Predicting short-term thromboembolic risk following Roux-en-Y gastric bypass using supervised machine learning  

作　　者：Hassam Ali Faisal Inayat Vishali Moond Ahtshamullah Chaudhry Arslan Afzal Zauraiz Anjum Hamza Tahir Muhammad Sajeel Anwar Dushyant Singh Dahiya Muhammad Sohaib Afzal Gul Nawaz Amir H Sohail Muhammad Aziz 

机构地区：[1]Department of Gastroenterology,East Carolina University Brody School of Medicine,Greenville,NC 27834,United States [2]Department of Internal Medicine,Allama Iqbal Medical College,Lahore,Punjab 54550,Pakistan [3]Department of Internal Medicine,Saint Peter's University Hospital and Robert Wood Johnson Medical School,New Brunswick,NJ 08901,United States [4]Department of Internal Medicine,St.Dominic's Hospital,Jackson,MS 39216,United States [5]Department of Internal Medicine,Rochester General Hospital,Rochester,NY 14621,United States [6]Department of Internal Medicine,Jefferson Einstein Hospital,Philadelphia,PA 19141,United States [7]Department of Internal Medicine,UHS Wilson Medical Center,Johnson,NY 13790,United States [8]Division of Gastroenterology,Hepatology and Motility,The University of Kansas School of Medicine,Kansas,KS 66160,United States [9]Department of Internal Medicine,Louisiana State University Health,Shreveport,LA 71103,United States [10]Department of Surgery,University of New Mexico School of Medicine,Albuquerque,NM 87106,United States [11]Department of Gastroenterology and Hepatology,The University of Toledo,Toledo,OH 43606,United States

出　　处：《World Journal of Gastrointestinal Surgery》2024年第4期1097-1108,共12页世界胃肠外科杂志（英文版）（电子版）

摘　　要：BACKGROUND Roux-en-Y gastric bypass(RYGB)is a widely recognized bariatric procedure that is particularly beneficial for patients with class III obesity.It aids in significant weight loss and improves obesity-related medical conditions.Despite its effectiveness,postoperative care still has challenges.Clinical evidence shows that venous thromboembolism(VTE)is a leading cause of 30-d morbidity and mortality after RYGB.Therefore,a clear unmet need exists for a tailored risk assessment tool for VTE in RYGB candidates.AIM To develop and internally validate a scoring system determining the individualized risk of 30-d VTE in patients undergoing RYGB.METHODS Using the 2016–2021 Metabolic and Bariatric Surgery Accreditation Quality Improvement Program,data from 6526 patients(body mass index≥40 kg/m^(2))who underwent RYGB were analyzed.A backward elimination multivariate analysis identified predictors of VTE characterized by pulmonary embolism and/or deep venous thrombosis within 30 d of RYGB.The resultant risk scores were derived from the coefficients of statistically significant variables.The performance of the model was evaluated using receiver operating curves through 5-fold cross-validation.RESULTS Of the 26 initial variables,six predictors were identified.These included a history of chronic obstructive pulmonary disease with a regression coefficient(Coef)of 2.54(P<0.001),length of stay(Coef 0.08,P<0.001),prior deep venous thrombosis(Coef 1.61,P<0.001),hemoglobin A1c>7%(Coef 1.19,P<0.001),venous stasis history(Coef 1.43,P<0.001),and preoperative anticoagulation use(Coef 1.24,P<0.001).These variables were weighted according to their regression coefficients in an algorithm that was generated for the model predicting 30-d VTE risk post-RYGB.The risk model's area under the curve(AUC)was 0.79[95%confidence interval(CI):0.63-0.81],showing good discriminatory power,achieving a sensitivity of 0.60 and a specificity of 0.91.Without training,the same model performed satisfactorily in patients with laparoscopic sleeve gastrec

关 键 词：Roux-en-Y gastric bypass Venous thromboembolism Machine learning Bariatric surgery Predictive modeling 

分 类 号：R735.2[医药卫生—肿瘤]