Predicting Hypoglycemia Risk After Gastrointestinal Surgery in T2DM: A Retrospective Cohort Study

Huilan Yao¹Shijin Yuan²Hongying Pan^1*Sisi Hong¹Chen Huang¹Linfang Zhao¹Hongdi Yuan¹Lei Mei¹Yinghong Zheng¹Xiaolong Liu³Weina Lu⁴

• ¹Sir Run Run Shaw Hospital, School of Medicine, Graduate School, Zhejiang University, Hangzhou, China
• ²Department of medical oncology, Sir Run Run Shaw Hospital, School of Medicine, Graduate School, Zhejiang University, Hangzhou, China
• ³Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Graduate School, Zhejiang University, Hangzhou, China
• ⁴Department of Endocrinology, Sir Run Run Shaw Hospital, School of Medicine, Graduate School, Zhejiang University, Hangzhou, China

Objective: To identify factors influencing hypoglycemia in patients with type 2 diabetes mellitus (T2DM) following gastrointestinal tumour surgery and construct a predictive model for assessing hypoglycemia hypoglycemia risk. Methods: We retrospectively collected data on 1280 patients with T2DM who underwent gastrointestinal tumour surgery and divided them into two groups: one for model building (n = 982) and another for validation (n = 298). We used multivariate logistic regression to develop a predictive model for hypoglycemia following gastrointestinal tumour surgery. The model's predictive performance was evaluated using the area under the receiver operating characteristic (ROC) curve, and its generalization ability was evaluated using the Bootstrap test and the 5-fold cross-validation test. Results: We identified hypoglycemia following gastrointestinal tumour surgery in 124 of 982 (12.6%) T2DM patients in the developmental cohort. Finally, five predictors including duration of diabetes, operation duration, preoperative fasting time, preoperative hypoglycemic regimen (subcutaneous insulin injection), and glucose fluctuation on the day of surgery,were integrated into the predictive model. The performance of the hypoglycemia risk prediction model for patients with T2DM undergoing gastrointestinal tumor surgery was comprehensively evaluated. The model demonstrated an area under the receiver operating characteristic curve (AUC) of 0.837 (95% CI: 0.792-0.882), indicating strong discriminative ability. Internal validation via five-fold cross-validation with Bootstrap resampling revealed close approximation of the calibration curve to the ideal line, refining high consistency between predicted probabilities and actual hypoglycemia occurrence. Decision curve analysis (DCA) further supported its clinical utility, indicating value in clinical decision-making for hypoglycemia risk stratification and preventive intervention selection.The developed model exhibits high discriminative ability and good calibration. Following visualization (e.g., nomogram), it provides a clinical tool for healthcare providers to stratify hypoglycemia risk in T2DM patients undergoing gastrointestinal tumour surgery, enabling personalized perioperative glucose management and informed decision-making to improve patient outcomes.