Use of bariatric outcomes longitudinal database (BOLD) to study variability in patient success after bariatric surgery

Abstract

Background: This study was conducted to determine the contributions of various predictors to the large variations in absolute weight loss and percent body mass index (BMI) loss after bariatric surgery.

Methods: The data source was the Bariatric Outcomes Longitudinal Database(SM) by the Surgical Review Corporation. Eligibility criteria included a first bariatric surgery for adjustable gastric band (AGB), Roux-en-Y gastric bypass (RYBG), or sleeve gastrectomy (SG) between January 2007 and February 2010; age 21 years or older; presurgery BMI > 30 kg/m2; and at least one preoperative visit within 6 months and at least one postoperative visit 30 days or more after surgery. Potential predictor variables included procedural details, patient demographics, comorbidities, and prior surgical history. Linear regression models of absolute weight loss and %BMI loss were fitted at 12, 18, and 24 months. The 12-month absolute weight loss endpoint was then chosen for a more in-depth analysis of variability through variable transformations and separate models by procedure.

Results: A total of 31,443 AGB, 40,352 RYGB, and 2,194 SG patients met all inclusion criteria. Regression models explained 37 to 55% of the variability in %BMI loss and 52 to 65% of variability in absolute weight loss. The key predictors for absolute weight loss at 12 months were procedure (44.8%) and baseline weight (18.5%), with 34.2% of the variability unexplained. Other significant predictors, each of which accounted for <1% of variability, included age, race, and diabetes.

Conclusions: Research on additional sources of variability is still needed to help explain the remaining differences in outcomes after bariatric surgery.