Predicting serious complications following bariatric surgery in geriatric patients: development of the GeriBari scoring tool using the MBSAQIP database.

Abstract

Geriatric patients have a greater risk of complications after bariatric surgery. The objective of this study was to develop a tool to predict serious complications in geriatric patients after minimally invasive bariatric surgery. To develop a predictive model, GeriBari, for serious complications in geriatric patients after bariatric surgery. Multiple accredited bariatric surgery centers in the United States and Canada. This was a retrospective cohort study of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database, which collects 30-day bariatric surgery outcomes from 868 accredited centers. Geriatric patients defined as those ≥65 years old who underwent primary laparoscopic Roux-en-Y gastric bypass (LRYGB) or laparoscopic sleeve gastrectomy (LSG) were included. Characteristics associated with serious complications were identified using univariate and multivariable analyses. A predictive model, GeriBari, was derived using a forward selection algorithm from operative years 2015, 2017, and 2019. GeriBari's robustness was tested against a validation cohort of subjects from operative years 2016 and2018. A total of 40,199 geriatric patients underwent LRYGB (27.7%) or LSG (72.3%). Overall, 1866 (4.6%) experienced a complication, which included bleeding (1.6%), reoperation (1.6%), reintervention (1.3%), unplanned intubation (.4%), and pneumonia (.4%). Mortality was higher in the geriatric patients than that in younger patients (.27% versus .08%). GeriBari consists of 12 factors that predicted serious complications and stratified individuals into high- (>6%) and low-risk (<6%) groups. This tool accurately predicted events in the validation cohort with sensitivity of 46.0% and specificity of 100%. GeriBari enables preoperative risk stratification for 30-day serious complications in geriatric patients undergoing bariatric surgery. Stratifying low- and high-risk geriatric patients for adverse events allows for informed clinical decision-making prior to bariatric surgery.