ABSTRACT
Background: The occurrence of new-onset diabetes mellitus (NODM) following distal pancreatectomy (DP) is a significant concern, as it impacts long-term patient outcomes. There is a lack of reliable clinical models for predicting and stratifying danger of NODM in these patients.
Aim: This research intended to develop and confirm a novel medical model for predicting and stratifying the risk of new-onset diabetes mellitus in patients experiencing distal pancreatectomy.
Methods: A prospective cohort study was conducted from November 2022 and November 2023, involving 100 patients who underwent distal pancreatectomy. Patients were monitored for the development of NODM post-surgery. A variety of potential risk factors, including demographic, clinical, and surgical variables, were analyzed. Multivariate logistic regression was employed to recognize significant forecasters of NODM. The model was validated using bootstrapping techniques and performance metrics like area under receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis.
Results: The research included the diverse cohort of 100 individuals, having mean age of 58 years. Significant predictors of NODM identified included preoperative fasting glucose levels, body mass index (BMI), extent of pancreatic resection, and preoperative hemoglobin A1c levels. The final predictive model established good discrimination with an AUC of 0.87 (95% CI: 0.80-0.93) and adequate calibration. Internal validation confirmed the robustness of the model with minimal optimism.
Conclusion: The novel clinical model developed in this study effectively predicted and stratified danger of new-onset diabetes mellitus in individuals experiencing distal pancreatectomy. This model can aid clinicians in identifying high-risk patients and implementing targeted interventions to mitigate the risk of diabetes post-surgery.
Keywords: New-Onset Diabetes Mellitus, Distal Pancreatectomy, Risk Prediction Model, Clinical Stratification, Diabetes Risk Factors.