Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
BMC Surg. 2024 Oct 3;24(1):283. doi: 10.1186/s12893-024-02575-0.
Current research on delayed gastric emptying (DGE) after pancreatic surgery is predominantly focused on pancreaticoduodenectomy (PD), with little exploration into DGE following total pancreatectomy (TP). This study aims to investigate the risk factors for DGE after TP and develop a predictive model.
This retrospective cohort study included 106 consecutive cases of TP performed between January 2013 and December 2023 at Peking Union Medical College Hospital (PUMCH). After applying the inclusion criteria, 96 cases were selected for analysis. These patients were randomly divided into a training set (n = 67) and a validation set (n = 29) in a 7:3 ratio. LASSO regression and multivariate logistic regression analyses were used to identify factors associated with clinically relevant DGE (grades B/C) and to construct a predictive nomogram. The ROC curve, calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were employed to evaluate the model's prediction accuracy.
The predictive model identified end-to-side gastrointestinal anastomosis, intraoperative blood transfusion, and venous reconstruction as risk factors for clinically relevant DGE after TP. The ROC was 0.853 (95%CI 0.681-0.900) in the training set and 0.789 (95%CI 0.727-0.857) in the validation set. The calibration curve, DCA, and CIC confirmed the accuracy and practicality of the nomogram.
We developed a novel predictive model that accurately identifies potential risk factors associated with clinically relevant DGE in patients undergoing TP.
目前关于胰腺手术后胃排空延迟（DGE）的研究主要集中在胰十二指肠切除术（PD），而对全胰切除术（TP）后 DGE 的研究较少。本研究旨在探讨 TP 后 DGE 的危险因素，并建立预测模型。
这是一项回顾性队列研究，纳入了 2013 年 1 月至 2023 年 12 月期间在北京协和医院接受 TP 的 106 例连续病例。应用纳入标准后，选择了 96 例进行分析。这些患者以 7:3 的比例随机分为训练集（n=67）和验证集（n=29）。采用 LASSO 回归和多变量逻辑回归分析来识别与临床相关的 DGE（B/C 级）相关的因素，并构建预测列线图。通过 ROC 曲线、校准曲线、决策曲线分析（DCA）和临床影响曲线（CIC）评估模型的预测准确性。
预测模型确定了端端胃肠吻合、术中输血和静脉重建是 TP 后发生临床相关 DGE 的危险因素。该模型在训练集的 ROC 为 0.853（95%CI 0.681-0.900），在验证集的 ROC 为 0.789（95%CI 0.727-0.857）。校准曲线、DCA 和 CIC 证实了列线图的准确性和实用性。
我们开发了一种新的预测模型，可以准确识别接受 TP 的患者中与临床相关的 DGE 相关的潜在危险因素。
