization has not been found to produce improved survival after vascular surgery, clarifying which perioperative medicines alone or in combination may improve outcomes becomes even more important.20 We sought to ascertain if the use of concurrent combination aspirin, ACE inhibitors, beta‐blockers, and statins compared to nonuse was associated with a decrease in 6‐month mortality after vascular surgery.

Patients and Methods

Results

Patient Characteristics

There were 3020 patients with a median age of 67 years, and interquartile range of 59 to 75 years. Ninety‐nine percent were male, and all patients were assessed for death at 6 months after surgery (Table 1). Ten percent (304) had combination all‐4‐drug exposure, 22% (652) had 3‐drug exposure, 24% (736) had 2‐drug exposure, 26% (783) had 1‐drug exposure, and 18% (545) had no study drug exposures. Eight percent (229) of surgeries were aortic, 28% (861) were carotid, 28% (852) were lower extremity amputation, and 36% (1078) were lower extremity bypass. Twenty‐two percent (665) of patients were low risk, with a RCRI of 0, 60% (1822) were moderate risk with a RCRI of 1 to 2, and 18% (553) were high risk with a RCRI of 3. Overall the 6‐month mortality was 9.7% (294). The 6‐month mortality for carotid endarterectomy was 5.0% (43/861), for lower extremity bypass 7.6% (82/1078), for aorta repair 9.2% (21/229), and for lower extremity amputation 17.4% (148/852).

Table 1.Patient Demographics and Unadjusted Relative Risk of 6‐month Mortality

Variable	Level	N (%) Overall N = 3020	Relative Risk (95% CI)	Chi Square P‐Value
NOTE: Overall 6 month mortality: 9.7% (294). Abbreviations: Ace, angiotensin‐converting enzyme; CA, cancer; CAD, coronary artery disease; CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; CVA, cerebral vascular disease; DM, diabetes mellitus; HTN, hypertension; IQR, interquartile range; Lipid, hyperlipidemia; RCRI, Revised cardiac risk index; TIA, transient ischemic attack. * Age was continuous. P for linear trend. Chi‐square for overall group effect.
Age: year, median (IQR)		67 (59, 75)	1.04 (1.031.06)	<0.001*
Sex	Female	44 (1.5)	1	0.490
	Male	2976 (98.5)	1.48 (0.464.81)
Preoperative medical conditions	HTN	2388 (79.1)	1.40 (0.011.93)	0.036
	DM	1455 (48.2)	1.45 (1.131.84)	0.003
COPD	912 (30.2)	1.71 (1.342.19)	<0.001
CA	674 (22.3)	1.42 (1.091.86)	0.012
CKD	344 (11.4)	2.04 (1.492.80)	<0.001
CAD	1479 (49.0)	1.51 (1.181.92)	0.001
CHF	911 (30.2)	2.41 (1.893.08)	<0.001
CVA/TIA	802 (26.6)	1.08 (0.821.41)	0.587
Lipid	865 (28.6)	0.81 (0.611.06)	0.123
Blood chemistry	Creatinine > 2	228 (7.5)	3.11 (2.224.36)	<0.001
	Albumin 3.5	629 (20.8)	3.60 (2.804.62)	<0.001
Medication use	Aspirin	1773 (58.7)	1.12 (0.881.44)	0.355
	ACE, inhibitor	1238 (41.0)	0.81 (0.631.04)	0.090
Statin	1214 (40.2)	0.66 (0.510.86)	0.001
Beta blocker	1202 (39.8)	0.76 (0.590.98)	0.031
Clonidine	115 (3.8)	1.65 (0.972.80)	0.080
Insulin	474 (15.7)	1.47 (1.091.98)	0.013
Number of study drugs used	None	545 (18.0)	1	0.018
	One of 4	783 (25.9)	1.06 (0.751.51)
Two of 4	736 (24.4)	0.94 (0.651.35)
Three of 4	652 (21.6)	0.73 (0.491.08)
All four	304 (10.1)	0.66 (0.391.09)
Type of surgery	Carotid	861 (28.5)	1	<0.001
	Bypass	1078 (35.7)	1.57 (1.072.29)
Aorta	229 (7.6)	1.92 (1.123.31)
Amputation	852 (28.2)	4.00 (2.815.70)
RCRI category	0	665 (22.0)	1	<0.001
	1	976 (32.3)	1.12 (0.761.66)
2	846 (28.0)	1.66 (1.142.42)
3	553 (17.6)	2.83 (1.934.14)
Surgery year	1998	539 (17.8)	1	0.804
	1999	463 (15.3)	1.36 (0.892.07)
2000	418 (13.8)	1.07 (0.681.68)
2001	407 (13.5)	1.23 (0.791.92)
2002	368 (12.2)	1.34 (0.962.10)
2003	371 (12.3)	1.25 (0.801.97)
2004	395 (13.1)	1.17 (0.741.84)
2005	59 (2.0)	0.80 (0.282.30)

The most common single‐drug exposure was aspirin, 14% (416), followed by ACE inhibitors, 5% (163) (Table 2). The more common 2‐drug exposures included ACE inhibitors and aspirin, 7% (203), aspirin and beta‐blockers, 5% (161), and aspirin and statins, 5% (141). The common 3‐drug combinations included aspirin, beta‐blockers, and statins, 8% (229); ACE inhibitors, aspirin, and statins, 6% (167); and ACE inhibitors, aspirin, and beta‐blockers, 5% (152). ACE inhibitor exposure was common in all combinations, eg, 20.8% of the 1‐drug group had exposure to an ACE inhibitor, 40.5% in the 2‐drug group, 64.9% in the 3‐drug group, and all patients in the 4‐drug group. Overall, 39.3% of patients in the study had ACE inhibitor exposure. The gross unadjusted mortality for each drug exposure group was 10.6% for the no drug group, 11.2% for the 1‐drug group, 10.1% for the 2‐drug group, 8% for the 3‐drug group, and 7.2% for the 4‐drug group.

Table 2.Frequencies of Combination Drug Exposure Classes Before and 6 Months After Surgery

Drugs Used	Presurgery		6 Months Postsurgery
	Frequency	%	Frequency	%
* There were 294 deaths. Abbreviation: ACE, angiotensin‐converting enzyme.
None	545	18.1	669	24.5
1 Drug
Aspirin	416	53.1	169	28.3
ACE inhibitor	163	20.8	135	22.6
Beta‐blocker	110	14.1	163	27.2
Statin	94	12.0	131	21.9
All 1 drug	783	100.0	598	100.0
2 Drugs
Aspirin + ACE inhibitor	203	27.6	102	14.4
Aspirin + Beta‐blocker	161	21.8	117	16.5
Aspirin + Statin	141	19.2	86	12.1
ACE inhibitor + Beta‐blocker	56	7.6	103	14.5
ACE inhibitor + Statin	89	12.1	126	17.7
Beta‐blocker + Statin	86	11.7	176	24.8
All 2 drugs	36	100.0	710	100.0
3 Drugs
Aspirin + ACE inhibitor + Beta‐blocker	152	23.3	96	16.5
Aspirin + ACE inhibitor + Statin	167	25.6	103	17.7
Aspirin + Beta‐ blocker + Statin	229	35.1	165	28.4
ACE inhibitor + Beta‐blocker Statin	104	16.0	218	37.4
All 3 drugs	652	100.0	582	100.0
All 4 drugs	304	10.1	167	6.1
Total	3020	100.0	2726*	100.0

During the 6 complete years of the study (1998‐2004) the frequency of combination exposure for all 4 study drugs increased from 3.5% to 13.4%; 3‐drug exposure also increased, 14.7% to 27.8%; 2‐drug exposure remained relatively stable, 24.5% to 22%; and single‐drug exposure declined, 24.9% to 12.7% (Figure 1). Individual study drug exposures over the 6 years of the study generally also increased with respect to the other combinations: ACE inhibitor use increased, 34.5% to 42.5%; beta‐blocker, 27.8% to 53.4%; statin, 22.6% to 52.2%. The exception was aspirin, which was relatively stable, 54.5% in 1998, and 57.2% in 2004 (Figure 2).

Figure 1

Figure 2

We also compared the use of the study drug exposures at 6 months after surgery to use within 30 days before surgery (Table 2). In the VA healthcare system aspirin is cheaper for some patients to purchase over‐the‐counter. Aspirin is likely underestimated in this dataset. The frequency of follow‐up drug exposure at 6 months was overall similar to the drug exposure within 30 days before surgery. When aspirin was 1 of the combination exposures, the frequencies declined, and when aspirin was not 1 of the exposures, the frequencies generally increased. The frequency of no‐drug exposures increased from 18.1% before surgery to 24.5% 6 months after surgery, and the frequency of all 4 drug exposures decreased from 10.1% to 6.1%, respectively.

Discussion

This retrospective cohort study has demonstrated that the combination use of 4 drugs (aspirin, beta‐blockers, statins, and ACE inhibitors) compared to the use of none of these drugs had a trend toward decreased mortality, with a 49% decrease in propensity‐adjusted 6‐month mortality after vascular surgery and an NNT of 19. In addition, the combination use of 3 drug exposures was significantly associated with a 40% decrease in mortality, with propensity adjustment and NNT of 38; and the 2‐drug combination exposure showed a significant association, with a propensity‐adjusted 32% decreased mortality, and an NNT of 170. Both the unadjusted and adjusted analyses showed a linear trend, suggesting a dose‐response effect of more study‐drug exposure association with less 6‐month mortality and smaller NNT.

The lack of statistical significance for the 4‐drug exposure group is likely due to few patients and events in this group, and the exclusion of the first 2 quintiles (n = 339) due to having zero deaths with which to compare. It is not unusual to exclude patients from analyses in propensity methods. The patients we excluded were low‐risk who had survived to 6‐months after surgery, so they would have also been excluded in a propensity‐matched analysis. We did not perform propensity matching, as we had adequate homogeneity between our quintile strata, and were not powered to perform matching.

This is the first evidence of which we are aware of an association with decreased mortality for the combination perioperative use of aspirin, beta‐blockers, statins, and ACE inhibitors in vascular surgery patients. Aspirin has been associated with decreased mortality in patients undergoing coronary artery bypass graft surgery,25 but the effects of aspirin on noncardiac surgery outcomes is less clear.26

Beta‐blockers and statins have been associated with decreased short‐term and long‐term mortality after vascular surgery in the past,814 but more recent beta‐blocker studies have been negative, introducing controversy for the topic.1517, 27 Beta‐blockers are currently recommended as: Class I (should be used), Evidence Level B (limited population risk strata evaluated) for vascular surgery patients already taking a beta‐blocker or with positive ischemia on stress testing; Class IIa (reasonable to use), Evidence Level B for 1 or more clinical risk factors; or Class IIb (may be considered), Evidence Level B for no clinical risk factors, in the 2007 American College of Cardiology/American Heart Association (ACC/AHA) guidelines for perioperative evaluation.28 Perioperative beta‐blocker trials that have titrated the dose to a goal heart rate have consistently been associated with improved outcomes after vascular surgery,10, 12, 29, 30 and perioperative beta‐blocker trials that have used fixed dosing after surgery have been negative,1517, 27 including the POISE trial, which was associated with increased strokes and mortality.

This is also the first evidence of which we are aware that ACE inhibitors in combination with other drugs may be associated with decreased mortality after vascular surgery. While our study design does not support a causal relationship between ACE inhibitor exposure and decreased mortality, the increasing exposure in each drug exposure group for ACE inhibitors and correlated decreasing mortality is of sufficient interest to warrant further study. The use of ACE inhibitors has been associated with decreased mortality in patients with atherosclerotic vascular disease and CAD.31 There has been a concern expressed in the literature about the perioperative use of ACE inhibitors due to the potential for intraoperative hypotension.3236 Many centers advise patients to discontinue ACE inhibitor use the day before surgery. The number of patients studied remains small. More research is needed to clarify this issue. Use of angiotensin‐receptor blockers was not assessed; their use was considered to be rare, because use was restricted to patients intolerant of ACE inhibitors during the study period.

The 2005 ACC/AHA guideline for patients with peripheral arterial disease recommends the use of aspirin and statins.37 ACE inhibitors are recommended for both asymptomatic and symptomatic peripheral artery disease patients. The 2006 ACC/AHA guidelines for secondary prevention for patients with coronary or other atherosclerotic vascular disease recommends the use of chronic beta‐blockers.38 There appears to be some benefit in mortality from the combination aspirin, beta‐blocker, statin, and ACE inhibitor drug regimen in patients with established atherosclerotic vascular disease.

We expect the frequency of aspirin exposure to be underestimated in this study population (due to over‐the‐counter undocumented use), so our findings may be somewhat underestimated as well. This may also explain why the frequency of aspirin remained constant over time while the other drug exposures increased over time.

Our study has several limitations. First, our design was a retrospective cohort. Propensity analysis attempts to correct for confounding by indication in nonrandomized studies as patients that are exposed to a study drug are different from patients that are not exposed to the same study drug. For example, without adjustment for the propensity scores, the drug exposure classes were significantly associated with demographic and clinical characteristics when compare to the no‐drug‐exposure patients. However, with the propensity score adjustment, these associations were no longer statistically significant, with the exception of hyperlipidemia in patients taking all 4 drugs, which supports a rigorous propensity adjustment. We also controlled for the use of clonidine and serum albumin, both strong predictors of death after noncardiac surgery.22, 39 Second, we utilized administrative ICD‐9 code data for abstraction, and utilized only documented and coded comorbidities in the VA database. Unmeasured confounders may exist. Further, we cannot identify which combinations of specific study drugs were most associated with a reduction in 6‐month mortality, but we believe our data supports the case that all 4 of the study drugs be considered for each patient undergoing vascular surgery. It is important to also note that patient baseline risk, which can be difficult to clarify in retrospective cohort studies, will have a large impact on the results of the NNT. Lastly, this study needs to be repeated in a population that includes a greater number of female participants.

The combination exposure of 2 to 3 study drugs: aspirin, beta‐blockers, statins, and ACE inhibitors was consistently associated with decreased 6‐month mortality after vascular surgery, with a high prevalence of ACE inhibitor use, and the combination exposure of all 4 study drugs was marginally associated with decreased mortality. Consideration for the individual patient undergoing vascular surgery should include whether or not the patient may benefit from these 4 drugs. Further research with prospective and randomized studies is needed to clarify the optimum timing of these drugs and their combination efficacy in vascular surgery patients with attention to patient‐specific risk.

Vascular surgery is the most morbid of the noncardiac surgeries, with a 30‐day mortality estimated to be 3% to 10% and 6‐month mortality estimated to be 10% to 30%.14 Adverse outcomes are highly correlated with the presence of perioperative ischemia and infarction. Perioperative ischemia is associated with a 9‐fold increase in the odds of unstable angina, nonfatal myocardial infarction, and cardiac death, while a perioperative myocardial infarction increases the odds of death 20‐fold up to 2 years after surgery.57 Prior research has centered on the single or combination use of perioperative beta‐blockers and statins, which has been associated with decreased short‐term and long‐term mortality after vascular surgery,814 with the exceptions of the Metoprolol After Vascular Surgery (MAVS)15 and the Perioperative Beta‐Blockade (POBBLE) studies,16 which were negative beta‐blocker randomized controlled trials exclusively in vascular surgery patients, and the Perioperative Ischemic Evaluation (POISE) study,17 which was the largest perioperative beta‐blocker trial to date in noncardiac surgery, with 41% of the patients undergoing vascular surgery.

There have been few studies assessing clinical outcomes in patients taking multiple concurrent cardioprotective medications. Clinicians are challenged to apply research results to their patients, who generally take multiple drugs. A retrospective cohort study of acute coronary syndrome patients did assess the use of evidence‐based, combination therapies, including aspirin, ACE inhibitors, beta‐blockers, and statins, compared to the use of none of these agents and found an association with decreased 6‐month mortality.18 There are no prior noncardiac surgery studies assessing the concurrent use of multiple possibly cardioprotective drugs. There is 1 cohort study of coronary artery bypass graft surgery patients that assessed aspirin, ACE inhibitor, beta‐blocker, and statin use and found associations with decreased mortality.19 As preoperative coronary revascularization has not been found to produce improved survival after vascular surgery, clarifying which perioperative medicines alone or in combination may improve outcomes becomes even more important.20 We sought to ascertain if the use of concurrent combination aspirin, ACE inhibitors, beta‐blockers, and statins compared to nonuse was associated with a decrease in 6‐month mortality after vascular surgery.

Patients and Methods

Results

Patient Characteristics

There were 3020 patients with a median age of 67 years, and interquartile range of 59 to 75 years. Ninety‐nine percent were male, and all patients were assessed for death at 6 months after surgery (Table 1). Ten percent (304) had combination all‐4‐drug exposure, 22% (652) had 3‐drug exposure, 24% (736) had 2‐drug exposure, 26% (783) had 1‐drug exposure, and 18% (545) had no study drug exposures. Eight percent (229) of surgeries were aortic, 28% (861) were carotid, 28% (852) were lower extremity amputation, and 36% (1078) were lower extremity bypass. Twenty‐two percent (665) of patients were low risk, with a RCRI of 0, 60% (1822) were moderate risk with a RCRI of 1 to 2, and 18% (553) were high risk with a RCRI of 3. Overall the 6‐month mortality was 9.7% (294). The 6‐month mortality for carotid endarterectomy was 5.0% (43/861), for lower extremity bypass 7.6% (82/1078), for aorta repair 9.2% (21/229), and for lower extremity amputation 17.4% (148/852).

Table 1.Patient Demographics and Unadjusted Relative Risk of 6‐month Mortality

Variable	Level	N (%) Overall N = 3020	Relative Risk (95% CI)	Chi Square P‐Value
NOTE: Overall 6 month mortality: 9.7% (294). Abbreviations: Ace, angiotensin‐converting enzyme; CA, cancer; CAD, coronary artery disease; CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; CVA, cerebral vascular disease; DM, diabetes mellitus; HTN, hypertension; IQR, interquartile range; Lipid, hyperlipidemia; RCRI, Revised cardiac risk index; TIA, transient ischemic attack. * Age was continuous. P for linear trend. Chi‐square for overall group effect.
Age: year, median (IQR)		67 (59, 75)	1.04 (1.031.06)	<0.001*
Sex	Female	44 (1.5)	1	0.490
	Male	2976 (98.5)	1.48 (0.464.81)
Preoperative medical conditions	HTN	2388 (79.1)	1.40 (0.011.93)	0.036
	DM	1455 (48.2)	1.45 (1.131.84)	0.003
COPD	912 (30.2)	1.71 (1.342.19)	<0.001
CA	674 (22.3)	1.42 (1.091.86)	0.012
CKD	344 (11.4)	2.04 (1.492.80)	<0.001
CAD	1479 (49.0)	1.51 (1.181.92)	0.001
CHF	911 (30.2)	2.41 (1.893.08)	<0.001
CVA/TIA	802 (26.6)	1.08 (0.821.41)	0.587
Lipid	865 (28.6)	0.81 (0.611.06)	0.123
Blood chemistry	Creatinine > 2	228 (7.5)	3.11 (2.224.36)	<0.001
	Albumin 3.5	629 (20.8)	3.60 (2.804.62)	<0.001
Medication use	Aspirin	1773 (58.7)	1.12 (0.881.44)	0.355
	ACE, inhibitor	1238 (41.0)	0.81 (0.631.04)	0.090
Statin	1214 (40.2)	0.66 (0.510.86)	0.001
Beta blocker	1202 (39.8)	0.76 (0.590.98)	0.031
Clonidine	115 (3.8)	1.65 (0.972.80)	0.080
Insulin	474 (15.7)	1.47 (1.091.98)	0.013
Number of study drugs used	None	545 (18.0)	1	0.018
	One of 4	783 (25.9)	1.06 (0.751.51)
Two of 4	736 (24.4)	0.94 (0.651.35)
Three of 4	652 (21.6)	0.73 (0.491.08)
All four	304 (10.1)	0.66 (0.391.09)
Type of surgery	Carotid	861 (28.5)	1	<0.001
	Bypass	1078 (35.7)	1.57 (1.072.29)
Aorta	229 (7.6)	1.92 (1.123.31)
Amputation	852 (28.2)	4.00 (2.815.70)
RCRI category	0	665 (22.0)	1	<0.001
	1	976 (32.3)	1.12 (0.761.66)
2	846 (28.0)	1.66 (1.142.42)
3	553 (17.6)	2.83 (1.934.14)
Surgery year	1998	539 (17.8)	1	0.804
	1999	463 (15.3)	1.36 (0.892.07)
2000	418 (13.8)	1.07 (0.681.68)
2001	407 (13.5)	1.23 (0.791.92)
2002	368 (12.2)	1.34 (0.962.10)
2003	371 (12.3)	1.25 (0.801.97)
2004	395 (13.1)	1.17 (0.741.84)
2005	59 (2.0)	0.80 (0.282.30)

The most common single‐drug exposure was aspirin, 14% (416), followed by ACE inhibitors, 5% (163) (Table 2). The more common 2‐drug exposures included ACE inhibitors and aspirin, 7% (203), aspirin and beta‐blockers, 5% (161), and aspirin and statins, 5% (141). The common 3‐drug combinations included aspirin, beta‐blockers, and statins, 8% (229); ACE inhibitors, aspirin, and statins, 6% (167); and ACE inhibitors, aspirin, and beta‐blockers, 5% (152). ACE inhibitor exposure was common in all combinations, eg, 20.8% of the 1‐drug group had exposure to an ACE inhibitor, 40.5% in the 2‐drug group, 64.9% in the 3‐drug group, and all patients in the 4‐drug group. Overall, 39.3% of patients in the study had ACE inhibitor exposure. The gross unadjusted mortality for each drug exposure group was 10.6% for the no drug group, 11.2% for the 1‐drug group, 10.1% for the 2‐drug group, 8% for the 3‐drug group, and 7.2% for the 4‐drug group.

Table 2.Frequencies of Combination Drug Exposure Classes Before and 6 Months After Surgery

Drugs Used	Presurgery		6 Months Postsurgery
	Frequency	%	Frequency	%
* There were 294 deaths. Abbreviation: ACE, angiotensin‐converting enzyme.
None	545	18.1	669	24.5
1 Drug
Aspirin	416	53.1	169	28.3
ACE inhibitor	163	20.8	135	22.6
Beta‐blocker	110	14.1	163	27.2
Statin	94	12.0	131	21.9
All 1 drug	783	100.0	598	100.0
2 Drugs
Aspirin + ACE inhibitor	203	27.6	102	14.4
Aspirin + Beta‐blocker	161	21.8	117	16.5
Aspirin + Statin	141	19.2	86	12.1
ACE inhibitor + Beta‐blocker	56	7.6	103	14.5
ACE inhibitor + Statin	89	12.1	126	17.7
Beta‐blocker + Statin	86	11.7	176	24.8
All 2 drugs	36	100.0	710	100.0
3 Drugs
Aspirin + ACE inhibitor + Beta‐blocker	152	23.3	96	16.5
Aspirin + ACE inhibitor + Statin	167	25.6	103	17.7
Aspirin + Beta‐ blocker + Statin	229	35.1	165	28.4
ACE inhibitor + Beta‐blocker Statin	104	16.0	218	37.4
All 3 drugs	652	100.0	582	100.0
All 4 drugs	304	10.1	167	6.1
Total	3020	100.0	2726*	100.0

During the 6 complete years of the study (1998‐2004) the frequency of combination exposure for all 4 study drugs increased from 3.5% to 13.4%; 3‐drug exposure also increased, 14.7% to 27.8%; 2‐drug exposure remained relatively stable, 24.5% to 22%; and single‐drug exposure declined, 24.9% to 12.7% (Figure 1). Individual study drug exposures over the 6 years of the study generally also increased with respect to the other combinations: ACE inhibitor use increased, 34.5% to 42.5%; beta‐blocker, 27.8% to 53.4%; statin, 22.6% to 52.2%. The exception was aspirin, which was relatively stable, 54.5% in 1998, and 57.2% in 2004 (Figure 2).

Figure 1

Figure 2

We also compared the use of the study drug exposures at 6 months after surgery to use within 30 days before surgery (Table 2). In the VA healthcare system aspirin is cheaper for some patients to purchase over‐the‐counter. Aspirin is likely underestimated in this dataset. The frequency of follow‐up drug exposure at 6 months was overall similar to the drug exposure within 30 days before surgery. When aspirin was 1 of the combination exposures, the frequencies declined, and when aspirin was not 1 of the exposures, the frequencies generally increased. The frequency of no‐drug exposures increased from 18.1% before surgery to 24.5% 6 months after surgery, and the frequency of all 4 drug exposures decreased from 10.1% to 6.1%, respectively.

Discussion

This retrospective cohort study has demonstrated that the combination use of 4 drugs (aspirin, beta‐blockers, statins, and ACE inhibitors) compared to the use of none of these drugs had a trend toward decreased mortality, with a 49% decrease in propensity‐adjusted 6‐month mortality after vascular surgery and an NNT of 19. In addition, the combination use of 3 drug exposures was significantly associated with a 40% decrease in mortality, with propensity adjustment and NNT of 38; and the 2‐drug combination exposure showed a significant association, with a propensity‐adjusted 32% decreased mortality, and an NNT of 170. Both the unadjusted and adjusted analyses showed a linear trend, suggesting a dose‐response effect of more study‐drug exposure association with less 6‐month mortality and smaller NNT.

The lack of statistical significance for the 4‐drug exposure group is likely due to few patients and events in this group, and the exclusion of the first 2 quintiles (n = 339) due to having zero deaths with which to compare. It is not unusual to exclude patients from analyses in propensity methods. The patients we excluded were low‐risk who had survived to 6‐months after surgery, so they would have also been excluded in a propensity‐matched analysis. We did not perform propensity matching, as we had adequate homogeneity between our quintile strata, and were not powered to perform matching.

This is the first evidence of which we are aware of an association with decreased mortality for the combination perioperative use of aspirin, beta‐blockers, statins, and ACE inhibitors in vascular surgery patients. Aspirin has been associated with decreased mortality in patients undergoing coronary artery bypass graft surgery,25 but the effects of aspirin on noncardiac surgery outcomes is less clear.26

Beta‐blockers and statins have been associated with decreased short‐term and long‐term mortality after vascular surgery in the past,814 but more recent beta‐blocker studies have been negative, introducing controversy for the topic.1517, 27 Beta‐blockers are currently recommended as: Class I (should be used), Evidence Level B (limited population risk strata evaluated) for vascular surgery patients already taking a beta‐blocker or with positive ischemia on stress testing; Class IIa (reasonable to use), Evidence Level B for 1 or more clinical risk factors; or Class IIb (may be considered), Evidence Level B for no clinical risk factors, in the 2007 American College of Cardiology/American Heart Association (ACC/AHA) guidelines for perioperative evaluation.28 Perioperative beta‐blocker trials that have titrated the dose to a goal heart rate have consistently been associated with improved outcomes after vascular surgery,10, 12, 29, 30 and perioperative beta‐blocker trials that have used fixed dosing after surgery have been negative,1517, 27 including the POISE trial, which was associated with increased strokes and mortality.

This is also the first evidence of which we are aware that ACE inhibitors in combination with other drugs may be associated with decreased mortality after vascular surgery. While our study design does not support a causal relationship between ACE inhibitor exposure and decreased mortality, the increasing exposure in each drug exposure group for ACE inhibitors and correlated decreasing mortality is of sufficient interest to warrant further study. The use of ACE inhibitors has been associated with decreased mortality in patients with atherosclerotic vascular disease and CAD.31 There has been a concern expressed in the literature about the perioperative use of ACE inhibitors due to the potential for intraoperative hypotension.3236 Many centers advise patients to discontinue ACE inhibitor use the day before surgery. The number of patients studied remains small. More research is needed to clarify this issue. Use of angiotensin‐receptor blockers was not assessed; their use was considered to be rare, because use was restricted to patients intolerant of ACE inhibitors during the study period.

The 2005 ACC/AHA guideline for patients with peripheral arterial disease recommends the use of aspirin and statins.37 ACE inhibitors are recommended for both asymptomatic and symptomatic peripheral artery disease patients. The 2006 ACC/AHA guidelines for secondary prevention for patients with coronary or other atherosclerotic vascular disease recommends the use of chronic beta‐blockers.38 There appears to be some benefit in mortality from the combination aspirin, beta‐blocker, statin, and ACE inhibitor drug regimen in patients with established atherosclerotic vascular disease.

We expect the frequency of aspirin exposure to be underestimated in this study population (due to over‐the‐counter undocumented use), so our findings may be somewhat underestimated as well. This may also explain why the frequency of aspirin remained constant over time while the other drug exposures increased over time.

Our study has several limitations. First, our design was a retrospective cohort. Propensity analysis attempts to correct for confounding by indication in nonrandomized studies as patients that are exposed to a study drug are different from patients that are not exposed to the same study drug. For example, without adjustment for the propensity scores, the drug exposure classes were significantly associated with demographic and clinical characteristics when compare to the no‐drug‐exposure patients. However, with the propensity score adjustment, these associations were no longer statistically significant, with the exception of hyperlipidemia in patients taking all 4 drugs, which supports a rigorous propensity adjustment. We also controlled for the use of clonidine and serum albumin, both strong predictors of death after noncardiac surgery.22, 39 Second, we utilized administrative ICD‐9 code data for abstraction, and utilized only documented and coded comorbidities in the VA database. Unmeasured confounders may exist. Further, we cannot identify which combinations of specific study drugs were most associated with a reduction in 6‐month mortality, but we believe our data supports the case that all 4 of the study drugs be considered for each patient undergoing vascular surgery. It is important to also note that patient baseline risk, which can be difficult to clarify in retrospective cohort studies, will have a large impact on the results of the NNT. Lastly, this study needs to be repeated in a population that includes a greater number of female participants.

The combination exposure of 2 to 3 study drugs: aspirin, beta‐blockers, statins, and ACE inhibitors was consistently associated with decreased 6‐month mortality after vascular surgery, with a high prevalence of ACE inhibitor use, and the combination exposure of all 4 study drugs was marginally associated with decreased mortality. Consideration for the individual patient undergoing vascular surgery should include whether or not the patient may benefit from these 4 drugs. Further research with prospective and randomized studies is needed to clarify the optimum timing of these drugs and their combination efficacy in vascular surgery patients with attention to patient‐specific risk.

A 63‐year‐old man with multiple medical problems was transferred from a nursing home to the emergency room with progressively worsening diffuse abdominal pain of 3 days' duration. His vital signs were significant for heart rate of 94 beats per minute, blood pressure of 126/84 mmHg, respiratory rate of 20 breaths per minute, and oxygen saturation of 98% on room air. Abdominal examination showed diffuse tenderness in all quadrants. Active bowel sounds were heard; guarding or rigidity was absent. Examination of respiratory and cardiovascular system was unremarkable. His laboratory tests showed leukocytosis with left shift. Topogram done for planning computed tomography (CT) scan of abdomen (Figure 1) showed the following findings:

• 1

  The dilated sigmoid loops (outlined by linear black arrows) have closely apposed medial walls (arrowheads), giving the appearance of a coffee bean. In addition, the apex of the loop is seen under the left hemidiaphragm.

• 2

  The dilated sigmoid loop is seen to overlap the descending colon (the left flank overlap sign). The lateral margin of descending colon is shown with bold white arrows.

• 3

  The level of convergence of the 2 limbs of the loop is seen to lie below the lumbosacral junction and to the left of the midline (inferior convergence sign, shown by the bold black arrow).

• 4

  The small bowel and large bowel loops are dilated due to distal obstruction and are seen overlapping with the distended sigmoid colon.

• 5

  The rectal gas is not visualized.

Figure 1

These features were suggestive of sigmoid volvulus.

Patients with sigmoid volvulus are often in the sixth to eighth decades of life and frequently have concomitant chronic illnesses, such as cardiac, pulmonary, and renal disease, that significantly influence their outcome.14 Males develop sigmoid volvulus more commonly than do females. In a large series of patients with sigmoid volvulus, 30% had a history of psychiatric disease and 13% were institutionalized at the time of diagnosis.4 Abdominal tenderness is present in less than one‐third of patients with volvulus, and severe pain or signs of peritonitis suggest impending or actual colonic necrosis and perforation.

Plain radiograph of the abdomen is usually diagnostic and reveals a dilated ahaustral sigmoid colon with features of closed‐loop obstruction (bent inner‐tube appearance). The apex of the loop usually extends above the T10 vertebra. The various signs described for sigmoid volvulus on plain radiograph and the sensitivity and specificity for these are given in Table 1.5 A diagnosis of sigmoid volvulus can be made with abdominal radiographs alone in as many as 85% of instances.3 A CT scan helps detect the changes of bowel ischemia and can confirm or provide an alternate diagnosis. A single contrast barium enema examination may be done if signs of bowel ischemia or perforation are absent. This may reveal a mucosal spiral pattern or bird's beak appearance (due to abrupt termination of the barium column) at the site of twist.

In patients with abdominal films most consistent with a sigmoid volvulus, initial rigid or flexible proctosigmoidoscopy may allow prompt decompression of the volvulus. Early recognition and treatment are necessary to prevent mortality. Placement of a rectal tube for 48 hours may minimize the possibility of early recurrence. Successful reduction of sigmoid volvulus also has been reported with colonoscopy; however, the procedure must be performed carefully with minimal insufflation of air (or preferably carbon dioxide) to minimize the risk of perforation of the distended, inflamed bowel. Endoscopic reduction of sigmoid volvulus alone is associated with a recurrence rate of 25% to 50%.1, 2, 6, 7 Hence, elective sigmoid resection and coloproctostomy, or in medically compromised patients, end colostomy, should follow proctoscopic decompression and mechanical preparation of the bowel. Recurrence rates with this approach are 3% to 6%.1, 2, 7 Patients requiring emergent laparotomy for strangulated sigmoid volvulus require sigmoid resection with end colostomy and a Hartmann pouch. The patient's volvulus was successfully decompressed with colonoscopy. He was offered elective sigmoid resection and coloproctostomy as a definitive therapy, which he declined.

A 63‐year‐old man with multiple medical problems was transferred from a nursing home to the emergency room with progressively worsening diffuse abdominal pain of 3 days' duration. His vital signs were significant for heart rate of 94 beats per minute, blood pressure of 126/84 mmHg, respiratory rate of 20 breaths per minute, and oxygen saturation of 98% on room air. Abdominal examination showed diffuse tenderness in all quadrants. Active bowel sounds were heard; guarding or rigidity was absent. Examination of respiratory and cardiovascular system was unremarkable. His laboratory tests showed leukocytosis with left shift. Topogram done for planning computed tomography (CT) scan of abdomen (Figure 1) showed the following findings:

• 1

  The dilated sigmoid loops (outlined by linear black arrows) have closely apposed medial walls (arrowheads), giving the appearance of a coffee bean. In addition, the apex of the loop is seen under the left hemidiaphragm.

• 2

  The dilated sigmoid loop is seen to overlap the descending colon (the left flank overlap sign). The lateral margin of descending colon is shown with bold white arrows.

• 3

  The level of convergence of the 2 limbs of the loop is seen to lie below the lumbosacral junction and to the left of the midline (inferior convergence sign, shown by the bold black arrow).

• 4

  The small bowel and large bowel loops are dilated due to distal obstruction and are seen overlapping with the distended sigmoid colon.

• 5

  The rectal gas is not visualized.

Figure 1

These features were suggestive of sigmoid volvulus.

Patients with sigmoid volvulus are often in the sixth to eighth decades of life and frequently have concomitant chronic illnesses, such as cardiac, pulmonary, and renal disease, that significantly influence their outcome.14 Males develop sigmoid volvulus more commonly than do females. In a large series of patients with sigmoid volvulus, 30% had a history of psychiatric disease and 13% were institutionalized at the time of diagnosis.4 Abdominal tenderness is present in less than one‐third of patients with volvulus, and severe pain or signs of peritonitis suggest impending or actual colonic necrosis and perforation.

Plain radiograph of the abdomen is usually diagnostic and reveals a dilated ahaustral sigmoid colon with features of closed‐loop obstruction (bent inner‐tube appearance). The apex of the loop usually extends above the T10 vertebra. The various signs described for sigmoid volvulus on plain radiograph and the sensitivity and specificity for these are given in Table 1.5 A diagnosis of sigmoid volvulus can be made with abdominal radiographs alone in as many as 85% of instances.3 A CT scan helps detect the changes of bowel ischemia and can confirm or provide an alternate diagnosis. A single contrast barium enema examination may be done if signs of bowel ischemia or perforation are absent. This may reveal a mucosal spiral pattern or bird's beak appearance (due to abrupt termination of the barium column) at the site of twist.

In patients with abdominal films most consistent with a sigmoid volvulus, initial rigid or flexible proctosigmoidoscopy may allow prompt decompression of the volvulus. Early recognition and treatment are necessary to prevent mortality. Placement of a rectal tube for 48 hours may minimize the possibility of early recurrence. Successful reduction of sigmoid volvulus also has been reported with colonoscopy; however, the procedure must be performed carefully with minimal insufflation of air (or preferably carbon dioxide) to minimize the risk of perforation of the distended, inflamed bowel. Endoscopic reduction of sigmoid volvulus alone is associated with a recurrence rate of 25% to 50%.1, 2, 6, 7 Hence, elective sigmoid resection and coloproctostomy, or in medically compromised patients, end colostomy, should follow proctoscopic decompression and mechanical preparation of the bowel. Recurrence rates with this approach are 3% to 6%.1, 2, 7 Patients requiring emergent laparotomy for strangulated sigmoid volvulus require sigmoid resection with end colostomy and a Hartmann pouch. The patient's volvulus was successfully decompressed with colonoscopy. He was offered elective sigmoid resection and coloproctostomy as a definitive therapy, which he declined.

A 63‐year‐old man with multiple medical problems was transferred from a nursing home to the emergency room with progressively worsening diffuse abdominal pain of 3 days' duration. His vital signs were significant for heart rate of 94 beats per minute, blood pressure of 126/84 mmHg, respiratory rate of 20 breaths per minute, and oxygen saturation of 98% on room air. Abdominal examination showed diffuse tenderness in all quadrants. Active bowel sounds were heard; guarding or rigidity was absent. Examination of respiratory and cardiovascular system was unremarkable. His laboratory tests showed leukocytosis with left shift. Topogram done for planning computed tomography (CT) scan of abdomen (Figure 1) showed the following findings:

• 1

  The dilated sigmoid loops (outlined by linear black arrows) have closely apposed medial walls (arrowheads), giving the appearance of a coffee bean. In addition, the apex of the loop is seen under the left hemidiaphragm.

• 2

  The dilated sigmoid loop is seen to overlap the descending colon (the left flank overlap sign). The lateral margin of descending colon is shown with bold white arrows.

• 3

  The level of convergence of the 2 limbs of the loop is seen to lie below the lumbosacral junction and to the left of the midline (inferior convergence sign, shown by the bold black arrow).

• 4

  The small bowel and large bowel loops are dilated due to distal obstruction and are seen overlapping with the distended sigmoid colon.

• 5

  The rectal gas is not visualized.

Figure 1

These features were suggestive of sigmoid volvulus.

Patients with sigmoid volvulus are often in the sixth to eighth decades of life and frequently have concomitant chronic illnesses, such as cardiac, pulmonary, and renal disease, that significantly influence their outcome.14 Males develop sigmoid volvulus more commonly than do females. In a large series of patients with sigmoid volvulus, 30% had a history of psychiatric disease and 13% were institutionalized at the time of diagnosis.4 Abdominal tenderness is present in less than one‐third of patients with volvulus, and severe pain or signs of peritonitis suggest impending or actual colonic necrosis and perforation.

Plain radiograph of the abdomen is usually diagnostic and reveals a dilated ahaustral sigmoid colon with features of closed‐loop obstruction (bent inner‐tube appearance). The apex of the loop usually extends above the T10 vertebra. The various signs described for sigmoid volvulus on plain radiograph and the sensitivity and specificity for these are given in Table 1.5 A diagnosis of sigmoid volvulus can be made with abdominal radiographs alone in as many as 85% of instances.3 A CT scan helps detect the changes of bowel ischemia and can confirm or provide an alternate diagnosis. A single contrast barium enema examination may be done if signs of bowel ischemia or perforation are absent. This may reveal a mucosal spiral pattern or bird's beak appearance (due to abrupt termination of the barium column) at the site of twist.

In patients with abdominal films most consistent with a sigmoid volvulus, initial rigid or flexible proctosigmoidoscopy may allow prompt decompression of the volvulus. Early recognition and treatment are necessary to prevent mortality. Placement of a rectal tube for 48 hours may minimize the possibility of early recurrence. Successful reduction of sigmoid volvulus also has been reported with colonoscopy; however, the procedure must be performed carefully with minimal insufflation of air (or preferably carbon dioxide) to minimize the risk of perforation of the distended, inflamed bowel. Endoscopic reduction of sigmoid volvulus alone is associated with a recurrence rate of 25% to 50%.1, 2, 6, 7 Hence, elective sigmoid resection and coloproctostomy, or in medically compromised patients, end colostomy, should follow proctoscopic decompression and mechanical preparation of the bowel. Recurrence rates with this approach are 3% to 6%.1, 2, 7 Patients requiring emergent laparotomy for strangulated sigmoid volvulus require sigmoid resection with end colostomy and a Hartmann pouch. The patient's volvulus was successfully decompressed with colonoscopy. He was offered elective sigmoid resection and coloproctostomy as a definitive therapy, which he declined.

A 56‐year‐old man with a 1‐year history of a verrucous nodule on his left foot presented to our department due to the unexpected growth. He was previously diagnosed with a plantar wart so underwent salicylic ointment application, liquid‐nitrogen cryotherapy and electrocoagulation, with no improvement of the condition.

Clinical examination revealed a 22‐mm flesh‐colored, centrally hypopigmented and ulcerated, exophytic nodule, with an adjacent 5 4 mm pink papule with telangiectasia (Figure 1A and B).

Figure 1

Histological examination established the diagnosis of ulcerated amelanotic malignant melanoma (Clark's level IV, Breslow's thickness of 3 mm) with a satellite nodule. Radical inguinal lymph node dissection yielded a negative result. Total‐body computed tomographic scan was unremarkable. One‐year follow‐up revealed no metastatic disease.

Melanoma of the foot accounts for 3% to 15% of all cutaneous melanoma. In acral skin, melanomas tend to have unusual clinical appearances. Amelanotic variants may masquerade as several benign hyperkeratotic dermatoses (warts, calluses, fungal disorders, foreign bodies, moles, keratoacanthomas, hematomas) increasing misdiagnosis and inadequate treatment rates, with a poorer patient outcome.1 Pedal lesions require close observation and biopsy when diagnostic uncertainty exists or when therapeutic interventions fail.

A 56‐year‐old man with a 1‐year history of a verrucous nodule on his left foot presented to our department due to the unexpected growth. He was previously diagnosed with a plantar wart so underwent salicylic ointment application, liquid‐nitrogen cryotherapy and electrocoagulation, with no improvement of the condition.

Clinical examination revealed a 22‐mm flesh‐colored, centrally hypopigmented and ulcerated, exophytic nodule, with an adjacent 5 4 mm pink papule with telangiectasia (Figure 1A and B).

Figure 1

Histological examination established the diagnosis of ulcerated amelanotic malignant melanoma (Clark's level IV, Breslow's thickness of 3 mm) with a satellite nodule. Radical inguinal lymph node dissection yielded a negative result. Total‐body computed tomographic scan was unremarkable. One‐year follow‐up revealed no metastatic disease.

Melanoma of the foot accounts for 3% to 15% of all cutaneous melanoma. In acral skin, melanomas tend to have unusual clinical appearances. Amelanotic variants may masquerade as several benign hyperkeratotic dermatoses (warts, calluses, fungal disorders, foreign bodies, moles, keratoacanthomas, hematomas) increasing misdiagnosis and inadequate treatment rates, with a poorer patient outcome.1 Pedal lesions require close observation and biopsy when diagnostic uncertainty exists or when therapeutic interventions fail.

A 56‐year‐old man with a 1‐year history of a verrucous nodule on his left foot presented to our department due to the unexpected growth. He was previously diagnosed with a plantar wart so underwent salicylic ointment application, liquid‐nitrogen cryotherapy and electrocoagulation, with no improvement of the condition.

Clinical examination revealed a 22‐mm flesh‐colored, centrally hypopigmented and ulcerated, exophytic nodule, with an adjacent 5 4 mm pink papule with telangiectasia (Figure 1A and B).

Figure 1

Histological examination established the diagnosis of ulcerated amelanotic malignant melanoma (Clark's level IV, Breslow's thickness of 3 mm) with a satellite nodule. Radical inguinal lymph node dissection yielded a negative result. Total‐body computed tomographic scan was unremarkable. One‐year follow‐up revealed no metastatic disease.

Melanoma of the foot accounts for 3% to 15% of all cutaneous melanoma. In acral skin, melanomas tend to have unusual clinical appearances. Amelanotic variants may masquerade as several benign hyperkeratotic dermatoses (warts, calluses, fungal disorders, foreign bodies, moles, keratoacanthomas, hematomas) increasing misdiagnosis and inadequate treatment rates, with a poorer patient outcome.1 Pedal lesions require close observation and biopsy when diagnostic uncertainty exists or when therapeutic interventions fail.

A 53‐year‐old man with a history of heavy tobacco use presented with shortness of breath. Eight days prior to his presentation he was diagnosed with multiple rib fractures after suffering an assault. Since then he had developed dyspnea and a nonproductive cough. A chest x‐ray revealed a large pneumothorax on the right with approximately 80% volume loss (arrow, Figure 1).

Figure 1

Tube thoracostomy was performed. Repeat chest x‐ray showed that the pneumothorax had resolved, revealing a consolidation likely caused by either reexpansion pulmonary edema1, 2 or, given its location in the superior segment of the right lower lobe, aspiration pneumonia (thin arrow, Figure 2). Also seen in the x‐ray is an old scar (thick arrow, Figure 2) and apical bullous changes with hyperinflated lungs suggestive of chronic obstructive pulmonary disease (COPD).

Figure 2

DISCUSSION

Pneumothorax is a common complication of blunt trauma and rib fractures.3 While the patient did not have a preceding diagnosis of COPD, his extensive smoking history and his radiographic changes are consistent with COPD, which is a risk factor for pneumothroax. Secondary pneumothorax is defined as pneumothorax that occurs as a complication of underlying lung disease and is most commonly associated with COPD,4 with rupturing of apical blebs as the proposed mechanism. This patient suffered a pneumothorax due to trauma, but given his COPD he is at increased risk for developing spontaneous pneumothorax in the future.

A 53‐year‐old man with a history of heavy tobacco use presented with shortness of breath. Eight days prior to his presentation he was diagnosed with multiple rib fractures after suffering an assault. Since then he had developed dyspnea and a nonproductive cough. A chest x‐ray revealed a large pneumothorax on the right with approximately 80% volume loss (arrow, Figure 1).

Figure 1

Tube thoracostomy was performed. Repeat chest x‐ray showed that the pneumothorax had resolved, revealing a consolidation likely caused by either reexpansion pulmonary edema1, 2 or, given its location in the superior segment of the right lower lobe, aspiration pneumonia (thin arrow, Figure 2). Also seen in the x‐ray is an old scar (thick arrow, Figure 2) and apical bullous changes with hyperinflated lungs suggestive of chronic obstructive pulmonary disease (COPD).

Figure 2

DISCUSSION

Pneumothorax is a common complication of blunt trauma and rib fractures.3 While the patient did not have a preceding diagnosis of COPD, his extensive smoking history and his radiographic changes are consistent with COPD, which is a risk factor for pneumothroax. Secondary pneumothorax is defined as pneumothorax that occurs as a complication of underlying lung disease and is most commonly associated with COPD,4 with rupturing of apical blebs as the proposed mechanism. This patient suffered a pneumothorax due to trauma, but given his COPD he is at increased risk for developing spontaneous pneumothorax in the future.

A 53‐year‐old man with a history of heavy tobacco use presented with shortness of breath. Eight days prior to his presentation he was diagnosed with multiple rib fractures after suffering an assault. Since then he had developed dyspnea and a nonproductive cough. A chest x‐ray revealed a large pneumothorax on the right with approximately 80% volume loss (arrow, Figure 1).

Figure 1

Tube thoracostomy was performed. Repeat chest x‐ray showed that the pneumothorax had resolved, revealing a consolidation likely caused by either reexpansion pulmonary edema1, 2 or, given its location in the superior segment of the right lower lobe, aspiration pneumonia (thin arrow, Figure 2). Also seen in the x‐ray is an old scar (thick arrow, Figure 2) and apical bullous changes with hyperinflated lungs suggestive of chronic obstructive pulmonary disease (COPD).

Figure 2

DISCUSSION

Pneumothorax is a common complication of blunt trauma and rib fractures.3 While the patient did not have a preceding diagnosis of COPD, his extensive smoking history and his radiographic changes are consistent with COPD, which is a risk factor for pneumothroax. Secondary pneumothorax is defined as pneumothorax that occurs as a complication of underlying lung disease and is most commonly associated with COPD,4 with rupturing of apical blebs as the proposed mechanism. This patient suffered a pneumothorax due to trauma, but given his COPD he is at increased risk for developing spontaneous pneumothorax in the future.

A 68‐year‐old man with a history of congestive heart failure and hypertension presented to the emergency department with fatigue and dyspnea of 3 weeks duration. Physical examination was consistent with heart failure. In addition, a right upper extremity resting tremor was noticed. An electrocardiogram (ECG) revealed an atrial flutter with a conduction ratio of 4:1 (Figure 1A). He denied palpitations or a previous history of atrial flutter/fibrillation. Unlike typical atrial flutter, these flutter like waves were distinctly absent in lead III, the only limb lead not connected to the right arm.

Figure 1

While holding the patient's right arm to control the tremor, a second ECG tracing was obtained. As expected the flutter like waves disappeared (Figure 1B). These ECG findings were attributed to the patient's tremor. A neurological consultation established a clinical diagnosis of Parkinson's disease. His congestive heart failure (CHF) was treated with increasing diuretics and appropriate treatment for Parkinson's disease was initiated.

A 68‐year‐old man with a history of congestive heart failure and hypertension presented to the emergency department with fatigue and dyspnea of 3 weeks duration. Physical examination was consistent with heart failure. In addition, a right upper extremity resting tremor was noticed. An electrocardiogram (ECG) revealed an atrial flutter with a conduction ratio of 4:1 (Figure 1A). He denied palpitations or a previous history of atrial flutter/fibrillation. Unlike typical atrial flutter, these flutter like waves were distinctly absent in lead III, the only limb lead not connected to the right arm.

Figure 1

While holding the patient's right arm to control the tremor, a second ECG tracing was obtained. As expected the flutter like waves disappeared (Figure 1B). These ECG findings were attributed to the patient's tremor. A neurological consultation established a clinical diagnosis of Parkinson's disease. His congestive heart failure (CHF) was treated with increasing diuretics and appropriate treatment for Parkinson's disease was initiated.

A 68‐year‐old man with a history of congestive heart failure and hypertension presented to the emergency department with fatigue and dyspnea of 3 weeks duration. Physical examination was consistent with heart failure. In addition, a right upper extremity resting tremor was noticed. An electrocardiogram (ECG) revealed an atrial flutter with a conduction ratio of 4:1 (Figure 1A). He denied palpitations or a previous history of atrial flutter/fibrillation. Unlike typical atrial flutter, these flutter like waves were distinctly absent in lead III, the only limb lead not connected to the right arm.

Figure 1

While holding the patient's right arm to control the tremor, a second ECG tracing was obtained. As expected the flutter like waves disappeared (Figure 1B). These ECG findings were attributed to the patient's tremor. A neurological consultation established a clinical diagnosis of Parkinson's disease. His congestive heart failure (CHF) was treated with increasing diuretics and appropriate treatment for Parkinson's disease was initiated.

Quality of care in US hospitals is inconsistent and often below accepted standards.1 This observation has catalyzed a number of performance measurement initiatives intended to publicize gaps and spur quality improvement.2 As the field has evolved, organizational factors such as teaching status, ownership model, nurse staffing levels, and hospital volume have been found to be associated with performance on quality measures.1, 3‐7 Hospitalists represent a more recent change in the organization of inpatient care8 that may impact hospital‐level performance. In fact, most hospitals provide financial support to hospitalists, not only for hopes of improving efficiency, but also for improving quality and safety.9

Only a few single‐site studies have examined the impact of hospitalists on quality of care for common medical conditions (ie, pneumonia, congestive heart failure, and acute myocardial infarction), and each has focused on patient‐level effects. Rifkin et al.10, 11 did not find differences between hospitalists' and nonhospitalists' patients in terms of pneumonia process measures. Roytman et al.12 found hospitalists more frequently prescribed afterload‐reducing agents for congestive heart failure (CHF), but other studies have shown no differences in care quality for heart failure.13, 14 Importantly, no studies have examined the role of hospitalists in the care of patients with acute myocardial infarction (AMI). In addition, studies have not addressed the effect of hospitalists at the hospital level to understand whether hospitalists have broader system‐level effects reflected by overall hospital performance.

We hypothesized that the presence of hospitalists within a hospital would be associated with improvements in hospital‐level adherence to publicly reported quality process measures, and having a greater percentage of patients admitted by hospitalists would be associated with improved performance. To test these hypotheses, we linked data from a statewide census of hospitalists with data collected as part of a hospital quality‐reporting initiative.

Materials and Methods

Results

Discussion

In this cross‐sectional analysis of hospitals participating in a voluntary quality reporting initiative, hospitals with at least 1 hospitalist group had fewer missed discharge care process measures for CHF, even after adjusting for hospital‐level characteristics. In addition, as the estimated percentage of patients admitted by hospitalists increased, the percentage of missed quality opportunities decreased across all measures. The observed relationships were most apparent for measures that could be completed at any time during the hospitalization and at discharge. While it is likely that hospitalists are a marker of a hospital's ability to invest in systems (and as a result, care improvement initiatives), the presence of a potential dose‐response relationship suggests that hospitalists themselves may have a role in improving processes of care.

Our study suggests a generally positive, but mixed, picture of hospitalists' effects on quality process measure performance. Lack of uniformity across measures may depend on the timing of the process measure (eg, whether or not the process is measured at admission or discharge). For example, in contrast to admission process measures, we more commonly observed a positive association between hospitalists and care quality on process measures targeting processes that generally took place later in hospitalization or at discharge. Many admission process measures (eg, door to antibiotic time, blood cultures, and appropriate initial antibiotics) likely occurred prior to hospitalist involvement in most cases and were instead under the direction of emergency medicine physicians. Performance on these measures would not be expected to relate to use of hospitalists, and that is what we observed.

In addition to the timing of when a process was measured or took place, associations between hospitalists and care quality vary by disease. The apparent variation in impact of hospitalists by disease (more impact for cardiac conditions, less for pneumonia) may relate primarily to the characteristics of the processes of care that were measured for each condition. For example, one‐half of the pneumonia process measures related to care occurring within a few hours of admission, while the other one‐half (smoking cessation advice and streptococcal and influenza vaccines) were often administered per protocol or by nonphysician providers.26‐29 However, more of the cardiac measures required physician action (eg, prescription of an ACE‐I at discharge). Alternatively, unmeasured confounders important in the delivery of cardiac care might play an important role in the relationship between hospitalists and cardiac process measure performance.

Our approach to defining hospitalists bears mention as well. While a dichotomous measure of having hospitalists available was only statistically significant for the single CHF discharge composite measure, our measure of hospitalist availabilitythe percentage of patients admitted by hospitalistswas more strongly associated with a larger number of quality measures. Contrast between the dichotomous and continuous measures may have statistical explanations (the power to see differences between 2 groups is more limited with use of a binary predictor, which itself can be subject to bias),30 but may also indicate a dose‐response relationship. A larger number of admissions to hospitalists may help standardize practices, as care is concentrated in a smaller number of physicians' hands. Moreover, larger hospitalist programs may be more likely to have implemented care standardization or quality improvement processes or to have been incorporated into (or lead) hospitals' quality infrastructures. Finally, presence of larger hospitalist groups may be a marker for a hospital's capacity to make hospital‐wide investments in improvement. However, the association between the percentage of patients admitted by hospitalists and care quality persisted even after adjustment for many measures plausibly associated with ability to invest in care quality.

Our study has several limitations. First, although we used a widely accepted definition of hospitalists endorsed by the Society of Hospital Medicine, there are no gold standard definitions for a hospitalist's job description or skill set. As a result, it is possible that a model utilizing rotating internists (from a multispecialty group) might have been misidentified as a hospitalist model. Second, our findings represent a convenience sample of hospitals in a voluntary reporting initiative (CHART) and may not be applicable to hospitals that are less able to participate in such an endeavor. CHART hospitals are recognized to be better performers than the overall California population of hospitals, potentially decreasing variability in our quality of care measures.2 Third, there were significant differences between our comparison groups within the CHART hospitals, including sample size. Although we attempted to adjust our analyses for many important potential confounders and applied conservative measures to assess statistical significance, given the baseline differences, we cannot rule out the possibility of residual confounding by unmeasured factors. Fourth, as described above, this observational study cannot provide robust evidence to support conclusions regarding causality. Fifth, the estimation of the percent of patients admitted by hospitalists is unvalidated and based upon self‐reported and incomplete (41% of respondents) data. We are somewhat reassured by the fact that respondents and nonresponders were similar across all hospital characteristics, as well as outcomes. Sixth, misclassification of the estimated percentage of patients admitted by hospitalists may have influenced our results. Although possible, misclassification often biases results toward the null, potentially weakening any observed association. Given that our respondents were not aware of our hypotheses, there is no reason to expect recall issues to bias the results one way or the other. Finally, for many performance measures, overall performance was excellent among all hospitals (eg, aspirin at admission) with limited variability, thus limiting the ability to assess for differences.

In summary, in a large, cross‐sectional study of California hospitals participating in a voluntary quality reporting initiative, the presence of hospitalists was associated with modest improvements in hospital‐level performance of quality process measures. In addition, we found a relationship between the percentage of patients admitted by hospitalists and improved process measure adherence. Although we cannot determine causality, our data support the hypothesis that dedicated hospital physicians can positively affect the quality of care. Future research should examine this relationship in other settings and should address causality using broader measures of quality including both processes and outcomes.

Quality of care in US hospitals is inconsistent and often below accepted standards.1 This observation has catalyzed a number of performance measurement initiatives intended to publicize gaps and spur quality improvement.2 As the field has evolved, organizational factors such as teaching status, ownership model, nurse staffing levels, and hospital volume have been found to be associated with performance on quality measures.1, 3‐7 Hospitalists represent a more recent change in the organization of inpatient care8 that may impact hospital‐level performance. In fact, most hospitals provide financial support to hospitalists, not only for hopes of improving efficiency, but also for improving quality and safety.9

Only a few single‐site studies have examined the impact of hospitalists on quality of care for common medical conditions (ie, pneumonia, congestive heart failure, and acute myocardial infarction), and each has focused on patient‐level effects. Rifkin et al.10, 11 did not find differences between hospitalists' and nonhospitalists' patients in terms of pneumonia process measures. Roytman et al.12 found hospitalists more frequently prescribed afterload‐reducing agents for congestive heart failure (CHF), but other studies have shown no differences in care quality for heart failure.13, 14 Importantly, no studies have examined the role of hospitalists in the care of patients with acute myocardial infarction (AMI). In addition, studies have not addressed the effect of hospitalists at the hospital level to understand whether hospitalists have broader system‐level effects reflected by overall hospital performance.

We hypothesized that the presence of hospitalists within a hospital would be associated with improvements in hospital‐level adherence to publicly reported quality process measures, and having a greater percentage of patients admitted by hospitalists would be associated with improved performance. To test these hypotheses, we linked data from a statewide census of hospitalists with data collected as part of a hospital quality‐reporting initiative.

Materials and Methods

Results

Discussion

In this cross‐sectional analysis of hospitals participating in a voluntary quality reporting initiative, hospitals with at least 1 hospitalist group had fewer missed discharge care process measures for CHF, even after adjusting for hospital‐level characteristics. In addition, as the estimated percentage of patients admitted by hospitalists increased, the percentage of missed quality opportunities decreased across all measures. The observed relationships were most apparent for measures that could be completed at any time during the hospitalization and at discharge. While it is likely that hospitalists are a marker of a hospital's ability to invest in systems (and as a result, care improvement initiatives), the presence of a potential dose‐response relationship suggests that hospitalists themselves may have a role in improving processes of care.

Our study suggests a generally positive, but mixed, picture of hospitalists' effects on quality process measure performance. Lack of uniformity across measures may depend on the timing of the process measure (eg, whether or not the process is measured at admission or discharge). For example, in contrast to admission process measures, we more commonly observed a positive association between hospitalists and care quality on process measures targeting processes that generally took place later in hospitalization or at discharge. Many admission process measures (eg, door to antibiotic time, blood cultures, and appropriate initial antibiotics) likely occurred prior to hospitalist involvement in most cases and were instead under the direction of emergency medicine physicians. Performance on these measures would not be expected to relate to use of hospitalists, and that is what we observed.

In addition to the timing of when a process was measured or took place, associations between hospitalists and care quality vary by disease. The apparent variation in impact of hospitalists by disease (more impact for cardiac conditions, less for pneumonia) may relate primarily to the characteristics of the processes of care that were measured for each condition. For example, one‐half of the pneumonia process measures related to care occurring within a few hours of admission, while the other one‐half (smoking cessation advice and streptococcal and influenza vaccines) were often administered per protocol or by nonphysician providers.26‐29 However, more of the cardiac measures required physician action (eg, prescription of an ACE‐I at discharge). Alternatively, unmeasured confounders important in the delivery of cardiac care might play an important role in the relationship between hospitalists and cardiac process measure performance.

Our approach to defining hospitalists bears mention as well. While a dichotomous measure of having hospitalists available was only statistically significant for the single CHF discharge composite measure, our measure of hospitalist availabilitythe percentage of patients admitted by hospitalistswas more strongly associated with a larger number of quality measures. Contrast between the dichotomous and continuous measures may have statistical explanations (the power to see differences between 2 groups is more limited with use of a binary predictor, which itself can be subject to bias),30 but may also indicate a dose‐response relationship. A larger number of admissions to hospitalists may help standardize practices, as care is concentrated in a smaller number of physicians' hands. Moreover, larger hospitalist programs may be more likely to have implemented care standardization or quality improvement processes or to have been incorporated into (or lead) hospitals' quality infrastructures. Finally, presence of larger hospitalist groups may be a marker for a hospital's capacity to make hospital‐wide investments in improvement. However, the association between the percentage of patients admitted by hospitalists and care quality persisted even after adjustment for many measures plausibly associated with ability to invest in care quality.

Our study has several limitations. First, although we used a widely accepted definition of hospitalists endorsed by the Society of Hospital Medicine, there are no gold standard definitions for a hospitalist's job description or skill set. As a result, it is possible that a model utilizing rotating internists (from a multispecialty group) might have been misidentified as a hospitalist model. Second, our findings represent a convenience sample of hospitals in a voluntary reporting initiative (CHART) and may not be applicable to hospitals that are less able to participate in such an endeavor. CHART hospitals are recognized to be better performers than the overall California population of hospitals, potentially decreasing variability in our quality of care measures.2 Third, there were significant differences between our comparison groups within the CHART hospitals, including sample size. Although we attempted to adjust our analyses for many important potential confounders and applied conservative measures to assess statistical significance, given the baseline differences, we cannot rule out the possibility of residual confounding by unmeasured factors. Fourth, as described above, this observational study cannot provide robust evidence to support conclusions regarding causality. Fifth, the estimation of the percent of patients admitted by hospitalists is unvalidated and based upon self‐reported and incomplete (41% of respondents) data. We are somewhat reassured by the fact that respondents and nonresponders were similar across all hospital characteristics, as well as outcomes. Sixth, misclassification of the estimated percentage of patients admitted by hospitalists may have influenced our results. Although possible, misclassification often biases results toward the null, potentially weakening any observed association. Given that our respondents were not aware of our hypotheses, there is no reason to expect recall issues to bias the results one way or the other. Finally, for many performance measures, overall performance was excellent among all hospitals (eg, aspirin at admission) with limited variability, thus limiting the ability to assess for differences.

In summary, in a large, cross‐sectional study of California hospitals participating in a voluntary quality reporting initiative, the presence of hospitalists was associated with modest improvements in hospital‐level performance of quality process measures. In addition, we found a relationship between the percentage of patients admitted by hospitalists and improved process measure adherence. Although we cannot determine causality, our data support the hypothesis that dedicated hospital physicians can positively affect the quality of care. Future research should examine this relationship in other settings and should address causality using broader measures of quality including both processes and outcomes.

Quality of care in US hospitals is inconsistent and often below accepted standards.1 This observation has catalyzed a number of performance measurement initiatives intended to publicize gaps and spur quality improvement.2 As the field has evolved, organizational factors such as teaching status, ownership model, nurse staffing levels, and hospital volume have been found to be associated with performance on quality measures.1, 3‐7 Hospitalists represent a more recent change in the organization of inpatient care8 that may impact hospital‐level performance. In fact, most hospitals provide financial support to hospitalists, not only for hopes of improving efficiency, but also for improving quality and safety.9

Only a few single‐site studies have examined the impact of hospitalists on quality of care for common medical conditions (ie, pneumonia, congestive heart failure, and acute myocardial infarction), and each has focused on patient‐level effects. Rifkin et al.10, 11 did not find differences between hospitalists' and nonhospitalists' patients in terms of pneumonia process measures. Roytman et al.12 found hospitalists more frequently prescribed afterload‐reducing agents for congestive heart failure (CHF), but other studies have shown no differences in care quality for heart failure.13, 14 Importantly, no studies have examined the role of hospitalists in the care of patients with acute myocardial infarction (AMI). In addition, studies have not addressed the effect of hospitalists at the hospital level to understand whether hospitalists have broader system‐level effects reflected by overall hospital performance.

We hypothesized that the presence of hospitalists within a hospital would be associated with improvements in hospital‐level adherence to publicly reported quality process measures, and having a greater percentage of patients admitted by hospitalists would be associated with improved performance. To test these hypotheses, we linked data from a statewide census of hospitalists with data collected as part of a hospital quality‐reporting initiative.

Materials and Methods

Results

Discussion

In this cross‐sectional analysis of hospitals participating in a voluntary quality reporting initiative, hospitals with at least 1 hospitalist group had fewer missed discharge care process measures for CHF, even after adjusting for hospital‐level characteristics. In addition, as the estimated percentage of patients admitted by hospitalists increased, the percentage of missed quality opportunities decreased across all measures. The observed relationships were most apparent for measures that could be completed at any time during the hospitalization and at discharge. While it is likely that hospitalists are a marker of a hospital's ability to invest in systems (and as a result, care improvement initiatives), the presence of a potential dose‐response relationship suggests that hospitalists themselves may have a role in improving processes of care.

Our study suggests a generally positive, but mixed, picture of hospitalists' effects on quality process measure performance. Lack of uniformity across measures may depend on the timing of the process measure (eg, whether or not the process is measured at admission or discharge). For example, in contrast to admission process measures, we more commonly observed a positive association between hospitalists and care quality on process measures targeting processes that generally took place later in hospitalization or at discharge. Many admission process measures (eg, door to antibiotic time, blood cultures, and appropriate initial antibiotics) likely occurred prior to hospitalist involvement in most cases and were instead under the direction of emergency medicine physicians. Performance on these measures would not be expected to relate to use of hospitalists, and that is what we observed.

In addition to the timing of when a process was measured or took place, associations between hospitalists and care quality vary by disease. The apparent variation in impact of hospitalists by disease (more impact for cardiac conditions, less for pneumonia) may relate primarily to the characteristics of the processes of care that were measured for each condition. For example, one‐half of the pneumonia process measures related to care occurring within a few hours of admission, while the other one‐half (smoking cessation advice and streptococcal and influenza vaccines) were often administered per protocol or by nonphysician providers.26‐29 However, more of the cardiac measures required physician action (eg, prescription of an ACE‐I at discharge). Alternatively, unmeasured confounders important in the delivery of cardiac care might play an important role in the relationship between hospitalists and cardiac process measure performance.

Our approach to defining hospitalists bears mention as well. While a dichotomous measure of having hospitalists available was only statistically significant for the single CHF discharge composite measure, our measure of hospitalist availabilitythe percentage of patients admitted by hospitalistswas more strongly associated with a larger number of quality measures. Contrast between the dichotomous and continuous measures may have statistical explanations (the power to see differences between 2 groups is more limited with use of a binary predictor, which itself can be subject to bias),30 but may also indicate a dose‐response relationship. A larger number of admissions to hospitalists may help standardize practices, as care is concentrated in a smaller number of physicians' hands. Moreover, larger hospitalist programs may be more likely to have implemented care standardization or quality improvement processes or to have been incorporated into (or lead) hospitals' quality infrastructures. Finally, presence of larger hospitalist groups may be a marker for a hospital's capacity to make hospital‐wide investments in improvement. However, the association between the percentage of patients admitted by hospitalists and care quality persisted even after adjustment for many measures plausibly associated with ability to invest in care quality.

Our study has several limitations. First, although we used a widely accepted definition of hospitalists endorsed by the Society of Hospital Medicine, there are no gold standard definitions for a hospitalist's job description or skill set. As a result, it is possible that a model utilizing rotating internists (from a multispecialty group) might have been misidentified as a hospitalist model. Second, our findings represent a convenience sample of hospitals in a voluntary reporting initiative (CHART) and may not be applicable to hospitals that are less able to participate in such an endeavor. CHART hospitals are recognized to be better performers than the overall California population of hospitals, potentially decreasing variability in our quality of care measures.2 Third, there were significant differences between our comparison groups within the CHART hospitals, including sample size. Although we attempted to adjust our analyses for many important potential confounders and applied conservative measures to assess statistical significance, given the baseline differences, we cannot rule out the possibility of residual confounding by unmeasured factors. Fourth, as described above, this observational study cannot provide robust evidence to support conclusions regarding causality. Fifth, the estimation of the percent of patients admitted by hospitalists is unvalidated and based upon self‐reported and incomplete (41% of respondents) data. We are somewhat reassured by the fact that respondents and nonresponders were similar across all hospital characteristics, as well as outcomes. Sixth, misclassification of the estimated percentage of patients admitted by hospitalists may have influenced our results. Although possible, misclassification often biases results toward the null, potentially weakening any observed association. Given that our respondents were not aware of our hypotheses, there is no reason to expect recall issues to bias the results one way or the other. Finally, for many performance measures, overall performance was excellent among all hospitals (eg, aspirin at admission) with limited variability, thus limiting the ability to assess for differences.

In summary, in a large, cross‐sectional study of California hospitals participating in a voluntary quality reporting initiative, the presence of hospitalists was associated with modest improvements in hospital‐level performance of quality process measures. In addition, we found a relationship between the percentage of patients admitted by hospitalists and improved process measure adherence. Although we cannot determine causality, our data support the hypothesis that dedicated hospital physicians can positively affect the quality of care. Future research should examine this relationship in other settings and should address causality using broader measures of quality including both processes and outcomes.