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From the Eastern Vascular Society

Class I obesity is paradoxically associated with decreased risk of postoperative stroke after carotid endarterectomy Rubie Sue Jackson, MD, MPH,a,b James H. Black III, MD,a Ying Wei Lum, MD,a Eric B. Schneider, PhD,c Julie A. Freischlag, MD,a Bruce A. Perler, MD,a and Christopher J. Abularrage, MD,a Baltimore, Md; and Washington, DC Introduction: Although obesity is a risk factor for vascular disease, previous studies have shown an obesity paradox with decreased mortality in obese patients undergoing vascular surgery. This study examined the relationship between body mass index (BMI) and outcomes after carotid endarterectomy (CEA). Methods: The 2005-2009 American College of Surgeons National Surgical Quality Improvement Program database was queried to evaluate 30-day outcomes after isolated CEA across National Institutes of Health-defined obesity classes. ␹2 analysis was used to assess the unadjusted relationship of BMI category to postoperative outcomes. The independent association of BMI with morbidity and mortality was assessed with multivariable logistic regression, adjusting for preoperative and operative characteristics. Results: In the cohort of 23,652 CEA, 1.8% of patients were underweight (BMI 40). The overall stroke and mortality rates were 1.4% and 0.6%, respectively. On univariable analysis, there were U-shaped relationships between death (P ⴝ .017) and stroke (P ⴝ .029), with the lowest incidence in overweight and class I obese patients. The incidence of surgical site infection (SSI) (P ⴝ .021) increased incrementally with increasing BMI. On multivariable analysis, class I obesity was the only variable associated with decreased risk of stroke (odds ratio [OR], 0.51; 95% confidence interval [CI], 0.31-0.83; P ⴝ .007). Independent risk factors for stroke were previous transient ischemic attack (OR, 1.97; P ⴝ .006), American Society of Anesthesiologists class 4 to 5 (OR, 1.62; P ⴝ .010), surgery performed by a nonvascular surgeon (OR, 1.85; P ⴝ .015), and hemiplegia (OR, 1.97; P ⴝ .018). There was also a trend, although not statistically significant, toward decreased mortality risk associated with class I obesity (OR, 0.53; 95% CI, .26-1.08; P ⴝ .080). Class II obesity was associated with an increased risk of SSI compared with normal weight (OR, 2.21; 95% CI, 1.01-4.82; P ⴝ .047). BMI category was not associated with the risk of myocardial infarction. Conclusions: An obesity paradox exists for stroke and mortality after CEA; for stroke, but not mortality, this protective association was independent of patient demographics and comorbidities. Obesity is not a contraindication to CEA, and surgeons may safely undertake CEA in obese patients when indicated. ( J Vasc Surg 2012;55:1306-12.)

Obesity has reached epidemic proportions in much of the developed world, with approximately 35% of United States citizens classified as overweight and 30% classified as obese.1 Obesity is an established risk factor for cardiovascular disease, including coronary disease, coronary death, congestive heart failure, and ischemic stroke,2,3 and accounts for as many as 7% to 13% of deaths in developed countries.4,5 Despite the well-established health risks associated with obesity, some research has pointed to the existence of an From the Division of Vascular Surgery and Endovascular Therapy, The Johns Hopkins Hospital, Baltimorea; the Department of Surgery, Georgetown University Hospital, Washington, DCb; and the Center for Surgical Trials and Outcomes Research, The Johns Hopkins Hospital, Baltimore.c Author conflict of interest: none. Presented at the Twenty-fifth Annual Meeting of the Eastern Vascular Society, Washington, DC, September 22-24, 2011. Reprint requests: Dr Christopher Abularrage, Division of Vascular Surgery and Endovascular Surgery, The Johns Hopkins Hospital, 600 N. Wolfe Street, Harvey 611, Baltimore, MD 21287 (e-mail: [email protected]). The editors and reviewers of this article have no relevant financial relationships to disclose per the JVS policy that requires reviewers to decline review of any manuscript for which they may have a competition of interest. 0741-5214/$36.00 Copyright © 2012 by the Society for Vascular Surgery. doi:10.1016/j.jvs.2011.11.135

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obesity paradox in surgery, with improved postoperative survival for overweight and obese patients, compared with normal-weight patients.6-10 A study of general surgery patients in the 2005-2006 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database showed that overweight and class II obese patients had lower adjusted 30-day mortality risk compared with normal-weight patients.6 Similarly, several large retrospective studies of cardiac and vascular surgery patients have demonstrated improved 30-day7,8 or long-term9,10 survival in overweight and/or obese patients compared with normal-weight patients. However, these studies have not distinguished among the various vascular surgery procedures. In particular, the association of body mass index (BMI) with outcomes after carotid endarterectomy (CEA) is not well understood. The purpose of this study was to examine the association of obesity with 30-day outcomes after CEA in the ACS NSQIP database. METHODS The Johns Hopkins Medicine Institutional Review Board approved this study.

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Table I. CPT and ICD-9 codes used to define study cohort CPT codes 35,301 35,390 ICD-9 codes 433.1 433.10 433.11 433.30 433.31

Thromboendarterectomy, including patch graft, if performed; carotid, vertebral, or subclavian, by neck incision Reoperation, carotid, thromboendarterectomy, more than 1 month after original operation Occlusion and stenosis of precerebral arteries: carotid artery Occlusion and stenosis of precerebral arteries: carotid artery, without mention of cerebral infarction Occlusion and stenosis of precerebral arteries: carotid artery, with mention of cerebral infarction Occlusion and stenosis of precerebral arteries: multiple and bilateral, without mention of cerebral infarction Occlusion and stenosis of precerebral arteries: multiple and bilateral, with mention of cerebral infarction

CPT, Current procedural technology; ICD-9, International Classification of Diseases, Ninth Edition.

Table II. Patient demographics, behaviors, operative characteristics, and preoperative laboratory values, compared across BMI categories

Demographics Female, % Black, % Age, mean (years) Behaviors Current smoker, % Current ethanol abuse, % Operative characteristics Emergency, % ASA class, % 1-2 3 4-5 General anesthesia, % Vascular surgeon, % Laboratory values Platelets ⬍150,000/mL, % White blood cells ⬎11,000 cells/mL, % Blood urea nitrogen ⬎40 mg/dL, % Hematocrit ⬍45%, %

Underweight (n ⫽ 428)

Normal weight (n ⫽ 6301)

Overweight (n ⫽ 9322)

Class I obese (n ⫽ 4997)

Class II obese (n ⫽ 1773)

Class III obese (n ⫽ 831)

P value

63.1 5.1 73.3

46.4 4.0 73.0

34.8 3.5 71.6

38.9 3.7 69.8

48.7 6.2 68.1

61.1 4.5 66.1

⬍.001 .001 ⬍.001

52.8 5.8

33.6 4.7

25.8 4.7

23.2 4.0

21.2 1.9

25.4 2.4

⬍.001 ⬍.001

1.6

0.9

1.4

1.1

0.9

1.1

.124 ⬍.001

9.3 74.3 16.4 84.6 94.9

10.5 78.4 11.0 83.2 95.1

11.3 77.8 10.9 83.0 95.4

8.6 79.2 12.2 83.6 94.1

7.0 79.5 13.5 85.4 95.3

3.9 77.7 18.4 86.6 95.0

.023 .026

5.9 7.1

7.7 6.9

7.4 5.8

7.7 7.0

7.0 6.6

6.3 9.3

.481 .001

3.8

3.8

3.3

4.4

4.9

7.2

⬍.001

8.7

8.2

12.0

12.3

10.8

7.8

⬍.001

ASA, American Society of Anesthesiology; BMI, body mass index.

Study cohort. This is a retrospective analysis of prospectively collected data in the ACS NSQIP database. The ACS NSQIP provides risk-adjusted surgical outcomes data to private sector surgical service administrators for the purposes of quality assessment and improvement. At each participating hospital, trained nurse reviewers prospectively collect preoperative, operative, and postoperative data from patients undergoing major surgical procedures, according to a uniform protocol.11 CEA procedures in the ACS NSQIP from 2005 to 2009 were included. CEA was defined by a combination of current procedural technology (CPT) code (35301 or 35390) and International Classification of Diseases, Ninth Edition (ICD-9) code (433.1, 433.10, 433.11, 433.30, or 433.31) (Table I). Any procedure for which height and/or weight information was not recorded, as well as CEAs performed with simultaneous coronary artery bypass graft (CABG; CPT 33510, 33511, 33512, 33513, 33514, 33515, 33516, 33517, 33518, 33519, 33521, 33522,

33523, 33530, 33533, 33534, 33535, 33536, 33542, or 33545) were excluded. Patients with ascites were also excluded, since BMI would be expected not to correlate with adiposity in these patients. Outcomes. Primary outcomes were death and stroke. Secondary outcomes were operative reintervention, myocardial infarction (MI), cardiac arrest, and surgical site infection (SSI). SSI was defined as superficial or deep SSI, organ/space SSI, or wound dehiscence. All other outcomes were predefined NSQIP binary outcome variables. Adjustment variables. BMI was defined, using preoperative weight and height measurements, as weight (kg)/height (m2), and was categorized as underweight (BMI ⬍18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0-29.9 kg/m2), class I obese (30.0-34.9 kg/m2), class II obese (35.0-39.9 kg/m2), or class III obese (ⱖ40.0 kg/m2).12 ACS NSQIP preoperative and operative characteristics used as adjustment variables are displayed in Tables

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Table III. Patient preoperative comorbidities, compared across BMI categories Underweight Normal weight (n ⫽ 428) (n ⫽ 6301) Transient ischemic attack, % Stroke without residual neurological deficit, % Stroke with residual neurological deficit, % Hemiplegia, % Central nervous system tumor, % Myocardial infarction, % Previous percutaneous coronary intervention, % Previous cardiac surgery, % Angina, % Treated hypertension, % Congestive heart failure, % Previous surgery for peripheral vascular disease, % Ventilator, % Chronic obstructive pulmonary disease, % Pneumonia, % Dyspnea, % with exercise at rest Acute renal failure, % Dialysis, % Esophageal varices, % Treated diabetes, % Oral medication Insulin Disseminated cancer, % Preoperative open/infected wound, % Steroid use, % Weight loss, % Systemic inflammatory response syndrome/sepsis, % Dependent, % Partially Totally

Overweight (n ⫽ 9322)

Class I obese (n ⫽ 4997)

Class II obese (n ⫽ 1773)

Class III obese (n ⫽ 831)

P value

21.1 8.9

26.3 8.6

27.6 8.5

27.2 8.4

26.1 8.8

26.6 7.7

.173 .950

16.6

13.3

12.3

12.5

11.6

13.7

.030

7.9 0 1.4 14.5

5.3 0.1 1.3 15.3

4.3 ⬍0.1 1.5 18.8

4.5 0.1 1.4 20.9

3.6 0 1.5 22.9

3.5 0 1.4 24.1

⬍.001 .376 .924 ⬍.001

14.3 3.0 79.7 1.2 13.1

20.2 1.8 81.9 0.7 11.0

24.4 2.2 85.2 0.6 8.6

25.9 2.6 88.4 1.1 9.2

27.0 4.3 89.4 1.2 9.0

21.8 3.6 90.6 1.2 8.7

⬍.001 ⬍.001 ⬍.001 .003 ⬍.001

0 22.2

⬍0.1 11.0

⬍0.1 8.9

0 9.9

0 10.9

0 13.0

.746 ⬍.001

0.5 19.6 1.4 0 1.4 0

0.2 15.7 1.2 0.2 1.2 ⬍0.1

0.1 15.5 1.0 0.2 0.8 0.1

0.1 20.6 1.1 0.3 0.9 ⬍0.1

0 25.8 1.6 0.2 0.7 0

0.1 31.7 1.8 0.4 0.7 0

.013 ⬍.001

7.2 3.5 0.2 2.6

12.6 4.6 0.3 1.5

17.8 6.9 0.2 1.1

23.4 12.6 0.2 1.2

26.3 20.4 0 1.2

28.6 24.6 0 2.1

⬍.001

2.6 3.7 1.6

2.4 1.0 0.6

2.0 0.3 0.4

1.8 0.3 0.7

1.4 0.3 1.3

1.6 0.2 0.7

.057 ⬍.001 ⬍.001

9.8 0.5

5.0 0.4

3.4 0.2

3.3 0.3

4.7 0.2

4.8 0.1

⬍.001

.631 .161 .792

.200 .011

BMI, Body mass index. P values for the ␹2 statistic are displayed.

II and III. The ACS NSQIP defines current smoking as smoking within 1 year prior to surgery. Current ethanol abuse is defined as consumption of two or more drinks daily during the 2 weeks preceding surgery. Diabetes and hypertension are defined by use of medication to treat these conditions.13 Statistical analysis. Analysis of variance was used to compare means of continuous variables across BMI categories. The ␹2 statistic was used to compare binary and categorical baseline characteristics and unadjusted incidence proportions across BMI categories. Multivariable logistic regression was used to assess the adjusted association of BMI category with each study outcome. All baseline characteristics were considered, and backwards stepwise regression, using an exit criterion of P ⬎ .1, was used to select variables for final model inclusion. BMI categories and baseline characteristics that were significantly associated with BMI category (Tables II and III) were forced into the models. To assess multicollinearity, weighted regres-

sion was used to calculate variance inflation factors (VIFs) and tolerances. Multicollinearity was defined as VIF ⬎2 or tolerance ⬍0.50, and model reduction was attempted for any variable showing evidence of multicollinearity. P values ⱕ.05 were considered statistically significant. RESULTS During the study period, 24,002 CEA procedures were identified. After excluding 322 procedures for unrecorded height and/or weight, 17 procedures for simultaneous CABG, and 11 procedures for ascites, 23,652 procedures were included in the analysis. Of these, 1.8% were underweight, 26.6% were normal weight, 39.4% were overweight, 21.1% were class I obese, 7.5% were class II obese, and 3.5% were class III obese. Baseline characteristics are displayed in Tables II and III. The majority of underweight and class III obese patients were female, and the majority of patients in other

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P=0.017

C 3

2.5

2.5

2 1.5

2 1.5

1

1

0.5

0.5

0

0

B 3.76

D

P=0.029

3

P=0.021

3

2.5

Incidence, %

Incidence, %

P=0.053

3

Incidencee, %

Incidencce, %

A

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2 1.5 1

25 2.5 2 1.5 1

0.5

0.5

0

0

Fig. Incidence (95% confidence interval [CI]) of mortality (A), stroke (B), cardiac arrest (C), and surgical site infection (D) by body mass index (BMI) category. P values for the ␹2 statistic, testing for a difference in incidence across BMI categories, are shown.

BMI categories were male. Overall, 3.9% of patients were black, with the lowest proportion of black patients in the overweight and class I obese categories. History of transient ischemic attack and stroke without residual neurological deficit were similar across BMI categories. History of stroke with residual neurological deficit, American Society of Anesthesiologists class 4-5, congestive heart failure, chronic obstructive pulmonary disease, dyspnea, preoperative open/infected wound, and dependent functional status each had “U”-shaped distributions, with the highest prevalence in the underweight and class III obese categories. History of percutaneous coronary intervention, treated hypertension, and diabetes increased with increasing BMI category. Mean age and the prevalence of current smoking, current ethanol abuse, hemiplegia, and history of surgery for peripheral vascular disease decreased with increasing BMI category. A history of cardiac surgery was most common among classes I and II obese patients. Weight loss was most common among underweight patients.

The overall mortality rate was 0.6%. Postoperative stroke occurred in 1.4%, operative reintervention in 4.8%, cardiac arrest in 0.3%, MI in 0.6%, and SSI in 0.6% of cases. On unadjusted analysis, the incidences of death (P ⫽ .017), stroke (P ⫽ .029), and SSI (P ⫽ .021) differed significantly across BMI categories, and there was a nonsignificant trend toward an association between BMI category and cardiac arrest (P ⫽ .053; Fig). Death and stroke had U-shaped distributions, with the highest incidence in the extremes of weight and the lowest incidence in overweight and class I obese patients. In contrast, the incidence of SSI and cardiac arrest increased incrementally with increasing BMI category. On multivariable analysis (Tables IV and V), class I obesity was associated with a 50% reduction in the risk of stroke (P ⫽ .007), compared with normal weight. American Society of Anesthesiologists class 4-5 (P ⫽ .010), surgery performed by a nonvascular surgeon (P ⫽ .015), previous transient ischemic attack (P ⫽ .006), and hemiplegia (P ⫽ .018) were each significantly associated with

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Table IV. Multivariable analysis of primary outcomes

BMI category Underweight Normal weight Overweight Class I obese Class II obese Class III obese Age, 5-year increase American Society of Anesthesiologists class 3 4-5 Nonvascular surgeon Blood urea nitrogen ⬎40 mg/dL Transient ischemic attack Hemiplegia Previous myocardial infarction Previous surgery for peripheral vascular disease Chronic obstructive pulmonary disease Dyspnea at rest Disseminated cancer Partially dependent status

Death OR (95% CI)

Stroke OR (95% CI)

0.31 (0.04-2.43) Reference 0.78 (0.46-1.30) 0.53 (0.26-1.08) 0.95 (0.41-2.23) 1.65 (0.67-4.10) 1.18 (1.03-1.35)b

1.37 (0.61-3.07) Reference 0.90 (0.63-1.27) 0.51 (0.31-0.83)a 1.28 (0.75-2.19) 1.16 (0.57-2.35)

Reference 2.14 (1.32-3.46)a

Reference 1.62 (1.12-2.35)b 1.85 (1.12-2.35)b

2.60 (1.34-5.03)a 1.51 (1.13-2.03)a 1.97 (1.12-3.45)b 3.27 (1.37-7.81)a 1.78 (1.02-3.09)b 2.22 (1.31-3.75)a 2.98 (1.19-7.43)b 8.28 (1.75-39.28)a 2.91 (1.63-5.20)c

BMI, Body mass index; CI, confidence interval; OR, odds ratio. OR (95% CI) associated with BMI categories and with statistically significant variables included in the final model. a P ⱕ .01. b P ⱕ .05. c P ⱕ .001.

increased risk of stroke. Class I obesity was also associated with a nonsignificant trend toward decreased risk of mortality (P ⫽ .080). In contrast, class II obesity was associated with a twofold increase in the risk of SSI (P ⫽ .047), and class III obesity was also associated with a strong trend toward increased risk of SSI (P ⫽ .055), compared with normal weight. Increasing age was associated with decreasing risk of SSI (P ⫽ .010). Class III obesity was also associated with a trend toward increased risk of cardiac arrest (P ⫽ .104), compared with normal weight. BMI was not significantly associated with operative reintervention or MI on univariable or multivariable analysis. DISCUSSION Although obesity is a risk factor for development of cerebrovascular disease,3 the present study found evidence of a paradoxical reduction in the risk of stroke and death among class I obese patients after CEA. Compared with normal-weight patients, class I obese patients had a significantly reduced risk of stroke on both univariable and

multivariable analysis. Class I obese patients had a significantly reduced risk of death on univariable analysis, with a trend toward decreased risk of death on multivariable analysis. In contrast, class II obesity was associated with an increase in the risk of SSI, and class III obesity had a trend-level association with increased risk of cardiac arrest compared with normal weight. Although several reports have demonstrated an obesity paradox for perioperative mortality,6-10 to the authors’ knowledge, the present finding of an obesity paradox for perioperative stroke has not been reported previously. However, Vemmos and colleagues recently reported an analogous finding from a large prospective cohort study of patients hospitalized after a first stroke.14 The authors found that obesity and overweight were associated with reduced short-term (1-week) and long-term (10-year) mortality. Furthermore, obese patients were less likely than normal-weight or overweight patients to die during the acute poststroke phase from severe neurological damage, or to die subsequently from recurrent strokes. These data suggest a possible neuroprotective effect of obesity in patients having sustained a cerebrovascular insult, a result analogous to the present study’s finding of decreased risk of post-CEA stroke in class I obese patients. The U-shaped relationship between BMI and postoperative mortality parallels, and is probably attributable to, the U-shaped relationship between BMI and postoperative stroke. The fact that the protective relationship between class I obesity and mortality did not reach statistical significance on multivariable analysis may be due to the low overall mortality rate (0.65%, less than half the overall stroke rate), which reduced the power to detect a statistically significant difference in mortality risk across BMI categories. The paradoxical relationship between obesity and the risk of postoperative stroke and death may be attributable to the actions of endocrine factors released from adipose tissue. Adipose tissue, in addition to its role in energy storage, functions as an endocrine organ, influencing a range of metabolic and inflammatory processes through the secretion of factors collectively known as adipokines. In particular, the adipokine adiponectin has been linked to the obesity paradox. Elevated BMI is associated with decreased levels of adiponectin, and decreased adiponectin levels are associated with incident cardiovascular disease and mortality in healthy patients.15,16 Paradoxically, however, decreased adiponectin levels are associated with reduced risk of cardiovascular mortality after stroke,17 heart failure,18 and coronary events.19 Furthermore, a recent prospective cohort study found that, although obesity was associated with prolonged survival after CABG, adjustment for adiponectin levels abolished this effect.20 This suggests that adiponectin could mediate the paradoxical association between obesity and postoperative mortality and stroke. In contrast to the U-shaped pattern seen with stroke and mortality, increasing BMI was associated with incremental increases in the incidence of cardiac arrest, and there was a strong trend toward increased adjusted risk of cardiac arrest in class III obese patients. Obesity is a risk factor for

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Table V. Multivariable analysis of secondary outcomes Myocardial infarction OR (95% CI) BMI category Underweight Normal weight Overweight Class I obese Class II obese Class III obese Age, 5-year increase ASA class 3 4-5 Angina Dyspnea on exertion Dialysis Preoperative wound infection Systemic inflammatory response syndrome/sepsis Functional status partially dependent

1.01 (0.23-4.47) Reference 1.21 (0.72-2.05) 0.72 (0.36-1.46) 0.58 (0.19-1.75) 0.59 (0.13-2.62) 1.26 (1.10-1.46)c

2.95 (1.31-6.68)d 1.66 (1.00-2.74)b 3.31 (1.03-10.65)b

Cardiac arrest OR (95% CI)

Surgical site infection OR (95% CI)

Undefineda Reference 1.18 (0.48-2.89) 1.24 (0.44-3.49) 1.65 (0.49-5.57) 2.87 (0.80-10.27)

0.95 (0.12-7.22) Reference 1.25 (0.69-2.26) 1.49 (0.78-2.86) 2.21 (1.01-4.82)b 2.49 (1.01-4.82)b 0.85 (0.76-0.96)b

Reference 2.70 (1.31-5.57)d 2.90 (1.02-8.22)b 3.98 (1.18-13.35)b

4.86 (1.41-16.81)b 2.54 (1.03-6.27)b

ASA, American Society of Anesthesiology; BMI, body mass index; CI, confidence interval; OR, odds ratio. OR (95% CI) associated with BMI classes and statistically significant variables included in the final model. a OR not estimable in multivariable model. b P ⱕ .05. c P ⱕ .001. d P ⱕ .01.

coronary artery disease21 and is also independently associated with cardiac atrial and ventricular dysfunction.22 These factors probably underlie the association of severe obesity with postoperative cardiac arrest. Classes II and III obesity were each associated with a significant, or nearly significant, twofold increase in the risk of postoperative SSI. The association of obesity with increased risk of SSI has been recognized after multiple vascular surgery procedures.7,8,23-26 Although not a common complication after CEA, the finding of increased risk of SSI does highlight the importance of preventive measures, such as weight-based dosing of prophylactic antibiotics and prompt surgical drain removal, especially in obese patients. The major strength of this study was the use of the ACS NSQIP database, which provided a large sample size for analysis. Furthermore, ACS NSQIP data are prospectively collected using standard definitions, helping to minimize reporting bias. There are, however, limitations to this study due to the use of administrative data. The ACS NSQIP defines diabetes and hypertension by use of medication to treat these conditions; as a result, it was not possible to control for patients with untreated diabetes or hypertension. It is likely, however, that the majority of patients with these diagnoses were pharmacologically treated for these conditions perioperatively, in order to optimize postoperative management. Furthermore, it was not possible to account for variables that are not included in the ACS NSQIP, including medication use, type of hospital, hospital or surgeon case volume, bilateral repair, or repair technique. Inability to adjust for these variables may have influenced study results. Additionally, this analysis was lim-

ited to the use of BMI as the measurement of obesity, and it is possible that use of an alternative scale would alter the relationship between obesity and postoperative outcomes. Finally, the ACS NSQIP database does not discriminate between symptomatic and asymptomatic carotid occlusive disease. It is possible that carotid plaque morphology and the risk of embolism differs across the BMI classes. Although obesity is associated with the development of carotid artery disease, class I obesity is associated with decreased risk of stroke after CEA. Furthermore, this analysis found no evidence of elevated perioperative mortality risk among obese patients after CEA. These findings suggest that surgeons may safely undertake CEA in obese patients, when indicated. AUTHOR CONTRIBUTIONS Conception and design: CA, RJ Analysis and interpretation: RJ, CA, ES Data collection: RJ, ES Writing the article: RJ Critical revision of the article: CA, JB, YL, JF, BP Final approval of the article: CA Statistical analysis: RJ, ES Obtained funding: CA Overall responsibility: RJ REFERENCES 1. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA 2010;303:235-41. 2. Hubert HB, Feinleib M, McNamara PM, Castelli WP. Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham heart study. Circulation 1983;67:968-77.

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Submitted Sep 29, 2011; accepted Nov 25, 2011.