ACS-NSQIP 2015 Julietta Chang MD, Ali Aminian MD, Stacy A Brethauer MD, Philip R Schauer MD Bariatric and Metabolic Institute

ACS-NSQIP 2015 Julietta Chang MD, Ali Aminian MD, Stacy A Brethauer MD, Philip R Schauer MD Bariatric and Metabolic Institute

Disclosures Authors: No disclosures ACS-NSQIP Disclaimer: The American College of Surgeons National Surgical Quality Improvement Program 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.

Introduction Laparoscopic sleeve gastrectomy (LSG) is gaining in popularity in the U.S. LSG provides durable weight loss and significant resolution of comorbid conditions Estimating the risk of postoperative adverse events after LSG can improve surgical decision making and informed patient consent There is considerable benefit in identifying modifiable preoperative factors associated with increased risk of postsurgical adverse events

Introduction Priorriskcalculators arelimitedbyold data;theuse ofbothopen and laparoscopic surgical outcomes; a lack of strong statistical analysis; and use of predominantly gastric bypass in its development. We lack a strong tool in predicting postoperative adverse events after LSG The aim of this study was to develop a specific and valid preoperative risk calculator for estimation of early postoperative morbidity and mortality after LSG based on a national dataset.

Methods Data extracted from 2012 ACS-NSQIP database 5,871 morbidly obese patients over the age of 18 undergoing LSG with the CPT code 43775 were included. Patients who underwent concurrent endoscopy, liver biopsy, abdominal wall hernia repair, hiatal hernia repair, cholecystectomy, and procedures to manage intraoperative complications were included. 2011 ACS-NSQIP database used to validate risk calculator

Methods Primary outcome was 30-day postoperative serious adverse outcome. Organ/deep surgical site infection Pulmonary embolism Stroke Coma Myocardial infarction Cardiac arrest Acute renal failure Deep vein thrombosis Reintubation Failure to wean from ventilation > 48 hrs Sepsis Septic shock Transfusion requirement Death

Methods Univariate analysis on 52 baseline variables was performed using student s t-test for continuous variables, and Pearson chi-square test or Fisher s exact test for categorical variables. Multiple logistic regression with stepwise variable selection was used to construct a model for prediction of the primary outcome. Model was validated using the 2011 ACS-NSQIP dataset. The regression equation used to generate the model was utilized to construct an online version of the calculator using the Cleveland Clinic Risk Calculator Constructor(www.r-calc.com).

Results 5,871 patients underwent LSG in the 2012 ACS-NSQIP database Meanage43.8,BMI45.9.80%female,76%white,22%withdiabetes. 30-day postoperative mortality was 0.05%, adverse event rate 2.4% Organ/space SSI (0.5%) Reintubation(0.2%) Stroke (0) Mechanical ventilation >48 hrs (0.2%) Coma (0) Sepsis (0.4%) ARF (0) Septic shock (0.1%) MI (0.1%) Need for transfusion (1.2%) DVT (0.3%) Cardiac arrest (0.1%) PE (0.2%) Death (0.05%)

Results 7 significant preoperative comorbidities associated with postoperative serious adverse events. Risk Factor Odds Ratio 95% CI SE Congestive heart failure 6.23 1.25-31.07 0.82 Steroid use for chronic conditions 5.00 2.06-12.15 0.45 Male sex 1.68 1.03-2.72 0.25 Diabetes 1.62 1.07-2.48 0.22 Total bilirubin level 1.57 1.11-2.22 0.18 Body mass index 1.03 1.01-1.05 0.01 Preoperative hematocrit 0.95 0.89-1.00 0.03

Results The multiple logistic regression equation: L = -3.497 + (0.487*Diabetes) + (0.0307*BMI) + (0.517*Male Gender) + (1.83*CHF) + (1.61*Steroid Use) +(0.451*Bilirubin)-(0.054*Hematocrit) Estimatedprobabilityofcompositeadverseevent(100%) =EXP[L]/(1+EXP[L]) The model demonstrated a good calibration and moderate discrimination(c-statistic 0.682). The generated risk model based on 2012 ACS-NSQIP was subsequently validated on the validation dataset (2011, n=3130) which showed a relatively similar performance(c-statistic 0.63; 95% CI 0.55 to 0.71). User-friendly version: www.r-calc.com

Examples of estimated risk Healthywoman,BMI38,Hct42%=1%. Diabeticman,BMI45,Hct42%=3.3% Woman,BMI55,NASHwithTbili3,Hct33%=9.6%. Diabeticwoman,BMI60,chronicsteroiduse,Hct44%=12.6% Diabeticman,BMI62,symptomaticCHF,Hct40%=28.5%

Summary Mortality of bariatric surgery has decreased substantially from 1.5-2% twodecadesagoto0.05%inthecurrentseriesoflsg. Incidence of all of individual complications, except postoperative bleeding,was 0.5%inthisseries Among the 7 identified risk factors, congestive heart failure and then chronic steroid use displayed the strongest independent associations with the probability of post-lsg adverse events. May contribute to surgical decision making