期刊
OBESITY SURGERY
卷 31, 期 3, 页码 1030-1037出版社
SPRINGER
DOI: 10.1007/s11695-020-05103-0
关键词
Bariatric surgery; Roux-en-Y gastric bypass; Waiting list; Public health; Waiting time; Scoring system
类别
资金
- National Council of Technological and Scientific Development (CNPq)
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brazil (CAPES) [001]
- Fundo de Incentivo a Pesquisa e Eventos (FIPE) of Hospital de Clinicas de Porto Alegre
This study aimed to identify preoperative characteristics that predict success after bariatric surgery, using PLS regression and multiple linear regression to find factors that influence postoperative outcomes. A success index was developed to prioritize patients with the best indication for the procedure.
Purpose There are no criteria to establish priority for bariatric surgery candidates in the public health system in several countries. The aim of this study is to identify preoperative characteristics that allow predicting the success after bariatric surgery. Materials and Methods Four hundred and sixty-one patients submitted to Roux-en-Y gastric bypass were included. Success of the surgery was defined as the sum of five outcome variables, assessed at baseline and 12 months after the surgery: excess weight loss, use of continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP) as a treatment for obstructive sleep apnea (OSA), daily number of antidiabetics, daily number of antihypertensive drugs, and all-cause mortality. Partial least squares (PLS) regression and multiple linear regression were performed to identify preoperative predictors. We performed a 90/10 split of the dataset in train and test sets and ran a leave-one-out cross-validation on the train set and the best PLS model was chosen based on goodness-of-fit criteria. Results The preoperative predictors of success after bariatric surgery included lower age, presence of non-alcoholic fatty liver disease and OSA, more years of CPAP/BiPAP use, negative history of cardiovascular disease, and lower number of antihypertensive drugs. The PLS model displayed a mean absolute percent error of 0.1121 in the test portion of the dataset, leading to accurate predictions of postoperative outcomes. Conclusion This success index allows prioritizing patients with the best indication for the procedure and could be incorporated in the public health system as a support tool in the decision-making process.
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