Advertisement

Surgical specialty and outcomes for carotid endarterectomy: evidence from the National Surgical Quality Improvement Program

Published:December 09, 2013DOI:https://doi.org/10.1016/j.jss.2013.11.1119

      Abstract

      Background

      Carotid endarterectomy (CEA) has been performed since the 1950s and remains one of the most common surgical procedures in the United States. The procedure is performed by cardiothoracic, general, neurologic, and vascular surgeons. This study uses data from the National Surgical Quality Improvement Program (NSQIP) to examine the outcomes after CEA when performed by general or vascular surgeons.

      Materials and methods

      Data included 34,493 CEAs from years 2005 to 2010 recorded in the NSQIP database. Primary outcomes measured were length of stay, 30-d mortality, surgical site infection, cerebrovascular accident, myocardial infarction, and blood transfusion requirement. Secondary outcomes measured were the remaining intraoperative outcomes from the NSQIP database.

      Results

      After controlling for patient and surgical characteristics, patients treated by general surgeons did not have a significantly different LOS or 30-d mortality than those treated by vascular surgeons. Patients of general surgeons had nearly twice the risk of acquiring a surgical site infection (odds ratio [OR] = 1.94; P = 0.012), >1.5 times the risk of cerebrovascular accident (OR = 1.56; P = 0.008), and >1.8 times the risk of blood transfusion (OR = 1.85; P = 0.017) than those of vascular surgeons. Patients of general surgeons had less than half the risk of having a myocardial infarction (OR = 0.34; P = 0.031) than those of vascular surgeons.

      Conclusions

      Surgical specialty is associated with a wide range of postoperative outcomes after CEA. Additional research is needed to explore practice and cultural differences across surgical specialty that may lead to outcome differences.

      Keywords

      1. Introduction

      In the United States, cerebrovascular disease accounts for nearly 130,000 deaths annually and is the fourth leading cause of death [
      • Murphy S.L.
      • Xu J.
      • Kochanek K.D.
      Deaths: preliminary data for 2010.
      ]. The large majority of strokes are ischemic in origin and as many of 20% of those are due to atherosclerotic disease of the carotid artery [
      • Howell G.M.
      • Makaroun M.S.
      • Chaer R.A.
      Current management of extracranial carotid occlusive disease.
      ]. Although there are various methods of treating carotid artery stenosis, carotid endarterectomy (CEA) is considered the standard of care and remains the most frequently performed surgical procedure to prevent stroke [
      • Boules T.N.
      • Proctor M.C.
      • Aref A.
      • et al.
      Carotid endarterectomy remains the standard of care, even in high-risk surgical patients.
      ,
      • Roger V.L.
      • Go A.S.
      • Lloyd-Jones D.M.
      • et al.
      Heart disease and stroke statistics—2011 update: a report from the American Heart Association.
      ]. CEA has been performed since the 1950s; however, since the publication of the North American Symptomatic Carotid Endarterectomy Trial [
      North American Symptomatic Carotid Endarterectomy Trial Collaborators
      Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis.
      ], the European Carotid Surgery Trial [
      Randomised trial of endarterectomy for recently symptomatic carotid stenosis: final results of the MRC European Carotid Surgery Trial (ECST).
      ], and the Asymptomatic Carotid Atherosclerosis Study [
      Endarterectomy for asymptomatic carotid artery stenosis. Executive Committee for the Asymptomatic Carotid Atherosclerosis Study.
      ] in the early 1990s, the number of procedures performed in the United States has markedly increased [
      • Roger V.L.
      • Go A.S.
      • Lloyd-Jones D.M.
      • et al.
      Heart disease and stroke statistics—2011 update: a report from the American Heart Association.
      ].
      Numerous reports on outcomes emphasizing perioperative mortality and stroke after CEA have been published. Studies have been conducted analyzing the effects of race, surgeon volume, hospital volume, shunting, intraoperative imaging, cerebral monitoring, as well as many other factors on CEA outcomes [
      • Bellosta R.
      • Luzzani L.
      • Carugati C.
      • et al.
      Routine shunting is a safe and reliable method of cerebral protection during carotid endarterectomy.
      ,
      • Feasby T.E.
      • Quan H.
      • Ghali W.A.
      Hospital and surgeon determinants of carotid endarterectomy outcomes.
      ,
      • Ruby S.T.
      • Robinson D.
      • Lynch J.T.
      • Mark H.
      Outcome analysis of carotid endarterectomy in Connecticut: the impact of volume and specialty.
      ,
      • Schneider E.B.
      • Black 3rd, J.H.
      • Hambridge H.L.
      • et al.
      The impact of race and ethnicity on the outcome of carotid interventions in the United States.
      ]. Investigations of the effect of surgical specialty on CEA outcomes have produced conflicting results. Some have reported no significant difference in effect of surgical specialty on outcomes [
      North American Symptomatic Carotid Endarterectomy Trial Collaborators
      Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis.
      ,
      • Ruby S.T.
      • Robinson D.
      • Lynch J.T.
      • Mark H.
      Outcome analysis of carotid endarterectomy in Connecticut: the impact of volume and specialty.
      ,
      • Kempczinski R.F.
      • Brott T.G.
      • Labutta R.J.
      The influence of surgical specialty and caseload on the results of carotid endarterectomy.
      ,
      • Brott T.
      • Thalinger K.
      The practice of carotid endarterectomy in a large metropolitan area.
      ] and others have demonstrated a significant effect of surgical specialty on outcomes for CEA [
      • Feasby T.E.
      • Quan H.
      • Ghali W.A.
      Hospital and surgeon determinants of carotid endarterectomy outcomes.
      ,
      • Hannan E.L.
      • Popp A.J.
      • Feustel P.
      • et al.
      Association of surgical specialty and processes of care with patient outcomes for carotid endarterectomy.
      ,
      • Hollenbeak C.S.
      • Bowman A.R.
      • Harbaugh R.E.
      • et al.
      The impact of surgical specialty on outcomes for carotid endarterectomy.
      ,
      • O'Neill L.
      • Lanska D.J.
      • Hartz A.
      Surgeon characteristics associated with mortality and morbidity following carotid endarterectomy.
      ]. Although Transient ischemic attack and stroke outcomes are included in some reports, there are many other outcomes associated with CEA that have not been as well studied. The purpose of this study was to examine the relationship between surgical specialty and outcomes from CEA using data from the American College of Surgeons private sector National Surgical Quality Improvement Program (NSQIP). This data set offers an opportunity to examine the effect of surgical specialty on a wide array of surgical outcomes, including hospital length of stay (LOS) and 30-d mortality, as well as surgical site infection (SSI), myocardial infarction (MI), cerebrovascular accident (CVA), blood transfusion requirement, and 11 other perioperative outcomes.

      2. Methods

      2.1 Data

      CEA was identified as a primary procedure using current procedure terminology code of 35301. Patients with additional procedures performed at the time of CEA were not excluded a priori, but by considering CEA only as a principal procedure, cases where CEA was performed secondarily to a major procedure, such as coronary artery bypass graft surgery, were excluded. This process identified 34,493 CEAs performed between the years 2005 and 2010 from all participating institutions. These cases represent only a fraction of the total CEAs performed during these years since NSQIP only samples cases at participating hospitals and is not all inclusive. [
      • Fink A.S.
      • Campbell Jr., D.A.
      • Mentzer Jr., R.M.
      • et al.
      The National Surgical Quality Improvement Program in non-veterans administration hospitals: initial demonstration of feasibility.
      ,
      • Khuri S.F.
      • Daley J.
      • Henderson W.
      • et al.
      The Department of Veterans Affairs' NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA Surgical Quality Improvement Program.
      ]. Most of these procedures were performed by vascular surgeons (N = 32,848) and general surgeons (N = 1,645). Analyses were stratified by these two surgical specialties.
      All patient characteristic and outcome data were taken from the NSQIP database collected using standard NSQIP methodology [
      • Fink A.S.
      • Campbell Jr., D.A.
      • Mentzer Jr., R.M.
      • et al.
      The National Surgical Quality Improvement Program in non-veterans administration hospitals: initial demonstration of feasibility.
      ,
      • Khuri S.F.
      • Daley J.
      • Henderson W.
      • et al.
      The Department of Veterans Affairs' NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA Surgical Quality Improvement Program.
      ]. Data were collected by a trained staff of surgical clinical nurse reviewers who worked in conjunction with the surgeon champion for accurate data collection. Uniformity was maintained through the use of an operation manual, which outlined data collection procedures and variable definitions, as well as routine conference calls, site visits, and annual meetings [
      • Boltz M.M.
      • Hollenbeak C.S.
      • Julian K.G.
      • et al.
      Hospital costs associated with surgical site infections in general and vascular surgery patients.
      ]. Surgeon specialty was assigned by the surgical clinical nurse reviewer using either the surgical service line most closely associated with the principal operative procedure or the surgeon's self-declared specialty [

      American College of Surgeons. (2013). ACS NSQIP Operations Manual: 26-27.

      ]. For CEA, if a surgeon was board certified in both vascular and general surgery, the surgeon was considered a vascular surgeon [

      American College of Surgeons. (2013). ACS NSQIP Operations Manual: 26-27.

      ].
      Of the 60 patient characteristics collected for the NSQIP database, variables that had the greatest relevance to the CEA procedure were selected. Preoperative characteristics included age, sex, race/ethnicity, anesthesia type, American Society of Anesthesiologists (ASA) class, operation time, and comorbidities (Table 1). Age was divided into quartiles including 20–64, 65–74, 75–79, and 80+ years. Similarly, operation time, recorded in minutes, was divided into quartiles including <84, 85–109, 110–139, and 140+. Race/ethnicity was stratified by white (non-Hispanic), black (non-Hispanic), Hispanic (including all Hispanic ethnicities), and other (including all other races recorded in the database: American Indian, Alaska Native, Asian, Pacific Islander, Native Hawaiian, or unknown race not of Hispanic origin). Anesthesia type was divided into four categories, the most common anesthesia type being general (N = 29,077), followed by regional (N = 3,709), then monitored (N = 1,372), then all the other types (N = 335), including spinal, epidural, other, and no anesthesia. Most patients were rated at an ASA class 3 (N = 26,801) or class 4 (N = 4,582), with very few rated at class 1 (N = 54) or class 5 (N = 12). For statistical analyses, ASA class was divided into two categories, “1, 2, and 3” and “4 and 5.” Comorbidities selected include diabetes, smoking, previous Percutaneous coronary intervention (PCI), previous previous cardiac surgery (PCS), hypertension requiring medication, and history of congestive heart failure (CHF), MI, angina, peripheral vascular disease (PVD), or CVA.
      Table 1Summary statistics of patients undergoing carotid endarterectomy stratified by surgeon specialty.
      VariableGeneral (N = 1,645)Vascular (N = 32,848)P value
      Age (y)71.371.10.440
       20–6422.7%24.3%
       65–7436.6%36.4%
       75–7919.9%18.4%
       80+20.7%20.8%
      Sex0.016
       Male56.3%59.3%
       Female43.7%40.7%
      Race/ethnicity<0.001
       White, non-Hispanic80.5%84.2%
       Black, non-Hispanic4.9%3.8%
       Hispanic5.3%3.0%
       Other3.2%1.3%
      Anesthesia<0.001
       General86.4%36.5%
       Regional5.5%31.3%
       Monitored6.3%19.3%
       Other1.8%9.6%
      ASA class0.031
       10.2%0.2%
       27.2%8.9%
       377.6%77.7%
       415.0%13.2%
       50.0%0.0%
      Operation time118.5116.50.106
       <8421.8%24.5%
       85–10926.7%25.9%
       110–13928.1%24.5%
       140+23.3%25.0%
      Comorbidities
       Diabetes28.0%27.9%0.911
       Smoker28.8%27.8%0.388
       Hx of CHF0.7%1.0%0.217
       Hx of MI1.5%1.5%0.876
       Hx of Angina1.8%2.7%0.040
       Hx of PVD8.5%9.7%0.102
       Previous PCI17.8%18.8%0.327
       Previous PCS22.9%22.8%0.933
       HT medication84.8%85.5%0.448
       CVA14.7%15.5%0.398
      Hx = History; HT = Hypertension.
      In addition to LOS, 30-d postoperative mortality, and any outcome variables, we selected four of NSQIP's 17 perioperative outcomes that were relevant to CEA: SSI, MI, CVA, and blood transfusion requirement. We also created two composite outcome variables. The first measured the incidence of any of the 17 intra- or postoperative outcomes of interest. These 17 outcomes included cardiac arrest, CVA, blood transfusion requirement, intubation lasting >48 h, failure of graft/prosthesis, wound dehiscence, three types of SSI, MI, venous thromboembolism, urinary tract infection, renal insufficiency, sepsis, pneumonia, septic shock, and acute renal failure. The second composite outcome variable measured the incidence of 30-d mortality, MI, or CVA. The SSI outcome included superficial SSI, deep incision SSI, and organ space SSI that occurred within 30 d of the procedure. Superficial SSI included infections that involved only the skin or subcutaneous tissue of the incision. Deep incision SSI included infection of the deep soft tissue (muscle and fascia) of the incision, whereas organ space SSI included infections of any of the organs or spaces unconnected to the incision but which were manipulated during the procedure. Patients with any one of these types of SSI were regarded as having an SSI in our analyses. The outcome of MI was recorded in the incidence of any new acute MI that occurred during the procedure or within 30 d postoperatively. The CVA outcome was recorded in the incidence of the patient's development of symptoms lasting for >24 h within 30 d postoperatively. Mortality was recorded as any death occurring during the procedure or within 30 d postoperatively. This was an institutional review board exempt study.

      2.2 Statistical analysis

      Statistical analysis was performed primarily to determine whether surgical specialty was significantly associated with outcomes after controlling for patient and surgical characteristics. The first statistical analysis performed was univariate analysis to determine whether there were differences in patient characteristics across surgeon specialty. This was done using t-tests for continuous variables and chi-square tests for binary and categorical variables. Patient outcomes were also compared across surgical specialty using t-tests and chi-square tests, without controlling for any patient characteristics.
      Logistic regression was then used to model the effect of surgical specialty on binary outcomes after controlling for patient and surgical characteristics. Areas under the receiver operating characteristic curves were calculated to assess model performance. Multivariate analysis of LOS was performed using a generalized linear regression model. This was done because LOS was highly skewed and clearly violated the normality assumption of classical linear regression. For the generalized linear model, we assumed a gamma family of distributions and a log link function. We report the marginal effects from the generalized linear models, which show the effect of a 1 unit change in the independent variable on the outcome. A deviance test was calculated to assess goodness-of-fit.
      If a significant imbalance in patient covariates existed between general and vascular surgeons, then a regression model may not adequately control for covariates. Therefore, a propensity score matching analysis that dealt with potential covariate imbalance was performed. The propensity score model was fit using a logistic regression model with general surgical specialty as the dependent variable and controlled for covariates as previously described. Predicted probability of treatment by a general surgeon (i.e., the propensity score) was then computed from the fitted regression model. Patients of general surgeons were matched 1:5 to patients of vascular surgeons. Patients were matched based on a k-nearest neighbor match with a max-min common support restriction.
      The primary metric for the propensity score analysis was the average effect of treatment on the treated (ATT). This is the difference between the outcome for a patient treated by a general surgeon and the outcome for a patient treated by a vascular surgeon. To deal with the uncertainty induced by both the selection process and the data, a standard bootstrapping algorithm was used to compute 95% confidence intervals. Reported inferences for the ATT are based on 50 bootstrap replicates. All statistical analyses were performed using STATA (version 12.1; StataCorp LLP, College Station, TX) and the psmatch2 routines [

      E Leuven, B Sianesi. (21 Dec 2012) PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. http://ideas.repec.org/c/boc/bocode/s432001.html. Accessed Oct 2012.

      ]. Statistical significance for all analyses was defined as a P value < 0.05.

      3. Results

      3.1 Patient characteristics

      There were 34,493 CEAs recorded in the NSQIP database between 2005 and 2010. Data from all participating institutions in the database were included. The Figure shows the number of CEAs recorded in the NSQIP database each year from 2005 to 2010, stratified according to surgical specialty. Most of the procedures were performed by vascular surgeons with an increasing number of procedures recorded up to 2009. Procedures performed by general surgeons also increased up to 2009.
      Figure thumbnail gr1
      FigNumber of carotid endarterectomies performed in the NSQIP stratified by surgical specialty, 2005–2010.
      Across the two surgical specialty strata, patient characteristics were similar in regard to age and most of the comorbidities, including diabetes, smoking, and previous PCI (Table 1). There were, however, some significant differences in patient characteristics across surgeon specialties. For example, general surgeons used significantly less general anesthesia and more regional, monitored, and other anesthesia as compared with vascular surgeons (P < 0.001). Other differences across specialty included gender, race/ethnicity, ASA classification, and history of angina.

      3.2 Patient outcomes

      Without controlling for patient characteristics, most of the postoperative outcomes were not significantly different across surgeon specialty (Table 2). Mortality, LOS, and patients with any postoperative outcome were all similar across surgical specialty. General surgeons had a higher rate of postoperative CVA than vascular surgeons (P = 0.011) as well as higher blood transfusion requirements (P = 0.018). There was also a significant difference in SSI between specialties (P = 0.017). Vascular surgeons had a higher rate of postoperative MI than general surgeons (P = 0.024).
      Table 2Summary of all NSQIP outcomes stratified by surgeon specialty.
      VariableGeneral (N = 1,645)Vascular (N = 32,848)P value
      Mortality1.1%0.7%0.113
      LOS (d)2.82.70.186
      Cardiac arrest requiring CPR0.4%0.3%0.718
      Cerebrovascular accident2.4%1.6%0.011
      Transfusion requirement1.0%0.6%0.018
      Intubated >48 h0.8%0.8%0.859
      Graft/prosthesis failure0.1%0.1%0.626
      Wound dehiscence0.0%0.1%0.254
      SSI1.0%0.5%0.017
      MI0.2%0.7%0.024
      Venous thromboembolism0.1%0.2%0.452
      Urinary tract infection0.9%0.8%0.552
      Renal insufficiency0.1%0.1%0.845
      Sepsis0.2%0.5%0.177
      Pneumonia0.9%0.9%0.974
      Septic shock0.1%0.2%0.331
      Acute renal failure with hemodialysis0.2%0.2%0.383
      Any outcome6.3%5.4%0.114
      Death, MI, or CVA3.4%2.8%<0.001
      CPR = Cardiopulmonary resuscitation.

      3.3 Length of stay

      After controlling for patient characteristics, there was still no significant difference in LOS between the surgeon specialties (Table 3). As would be expected, older age (75 years and older), higher ASA class (4 and 5), and all the statistically significant comorbidities resulted in a significant increase in LOS. The use of regional anesthesia was associated with a significantly shorter LOS (P < 0.001).
      Table 3Results of generalized linear model of effect of surgeon specialty on LOS, controlling for other covariates (deviance χ2 = 24,518, P < 0.001).
      VariableMarginal effect95% confidence intervalP value
      LowerUpper
      Surgical specialty
       VascularReference
       General0.09−0.080.270.302
      Age (y)
       20–64Reference
       65–74−0.03−0.130.060.490
       75–790.260.140.39<0.001
       80+0.720.580.86<0.001
      Sex
       FemaleReference
       Male−0.15−0.23−0.07<0.001
      Race/ethnicity
       White, non-HispanicReference
       Black, non-Hispanic1.190.911.46<0.001
       Hispanic0.910.621.20<0.001
       Other0.27−0.080.620.134
      Anesthesia
       GeneralReference
       Regional−0.28−0.39−0.17<0.001
       Monitored−0.10−0.280.090.303
       Other−0.20−0.540.150.265
      ASA class
       1, 2, and 3Reference
       4 and 51.471.311.63<0.001
      Operation time
       <84Reference
       85–1090.120.010.220.030
       110–1390.180.070.290.001
       140+0.720.600.84<0.001
      Comorbidities
       Diabetes0.230.140.32<0.001
       Smoker0.07−0.020.160.151
       Hx of CHF4.123.155.10<0.001
       Hx of MI1.681.162.19<0.001
       Hx of Angina1.861.462.27<0.001
       Hx of PVD0.290.150.43<0.001
       Previous PCI−0.09−0.180.000.061
       Previous PCS−0.08−0.170.010.067
       HT medication−0.09−0.200.020.117
       CVA1.471.321.62<0.001
      Hx = History; HT = Hypertension.

      3.4 Surgical site infection

      Patients treated by general surgeons were 1.94 times more likely to have a postoperative SSI relative to patients treated by vascular surgeons (P = 0.012, Table 4). Patient older than 64 years (65–74, 75–79, 80+ years), all had reduced incidence of SSI (P < 0.001, P = 0.040, P < 0.001, respectively). Neither history of MI, CVA, nor PVD had a significant effect on postoperative SSI.
      Table 4Results of logistic regression model of effect of surgeon specialty on SSI, controlling for other covariates (area under ROC curve = 0.65).
      VariableOdds ratio95% Confidence intervalP value
      LowerUpper
      Surgical specialty
       VascularReference
       General1.941.163.260.012
      Age (y)
       20–64Reference
       65–740.500.350.72<0.001
       75–790.520.340.810.004
       80+0.360.220.59<0.001
      Sex
       FemaleReference
       Male1.240.911.690.168
      Race/ethnicity
       White, non-HispanicReference
       Black, non-Hispanic0.830.391.790.639
       Hispanic1.420.722.800.312
       Other0.700.172.850.620
      Anesthesia
       GeneralReference
       Regional1.000.621.620.990
       Monitored0.560.211.530.258
       Other0.500.073.610.493
      ASA class
       1, 2, and 3Reference
       4 and 50.920.601.420.720
      Operation time
       <84Reference
       85–1091.180.771.820.444
       110–1390.940.591.480.780
       140+1.541.022.320.041
      Comorbidities
       Diabetes1.170.851.600.333
       Smoker0.980.711.370.928
       Hx of CHF1.510.464.950.493
       Hx of MI1.180.423.300.757
       Hx of angina1.070.462.490.870
       Hx of PVD1.280.831.990.263
       Previous PCI0.900.621.310.571
       Previous PCS1.380.991.920.055
       HT medication1.040.681.570.869
       CVA1.050.721.550.794
      bgfbbsb

      3.5 MI and CVA

      General surgery differed from vascular surgery in both the occurrence of postoperative MI and postoperative CVA. Compared with CEAs performed by vascular surgeons, those performed by general surgeons had a 66% reduced odds of resulting in a postoperative MI (P = 0.031, Table 5), but they had a 56% greater odds of resulting in a postoperative CVA (P = 0.008, Table 6). Patients older than 64 years had an increased incidence of postoperative MI, and patients aged 80 years or older had four times the incidence than those aged 20–64 years (P < 0.001). Patients who received regional anesthesia had less than half of the risk of postoperative MI than patients who received general anesthesia (P = 0.007). Age and anesthesia type had no significant effect on postoperative CVA; however, higher ASA class was associated with an increased risk of CVA (P = 0.007). Diabetes, smoking, history of MI, angina, PCI, and CVA all were associated with an increased likelihood of postoperative MI, whereas only history of angina and CVA were associated with an increased risk of postoperative CVA.
      Table 5Results of logistic regression model of effect of surgeon specialty on postoperative MI, controlling for other covariates (area under ROC curve = 0.71).
      VariableOdds ratio95% Confidence intervalP value
      LowerUpper
      Surgical specialty
       VascularReference
       General0.340.120.900.031
      Age (y)
       20–64Reference
       65–741.881.252.820.003
       75–791.771.092.880.022
       80+4.052.626.26<0.001
      Sex
       FemaleReference
       Male1.000.761.300.972
      Race/ethnicity
       White, non-HispanicReference
       Black, non-Hispanic1.080.582.010.805
       Hispanic0.920.431.970.826
       Other2.301.074.960.033
      Anesthesia
       GeneralReference
       Regional0.440.250.800.007
       Monitored0.500.211.230.132
       Other0.400.052.840.356
      ASA class
       1, 2, and 3Reference
       4 and 51.421.031.940.032
      Operation time
       <84Reference
       85–1090.880.601.300.527
       110–1390.890.601.320.560
       140+1.441.012.050.042
      Comorbidities
       Diabetes1.401.071.850.015
       Smoker1.461.072.000.017
       Hx of CHF0.670.241.890.446
       Hx of MI2.161.154.070.017
       Hx of angina2.881.794.63<0.001
       Hx of PVD1.430.982.070.061
       Previous PCI1.461.091.950.012
       Previous PCS1.260.941.680.122
       HT medication1.100.731.650.661
       CVA1.391.011.910.042
      Hx = History; HT = Hypertension.
      Table 6Results of logistic regression model of effect of surgeon specialty on postoperative CVA, controlling for other covariates (area under ROC curve = 0.63).
      VariableOdds ratio95% Confidence intervalP value
      LowerUpper
      Surgical specialty
       VascularReference
       General1.561.132.170.008
      Age (y)
       20–64Reference
       65–740.860.691.080.189
       75–790.890.681.170.407
       80+1.090.841.410.506
      Sex
       FemaleReference
       Male0.860.731.020.091
      Race/ethnicity
       White, non-HispanicReference
       Black, non-Hispanic1.200.831.740.342
       Hispanic1.070.681.690.761
       Other0.710.321.610.414
      Anesthesia
       GeneralReference
       Regional1.000.761.320.981
       Monitored0.900.571.420.661
       Other0.180.021.260.084
      ASA class
       1, 2, and 3Reference
       4 and 51.351.081.680.007
      Operation time
       <84Reference
       85–1091.010.801.280.929
       110–1390.800.621.030.087
       140+1.160.921.460.218
      Comorbidities
       Diabetes1.100.911.320.325
       Smoker1.070.871.300.528
       Hx of CHF0.800.371.750.581
       Hx of MI1.550.912.640.105
       Hx of angina1.751.172.630.006
       Hx of PVD1.210.931.570.165
       Previous PCI0.880.711.110.282
       Previous PCS1.000.821.230.972
       HT medication1.010.791.290.934
       CVA2.121.752.55<0.001
      Hx = History; HT = Hypertension.

      3.6 Blood transfusion requirement

      Patients treated by general surgeons were almost twice as likely to receive a blood transfusion than those patients treated by vascular surgeons (P = 0.017, Table 7). Patient age categories aged older than 64 years (65–74, 75–79, 80+ years), all had an increased risk of blood transfusion requirement, with patients older than 75 years at greater than twice the risk (P = 0.048, P = 0.001, P = 0.001, respectively). Diabetes and history of MI were associated with an increased risk of blood transfusion (P = 0.001 and P < 0.001, respectively), and a history of CHF was associated with over four times the risk of requiring a blood transfusion (P < 0.001).
      Table 7Results of logistic regression model of effect of surgeon specialty on transfusion requirement, controlling for other covariates (area under ROC curve = 0.77).
      VariableOdds ratio95% Confidence intervalP value
      LowerUpper
      Surgical specialty
       VascularReference
       General1.851.123.070.017
      Age (y)
       20–64Reference
       65–741.531.002.340.048
       75–792.181.363.470.001
       80+2.291.433.680.001
      Sex
       FemaleReference
       Male0.870.661.160.350
      Race/ethnicity
       White, non-HispanicReference
       Black, non-Hispanic1.170.642.130.601
       Hispanic0.600.251.490.274
       Other1.290.473.530.618
      Anesthesia
       GeneralReference
       Regional0.540.291.000.051
       Monitored0.680.281.680.403
       Other0.490.073.520.477
      ASA class
       1, 2, and 3Reference
       4 and 53.332.474.51<0.001
      Operation time
       <84Reference
       85–1091.270.811.990.296
       110–1391.140.721.800.585
       140+2.151.433.24<0.001
      Comorbidities
       Diabetes1.651.232.200.001
       Smoker1.310.941.820.115
       Hx of CHF4.202.467.19<0.001
       Hx of MI3.061.765.31<0.001
       Hx of angina1.420.802.510.226
       Hx of PVD1.370.912.050.127
       Previous PCI0.880.621.240.455
       Previous PCS0.830.591.150.260
       HT medication1.450.882.370.142
       CVA1.040.721.480.850
      Hx = History; HT = Hypertension.

      3.7 Mortality

      Of the 34,493 operations recorded in the database, 263 patients died within 30 d of their CEA. There were no significant differences found between surgical specialty and 30-d mortality, but several patient characteristics were associated with 30-d mortality. Patients who were aged >80 years had nearly three times greater odds of mortality than that of those from the age 20 to 64 years (P < 0.001). Patients rated as ASA class 4 or 5 had 2.4 times the odds of mortality compared with those patients rated 1, 2, or 3 (P < 0.001). History of CHF, MI, angina, PVD, and CVA all were significantly related to greater mortality. Anesthesia type had no significant association with mortality.

      3.8 Any outcome/complication

      After controlling for patient characteristics, the effect of surgical specialty on the composite outcome was not statistically significant. Smoking history, previous PCI or PCS, and use of hypertensive medications also did not have a significant effect on the aggregate outcome. The 80+ age category, black non-Hispanic race, and several comorbidities including diabetes, history of MI, angina, PVD, and CVA were all associated with an increased risk of a negative postoperative outcome compared with their respective reference groups. Patients with a history of CHF were more than three times more likely to have any negative postoperative outcome (P < 0.001). Regional and other anesthesia as well as male gender were associated with decreased odds of a negative postoperative outcome.

      3.9 Mortality, MI, and CVA

      Although there was a higher incidence of 30-d mortality, MI, and CVA in patients of general surgeons compared with vascular surgeons using univariate analysis, after controlling for patient characteristics, the effect of surgical specialty on the composite outcome was not statistically significant (P = 0.110, Table 8). Similar to the total composite outcome, the 80+ years age category, black non-Hispanic race, and several comorbidities including history of CHF, MI, angina, PVD, and CVA were all associated with an increased risk of a negative postoperative outcome compared with their respective reference groups. Not surprisingly, higher ASA class and longer operation times were also associated with increased odds of 30-d mortality, MI, and CVA.
      Table 8Results of logistic regression model of effect of surgeon specialty on composite outcome including 30-d mortality, postoperative MI, and postoperative CVA, controlling for other covariates (area under ROC curve = 0.65).
      VariableOdds ratio95% Confidence intervalP value
      LowerUpper
      Surgical specialty
       VascularReference
       General1.250.951.650.110
      Age (y)
       20–64Reference
       65–741.070.891.280.496
       75–791.180.951.460.135
       80+1.801.472.20<0.0001
      Sex
       FemaleReference
       Male0.860.750.980.024
      Race/ethnicity
       White, non-HispanicReference
       Black, non-Hispanic1.351.021.780.037
       White, non-Hispanic1.040.731.490.820
       Other0.880.491.570.657
      Anesthesia
       GeneralReference
       Regional0.840.671.060.136
       Monitored0.880.611.250.468
       Other0.510.211.230.133
      ASA class
       1, 2, and 3Reference
       4 and 51.591.361.87<0.0001
      Operation time
       <84Reference
       85–1090.980.811.180.804
       110–1390.840.691.030.088
       140+1.351.131.620.001
      Comorbidities
       Diabetes1.100.961.270.178
       Smoker1.150.981.340.083
       Hx of CHF1.651.082.510.020
       Hx of MI1.921.342.74<0.0001
       Hx of angina1.911.432.55<0.0001
       Hx of PVD1.411.161.71<0.0001
       Previous PCI1.050.891.230.579
       Previous PCS1.060.911.240.441
       HT medication1.070.881.300.494
       CVA1.881.622.18<0.0001
      Hx = History; HT = Hypertension.

      3.10 Propensity score matching

      Among propensity score matched groups, patients treated by general surgeons had a 6.3% risk of a negative postoperative outcome, as compared with a 4.6% risk incurred by patients treated by vascular surgeons (Table 9). This is a significant difference (ATT) of 1.8% (P = 0.021). In other propensity score matched groups, patients treated by general surgeons had a higher risk of longer LOS, SSI, CVA, blood transfusion requirement, mortality, and composite incidence of mortality, MI, and CVA than patients of vascular surgeons, but these differences were not significant. Patients treated by general surgeons had a lower risk of postoperative MI, but this was not significantly different than patients of vascular surgeons.
      Table 9Results of the propensity score analysis.
      VariableGeneralVascularATTP value
      LOS (d)2.82.70.20.209
      SSI1.0%0.4%0.6%0.056
      MI0.2%0.4%−0.2%0.331
      CVA2.4%1.6%0.8%0.083
      Transfusion requirement1.0%0.4%0.6%0.075
      Mortality1.1%0.7%0.4%0.219
      Any outcome6.3%4.6%1.8%0.021
      Mortality, MI, and CVA3.4%2.6%0.9%0.182

      4. Discussion

      CEA is one of the most commonly performed major surgical operations in the United States, and its postoperative outcomes have been well studied. Multiple patient and procedural variables have been shown to affect outcomes, as well as other factors such as hospital volume, surgeon volume, and surgical specialty [
      • Feasby T.E.
      • Quan H.
      • Ghali W.A.
      Hospital and surgeon determinants of carotid endarterectomy outcomes.
      ,
      • O'Neill L.
      • Lanska D.J.
      • Hartz A.
      Surgeon characteristics associated with mortality and morbidity following carotid endarterectomy.
      ,
      • Finks J.F.
      • Osborne N.H.
      • Birkmeyer J.D.
      Trends in hospital volume and operative mortality for high-risk surgery.
      ,
      • Goodney P.P.
      • Likosky D.S.
      • Cronenwett J.L.
      Factors associated with stroke or death after carotid endarterectomy in Northern New England.
      ,
      • Holt P.J.
      • Poloniecki J.D.
      • Loftus I.M.
      • Thompson M.M.
      The relationship between hospital case volume and outcome from carotid endartectomy in England from 2000 to 2005.
      ,
      • Holt P.J.
      • Poloniecki J.D.
      • Loftus I.M.
      • Thompson M.M.
      Meta-analysis and systematic review of the relationship between hospital volume and outcome following carotid endarterectomy.
      ,
      • Halm E.A.
      • Tuhrim S.
      • Wang J.J.
      • et al.
      Racial and ethnic disparities in outcomes and appropriateness of carotid endarterectomy: impact of patient and provider factors.
      ,
      • Harthun N.L.
      • Stukenborg G.J.
      Atrial fibrillation is associated with increased risk of perioperative stroke and death from carotid endarterectomy.
      ,
      • Killeen S.D.
      • Andrews E.J.
      • Redmond H.P.
      • Fulton G.J.
      Provider volume and outcomes for abdominal aortic aneurysm repair, carotid endarterectomy, and lower extremity revascularization procedures.
      ,
      • Waljee J.F.
      • Greenfield L.J.
      • Dimick J.B.
      • Birkmeyer J.D.
      Surgeon age and operative mortality in the United States.
      ,
      • Westvik H.H.
      • Westvik T.S.
      • Maloney S.P.
      • et al.
      Hospital-based factors predict outcome after carotid endarterectomy.
      ,
      • Harthun N.L.
      • Kongable G.L.
      • Baglioni A.J.
      • et al.
      Examination of sex as an independent risk factor for adverse events after carotid endarterectomy.
      ,
      • Cowan Jr., J.A.
      • Dimick J.B.
      • Thompson B.G.
      • et al.
      Surgeon volume as an indicator of outcomes after carotid endarterectomy: an effect independent of specialty practice and hospital volume.
      ,
      • Birkmeyer J.D.
      • Siewers A.E.
      • Finlayson E.V.
      • et al.
      Hospital volume and surgical mortality in the United States.
      ,
      • Pearce W.H.
      • Parker M.A.
      • Feinglass J.
      • et al.
      The importance of surgeon volume and training in outcomes for vascular surgical procedures.
      ,
      • Kucey D.S.
      • Bowyer B.
      • Iron K.
      • et al.
      Determinants of outcome after carotid endarterectomy.
      ,
      • Hannan E.L.
      • Popp A.J.
      • Tranmer B.
      • et al.
      Relationship between provider volume and mortality for carotid endarterectomies in New York state.
      ,
      • Cebul R.D.
      • Snow R.J.
      • Pine R.
      • et al.
      Indications, outcomes, and provider volumes for carotid endarterectomy.
      ,
      • Perler B.A.
      • Dardik A.
      • Burleyson G.P.
      • et al.
      Influence of age and hospital volume on the results of carotid endarterectomy: a statewide analysis of 9918 cases.
      ]. Significant differences in outcomes across surgical specialty have, however, been limited primarily to death, stroke, and combined death and stroke. Of those that showed significant differences, Feasby et al. [
      • Feasby T.E.
      • Quan H.
      • Ghali W.A.
      Hospital and surgeon determinants of carotid endarterectomy outcomes.
      ] reported that general surgeons had poorer mortality and stroke outcomes than neurosurgeons, vascular surgeons, and cardiothoracic surgeons. AbuRahma et al. [
      • AbuRahma A.F.
      • Stone P.A.
      • Srivastava M.
      • et al.
      The effect of surgeon's specialty and volume on the perioperative outcome of carotid endarterectomy.
      ] found that perioperative stroke rates were significantly higher for nonvascular surgeons, whereas O'Neill et al. [
      • O'Neill L.
      • Lanska D.J.
      • Hartz A.
      Surgeon characteristics associated with mortality and morbidity following carotid endarterectomy.
      ] showed that neurosurgeons had lower mortality rates than nonneurosurgeons. A study by Hannan et al. [
      • Hannan E.L.
      • Popp A.J.
      • Feustel P.
      • et al.
      Association of surgical specialty and processes of care with patient outcomes for carotid endarterectomy.
      ] analyzing processes of care found that vascular surgeons had greater numbers of processes of care and, therefore, lower odds of adverse outcome after CEA compared with other specialties. In contrast, Cowan et al. [
      • Cowan Jr., J.A.
      • Dimick J.B.
      • Thompson B.G.
      • et al.
      Surgeon volume as an indicator of outcomes after carotid endarterectomy: an effect independent of specialty practice and hospital volume.
      ] demonstrated that surgeon specialty and hospital volume had no statistically significant effect on mortality or postoperative stroke but that high surgeon volume significantly decreased mortality and stroke rates. An early study by Kempczinski et al. [
      • Kempczinski R.F.
      • Brott T.G.
      • Labutta R.J.
      The influence of surgical specialty and caseload on the results of carotid endarterectomy.
      ] also demonstrated no significant difference in postoperative death or stroke when surgeons were classified by specialty.
      A relatively smaller number of studies have evaluated outcomes for CEA other than mortality and stroke. Length and cost of hospital stay, Transient ischemic attack, and carotid re-occlusion were evaluated by Hollenbeak et al. They found that patients of general surgeons had the lowest costs compared with patients treated by surgeons of other specialties, and patients treated by vascular surgeons had lower re-occlusion rates and shorter hospital stays than patients treated by general surgeons [
      • Hollenbeak C.S.
      • Bowman A.R.
      • Harbaugh R.E.
      • et al.
      The impact of surgical specialty on outcomes for carotid endarterectomy.
      ]. Teso et al. [
      • Teso D.
      • Edwards R.E.
      • Antezana J.N.
      • et al.
      Do vascular surgeons improve the outcome of carotid endarterectomy? An analysis of 12,618 elective cases in the state of Connecticut.
      ] demonstrated that patients of vascular surgeons had a decreased risk of cardiac complications compared with patients of general surgeons.
      The results of this study suggest that surgical specialty has a significant effect on outcomes after CEA. Patients of general surgeons had nearly twice the risk of acquiring an SSI and >1.5 times the risk of CVA than patients of vascular surgeons. However, patients of general surgeons had less than half the risk of having an MI than patients of vascular surgeons. Of the remaining NSQIP outcomes measured, which were less specific to CEA, perioperative blood transfusion was the only other statistically significant outcome difference across specialty. Compared with patients of vascular surgeons, patients of general surgeons had nearly twice the risk of receiving a transfusion.
      Our study also demonstrated that age 80 years and older was associated with nearly three times the mortality risk, four times the MI risk, and interestingly, a significantly decreased SSI risk than that of patients aged younger than 65 years. Female gender was associated with increased LOS and higher risk for any adverse outcome. Not surprisingly, ASA classes 4 and 5 were associated with increased risk of mortality, MI, and CVA, and a significant increase in LOS as compared with the other ASA classes. Regional anesthesia was found to be associated with better outcomes. Risk of MI, risk of any negative outcome, and hospital LOS were all decreased in patients who received regional anesthesia compared with patients who received general anesthesia.
      Our finding of relatively low numbers of CEAs performed by general surgeons compared with the higher volumes of CEAs performed by vascular surgeons has been previously shown. Valentine et al. [
      • Valentine R.J.
      • Rhodes R.S.
      • Jones A.
      • Biester T.W.
      Evolving patterns of vascular surgery care in the United States: a report from the American Board of Surgery.
      ] demonstrated that the majority of general surgeons do not perform any major vascular procedures such as CEA, and younger general surgeons are performing fewer such procedures than their older counterparts. They attributed this to the rapid incorporation of endovascular technology into vascular practice. Solomon et al. [
      • Solomon H.
      • Chao A.B.
      • Weaver F.A.
      • Katz S.G.
      Change in practice patterns of an academic division of vascular surgery.
      ] demonstrated that between 2000 and 2005, endovascular CEAs increased by 28.8% compared with open CEA. This increase in endovascular technique has driven vascular surgery to become an independent specialty with unique training requirements, and vascular surgery training has thus decreased among general surgery residencies [
      • Cronenwett J.L.
      Vascular surgery training: is there enough case material?.
      ]. This progressive loss of operative vascular experience among general surgeons likely contributes to the lower volume of CEAs performed by practicing general surgeons.
      There are several limitations to this study. First, the degree of carotid stenosis, which has been shown to be important in determining CEA outcomes, is not included in our data set and we could not control for it [
      North American Symptomatic Carotid Endarterectomy Trial Collaborators
      Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis.
      ,
      Randomised trial of endarterectomy for recently symptomatic carotid stenosis: final results of the MRC European Carotid Surgery Trial (ECST).
      ]. Similarly, whether patients were symptomatic or asymptomatic from their disease was not included in our data set. The study was also limited by the assignment of surgical specialty by the surgical clinical nurse reviewer. Each institution develops its own internal process for determining the best surgical specialty designation for each procedure and can be based on the surgeon's board certification, self-declared specialty, or surgical service line most closely associated with the principal operative procedure [

      American College of Surgeons. (2013). ACS NSQIP Operations Manual: 26-27.

      ]. Outcomes are only measured for 30 d postoperatively; therefore, long-term outcomes cannot be determined from NSQIP data. The limited number of procedures performed by other specialties must also be taken into consideration. Due to small sample size, inferences could not be made in regard to outcome differences of patients treated by neurosurgeons or cardiothoracic surgeons as in previous studies [
      • Feasby T.E.
      • Quan H.
      • Ghali W.A.
      Hospital and surgeon determinants of carotid endarterectomy outcomes.
      ,
      • O'Neill L.
      • Lanska D.J.
      • Hartz A.
      Surgeon characteristics associated with mortality and morbidity following carotid endarterectomy.
      ], and these data were excluded from our study. A larger sample size is needed to determine more accurate outcome differences associated with additional surgical specialties. Another limitation is the large number of procedures performed with spinal, epidural, or no anesthesia (N = 335). It seems unlikely that these types of anesthesia would be used, in particular no anesthesia, and that they represent coding errors.
      The data used in this study also have many advantages over prior studies. This NSQIP data set provided CEA data through the year 2010 from institutions across the United States. This gives a more accurate reflection of CEA outcomes than previous studies that necessarily required participating surgeons to meet benchmarks and, therefore, excluded surgeons with lower success rates [
      North American Symptomatic Carotid Endarterectomy Trial Collaborators
      Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis.
      ,
      Endarterectomy for asymptomatic carotid artery stenosis. Executive Committee for the Asymptomatic Carotid Atherosclerosis Study.
      ]. The greatest advantage is the vast number of variables recorded in the database, including 49 preoperative variables, 17 intraoperative variables, and 33 outcome variables.
      Our analyses suggest that there are differences in outcomes after CEA across surgical specialty. Patients of general surgeons had nearly twice the risk of acquiring an SSI, >1.5 times the risk of CVA, and >1.8 times the risk of blood transfusion than patients of vascular surgeons but had less than half the risk of having an MI. Additional research is needed to explore cultural and practice pattern differences across surgical specialties that may be causative of these CEA outcome differences. More data from CEAs performed by other surgical specialties are also needed to better determine significant differences in outcomes compared with vascular and general surgery.

      Acknowledgment

      ACS-NSQIP Disclaimer: The ACS-NSQIP and the hospitals participating in the ACS-NSQIP are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors. This study does not represent the views or plans of the ACS or the ACS-NSQIP.

      References

        • Murphy S.L.
        • Xu J.
        • Kochanek K.D.
        Deaths: preliminary data for 2010.
        Natl Vital Stat Rep. 2012; 60: 1
        • Howell G.M.
        • Makaroun M.S.
        • Chaer R.A.
        Current management of extracranial carotid occlusive disease.
        J Am Coll Surg. 2009; 208: 442
        • Boules T.N.
        • Proctor M.C.
        • Aref A.
        • et al.
        Carotid endarterectomy remains the standard of care, even in high-risk surgical patients.
        Ann Surg. 2005; 241: 356
        • Roger V.L.
        • Go A.S.
        • Lloyd-Jones D.M.
        • et al.
        Heart disease and stroke statistics—2011 update: a report from the American Heart Association.
        Circulation. 2011; 123: e18
        • North American Symptomatic Carotid Endarterectomy Trial Collaborators
        Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis.
        N Engl J Med. 1991; 325: 445
      1. Randomised trial of endarterectomy for recently symptomatic carotid stenosis: final results of the MRC European Carotid Surgery Trial (ECST).
        Lancet. 1998; 351: 1379
      2. Endarterectomy for asymptomatic carotid artery stenosis. Executive Committee for the Asymptomatic Carotid Atherosclerosis Study.
        JAMA. 1995; 273: 1421
        • Bellosta R.
        • Luzzani L.
        • Carugati C.
        • et al.
        Routine shunting is a safe and reliable method of cerebral protection during carotid endarterectomy.
        Ann Vasc Surg. 2006; 20: 482
        • Feasby T.E.
        • Quan H.
        • Ghali W.A.
        Hospital and surgeon determinants of carotid endarterectomy outcomes.
        Arch Neurol. 2002; 59: 1877
        • Ruby S.T.
        • Robinson D.
        • Lynch J.T.
        • Mark H.
        Outcome analysis of carotid endarterectomy in Connecticut: the impact of volume and specialty.
        Ann Vasc Surg. 1996; 10: 22
        • Schneider E.B.
        • Black 3rd, J.H.
        • Hambridge H.L.
        • et al.
        The impact of race and ethnicity on the outcome of carotid interventions in the United States.
        J Surg Res. 2012; 177: 172
        • Kempczinski R.F.
        • Brott T.G.
        • Labutta R.J.
        The influence of surgical specialty and caseload on the results of carotid endarterectomy.
        J Vasc Surg. 1986; 3: 911
        • Brott T.
        • Thalinger K.
        The practice of carotid endarterectomy in a large metropolitan area.
        Stroke. 1984; 15: 950
        • Hannan E.L.
        • Popp A.J.
        • Feustel P.
        • et al.
        Association of surgical specialty and processes of care with patient outcomes for carotid endarterectomy.
        Stroke. 2001; 32: 2890
        • Hollenbeak C.S.
        • Bowman A.R.
        • Harbaugh R.E.
        • et al.
        The impact of surgical specialty on outcomes for carotid endarterectomy.
        J Surg Res. 2010; 159: 595
        • O'Neill L.
        • Lanska D.J.
        • Hartz A.
        Surgeon characteristics associated with mortality and morbidity following carotid endarterectomy.
        Neurology. 2000; 55: 773
        • Fink A.S.
        • Campbell Jr., D.A.
        • Mentzer Jr., R.M.
        • et al.
        The National Surgical Quality Improvement Program in non-veterans administration hospitals: initial demonstration of feasibility.
        Ann Surg. 2002; 236 (discussion 353-344): 344
        • Khuri S.F.
        • Daley J.
        • Henderson W.
        • et al.
        The Department of Veterans Affairs' NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA Surgical Quality Improvement Program.
        Ann Surg. 1998; 228: 491
        • Boltz M.M.
        • Hollenbeak C.S.
        • Julian K.G.
        • et al.
        Hospital costs associated with surgical site infections in general and vascular surgery patients.
        Surgery. 2011; 150: 934
      3. American College of Surgeons. (2013). ACS NSQIP Operations Manual: 26-27.

      4. E Leuven, B Sianesi. (21 Dec 2012) PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. http://ideas.repec.org/c/boc/bocode/s432001.html. Accessed Oct 2012.

        • Finks J.F.
        • Osborne N.H.
        • Birkmeyer J.D.
        Trends in hospital volume and operative mortality for high-risk surgery.
        N Engl J Med. 2011; 364: 2128
        • Goodney P.P.
        • Likosky D.S.
        • Cronenwett J.L.
        Factors associated with stroke or death after carotid endarterectomy in Northern New England.
        J Vasc Surg. 2008; 48: 1139
        • Holt P.J.
        • Poloniecki J.D.
        • Loftus I.M.
        • Thompson M.M.
        The relationship between hospital case volume and outcome from carotid endartectomy in England from 2000 to 2005.
        Eur J Vasc Endovasc Surg. 2007; 34: 646
        • Holt P.J.
        • Poloniecki J.D.
        • Loftus I.M.
        • Thompson M.M.
        Meta-analysis and systematic review of the relationship between hospital volume and outcome following carotid endarterectomy.
        Eur J Vasc Endovasc Surg. 2007; 33: 645
        • Halm E.A.
        • Tuhrim S.
        • Wang J.J.
        • et al.
        Racial and ethnic disparities in outcomes and appropriateness of carotid endarterectomy: impact of patient and provider factors.
        Stroke. 2009; 40: 2493
        • Harthun N.L.
        • Stukenborg G.J.
        Atrial fibrillation is associated with increased risk of perioperative stroke and death from carotid endarterectomy.
        J Vasc Surg. 2010; 51: 330
        • Killeen S.D.
        • Andrews E.J.
        • Redmond H.P.
        • Fulton G.J.
        Provider volume and outcomes for abdominal aortic aneurysm repair, carotid endarterectomy, and lower extremity revascularization procedures.
        J Vasc Surg. 2007; 45: 615
        • Waljee J.F.
        • Greenfield L.J.
        • Dimick J.B.
        • Birkmeyer J.D.
        Surgeon age and operative mortality in the United States.
        Ann Surg. 2006; 244: 353
        • Westvik H.H.
        • Westvik T.S.
        • Maloney S.P.
        • et al.
        Hospital-based factors predict outcome after carotid endarterectomy.
        J Surg Res. 2006; 134: 74
        • Harthun N.L.
        • Kongable G.L.
        • Baglioni A.J.
        • et al.
        Examination of sex as an independent risk factor for adverse events after carotid endarterectomy.
        J Vasc Surg. 2005; 41: 223
        • Cowan Jr., J.A.
        • Dimick J.B.
        • Thompson B.G.
        • et al.
        Surgeon volume as an indicator of outcomes after carotid endarterectomy: an effect independent of specialty practice and hospital volume.
        J Am Coll Surg. 2002; 195: 814
        • Birkmeyer J.D.
        • Siewers A.E.
        • Finlayson E.V.
        • et al.
        Hospital volume and surgical mortality in the United States.
        N Engl J Med. 2002; 346: 1128
        • Pearce W.H.
        • Parker M.A.
        • Feinglass J.
        • et al.
        The importance of surgeon volume and training in outcomes for vascular surgical procedures.
        J Vasc Surg. 1999; 29 (discussion 777–778): 768
        • Kucey D.S.
        • Bowyer B.
        • Iron K.
        • et al.
        Determinants of outcome after carotid endarterectomy.
        J Vasc Surg. 1998; 28: 1051
        • Hannan E.L.
        • Popp A.J.
        • Tranmer B.
        • et al.
        Relationship between provider volume and mortality for carotid endarterectomies in New York state.
        Stroke. 1998; 29: 2292
        • Cebul R.D.
        • Snow R.J.
        • Pine R.
        • et al.
        Indications, outcomes, and provider volumes for carotid endarterectomy.
        JAMA. 1998; 279: 1282
        • Perler B.A.
        • Dardik A.
        • Burleyson G.P.
        • et al.
        Influence of age and hospital volume on the results of carotid endarterectomy: a statewide analysis of 9918 cases.
        J Vasc Surg. 1998; 27 (discussion 31–33): 25
        • AbuRahma A.F.
        • Stone P.A.
        • Srivastava M.
        • et al.
        The effect of surgeon's specialty and volume on the perioperative outcome of carotid endarterectomy.
        J Vasc Surg. 2013; 58: 666
        • Teso D.
        • Edwards R.E.
        • Antezana J.N.
        • et al.
        Do vascular surgeons improve the outcome of carotid endarterectomy? An analysis of 12,618 elective cases in the state of Connecticut.
        Vascular. 2004; 12: 155
        • Valentine R.J.
        • Rhodes R.S.
        • Jones A.
        • Biester T.W.
        Evolving patterns of vascular surgery care in the United States: a report from the American Board of Surgery.
        J Am Coll Surg. 2013; 216 (e881): 886
        • Solomon H.
        • Chao A.B.
        • Weaver F.A.
        • Katz S.G.
        Change in practice patterns of an academic division of vascular surgery.
        Arch Surg. 2007; 142 (discussion 736–737): 733
        • Cronenwett J.L.
        Vascular surgery training: is there enough case material?.
        Semin Vasc Surg. 2006; 19: 187