胃旁路术后延迟出院的预测分析

文献信息

中文摘要

背景： 肥胖率的上升以及对减重手术需求的增加导致了术后住院时间的缩短。虽然次日出院正变得越来越普遍，但用于识别需要更长住院时间患者的数据有限。本研究旨在开发一个预测模型，利用术前因素来预测Roux-en-Y胃旁路术后24小时内成功出院（单日出院）。
方法： 进行了回顾性病历审查。记录了患者年龄、性别、术前体重、体重指数（BMI）、药物使用、合并症和出院数据。应用交叉验证（CV）来评估模型的泛化能力，并使用CV误差来确定最佳预测变量集。结果 共纳入525例患者。最终模型预测延长住院时间，预测误差为0.1545。延迟出院的最佳预测变量包括哮喘、术前体重、胃食管反流病（GERD）、加巴喷丁使用、术前BMI、术前抗凝剂使用、慢性疼痛、阻塞性睡眠呼吸暂停（OSA）、血脂异常、慢性肾脏病（CKD）和2型糖尿病（T2DM）。结论 生成了一个包含术前BMI、肥胖相关合并症和药物使用的预测模型。该模型有潜力支持医院资源管理和对适合短住院患者的分类，并提高胃旁路手术资源分配的效率。

英文摘要

BACKGROUND: Growing rates of obesity and an increased demand for bariatric surgery have led to shorter post-operative hospital stays. While next-day discharge is becoming increasingly common, limited data exists to identify patients requiring longer stays. This study aims to develop a prediction model using preoperative factors to predict the successful discharge within 24hours (single-day discharge) following Roux-en-Y gastric bypass.
METHODS: A retrospective chart review was performed. Patient age, gender, preoperative weight, body mass index (BMI), medication use, comorbidities and discharge data were recorded. Cross-validation (CV) was applied to assess the generalizability of the model and CV error was used to identify the best predictor set. Results A total of 525 patients were included. The final model predicted prolonged hospital stay with a prediction error of 0.1545. The best predictive variables for delayed discharge included were asthma, preoperative weight, gastroesophageal reflux disease (GERD), gabapentin use, preoperative BMI, preoperative anticoagulant use, chronic pain, obstructive sleep apnea (OSA), dyslipidemia, chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Conclusions A prediction model including preoperative BMI, obesity-related comorbidities and medication use was generated. This model has the potential to support hospital resource management and triaging patients suitable for short-stay and increase the efficiency of resource allocation for gastric bypass.