{"title":"训练ChatGPT用于手术决策:使用算法和证据进行减肥手术分析。","authors":"Sergi Sanchez-Cordero , Ruth Lopez-Gonzalez , Helena Fernandez , Jordi Pujol-Gebellí","doi":"10.1016/j.orcp.2025.08.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Selecting the most appropriate bariatric surgery (BS) technique is a complex, individualized process. Artificial intelligence (AI) tools like ChatGPT may assist, but their clinical utility is unclear. This study evaluates whether ChatGPT’s recommendations for BS improve after exposure to scientific literature and how they align with real-world clinical decisions.</div></div><div><h3>Methods</h3><div>A retrospective single-center study included 283 patients who underwent primary BS between 2023 and 2025. No exclusion criteria were applied. Clinical variables (age, sex, BMI, comorbidities, and preoperative data) were collected. ChatGPT was asked to recommend the most suitable BS technique for each patient profile, first without context and then after being exposed to 412 open-access scientific articles. Recommendations were compared with actual clinical decisions using percentage agreement and Cohen’s Kappa.</div></div><div><h3>Results</h3><div>Initially, ChatGPT favored sleeve gastrectomy (SG, 56.8 %), followed by Roux-en-Y gastric bypass (RYGB, 26.8 %) and one-anastomosis gastric bypass (OAGB, 16.4 %); SADI-S was never suggested. Concordance with clinical practice was 20.0 % (Kappa = 0.003; p = 0.96). After training, SG recommendations decreased (35.7 %), RYGB increased (30.3 %), SADI-S emerged (17.1 %), and dual options appeared in 4 %. Concordance improved modestly to 25.8 % (Kappa = 0.068; p = 0.29), with a significant shift in global distribution (p < 0.00001).</div></div><div><h3>Conclusions</h3><div>ChatGPT adapts its recommendations after contextual training, but concordance with clinical judgment remains low. While potentially useful as an educational tool, ChatGPT is not yet reliable for autonomous surgical decision-making.</div></div>","PeriodicalId":19408,"journal":{"name":"Obesity research & clinical practice","volume":"19 4","pages":"Pages 352-355"},"PeriodicalIF":2.5000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Training ChatGPT for surgical decisions: Bariatric surgery analysis using algorithms and evidence\",\"authors\":\"Sergi Sanchez-Cordero , Ruth Lopez-Gonzalez , Helena Fernandez , Jordi Pujol-Gebellí\",\"doi\":\"10.1016/j.orcp.2025.08.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Selecting the most appropriate bariatric surgery (BS) technique is a complex, individualized process. Artificial intelligence (AI) tools like ChatGPT may assist, but their clinical utility is unclear. This study evaluates whether ChatGPT’s recommendations for BS improve after exposure to scientific literature and how they align with real-world clinical decisions.</div></div><div><h3>Methods</h3><div>A retrospective single-center study included 283 patients who underwent primary BS between 2023 and 2025. No exclusion criteria were applied. Clinical variables (age, sex, BMI, comorbidities, and preoperative data) were collected. ChatGPT was asked to recommend the most suitable BS technique for each patient profile, first without context and then after being exposed to 412 open-access scientific articles. Recommendations were compared with actual clinical decisions using percentage agreement and Cohen’s Kappa.</div></div><div><h3>Results</h3><div>Initially, ChatGPT favored sleeve gastrectomy (SG, 56.8 %), followed by Roux-en-Y gastric bypass (RYGB, 26.8 %) and one-anastomosis gastric bypass (OAGB, 16.4 %); SADI-S was never suggested. Concordance with clinical practice was 20.0 % (Kappa = 0.003; p = 0.96). After training, SG recommendations decreased (35.7 %), RYGB increased (30.3 %), SADI-S emerged (17.1 %), and dual options appeared in 4 %. Concordance improved modestly to 25.8 % (Kappa = 0.068; p = 0.29), with a significant shift in global distribution (p < 0.00001).</div></div><div><h3>Conclusions</h3><div>ChatGPT adapts its recommendations after contextual training, but concordance with clinical judgment remains low. While potentially useful as an educational tool, ChatGPT is not yet reliable for autonomous surgical decision-making.</div></div>\",\"PeriodicalId\":19408,\"journal\":{\"name\":\"Obesity research & clinical practice\",\"volume\":\"19 4\",\"pages\":\"Pages 352-355\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Obesity research & clinical practice\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1871403X25000948\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Obesity research & clinical practice","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1871403X25000948","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Training ChatGPT for surgical decisions: Bariatric surgery analysis using algorithms and evidence
Background
Selecting the most appropriate bariatric surgery (BS) technique is a complex, individualized process. Artificial intelligence (AI) tools like ChatGPT may assist, but their clinical utility is unclear. This study evaluates whether ChatGPT’s recommendations for BS improve after exposure to scientific literature and how they align with real-world clinical decisions.
Methods
A retrospective single-center study included 283 patients who underwent primary BS between 2023 and 2025. No exclusion criteria were applied. Clinical variables (age, sex, BMI, comorbidities, and preoperative data) were collected. ChatGPT was asked to recommend the most suitable BS technique for each patient profile, first without context and then after being exposed to 412 open-access scientific articles. Recommendations were compared with actual clinical decisions using percentage agreement and Cohen’s Kappa.
Results
Initially, ChatGPT favored sleeve gastrectomy (SG, 56.8 %), followed by Roux-en-Y gastric bypass (RYGB, 26.8 %) and one-anastomosis gastric bypass (OAGB, 16.4 %); SADI-S was never suggested. Concordance with clinical practice was 20.0 % (Kappa = 0.003; p = 0.96). After training, SG recommendations decreased (35.7 %), RYGB increased (30.3 %), SADI-S emerged (17.1 %), and dual options appeared in 4 %. Concordance improved modestly to 25.8 % (Kappa = 0.068; p = 0.29), with a significant shift in global distribution (p < 0.00001).
Conclusions
ChatGPT adapts its recommendations after contextual training, but concordance with clinical judgment remains low. While potentially useful as an educational tool, ChatGPT is not yet reliable for autonomous surgical decision-making.
期刊介绍:
The aim of Obesity Research & Clinical Practice (ORCP) is to publish high quality clinical and basic research relating to the epidemiology, mechanism, complications and treatment of obesity and the complication of obesity. Studies relating to the Asia Oceania region are particularly welcome, given the increasing burden of obesity in Asia Pacific, compounded by specific regional population-based and genetic issues, and the devastating personal and economic consequences. The journal aims to expose health care practitioners, clinical researchers, basic scientists, epidemiologists, and public health officials in the region to all areas of obesity research and practice. In addition to original research the ORCP publishes reviews, patient reports, short communications, and letters to the editor (including comments on published papers). The proceedings and abstracts of the Annual Meeting of the Asia Oceania Association for the Study of Obesity is published as a supplement each year.