Construction of a risk prediction model for postoperative gastrointestinal dysfunction and prevention in patients with gastrointestinal tumors
Year: 2026
Type: article
Abstract: BACKGROUND: The global incidence of gastrointestinal tumors is continuously increasing. Surgery remains the primary treatment modality. However, postoperative gastrointestinal dysfunction remains prevalent, severely impeding patient recovery and increasing medical burden. Existing research investigating risk prediction and preventive management has some limitations. AIM: To construct a risk-prediction model for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors and explore preventive management strategies. METHODS: Data from 176 patients who underwent gastrointestinal tumor surgery at the authors' hospital between November 2022 and November 2024 were included. Patients were divided into groups according to Tilburg Frailty Scale scores on postoperative day 5. Risk factors were screened using univariate and multivariate logistic regression analyses to establish a model, and the effectiveness of preventive management measures was evaluated. RESULTS: Seven factors including age, sex, body mass index, tumor stage, operative duration, and preoperative hemoglobin and albumin levels were identified as independent risk factors. The constructed model had an area under the receiver operating characteristic curve of 0.895. The incidence of postoperative gastrointestinal dysfunction in the intervention group was significantly lower than that in the control group using preventive management measures based on the model. CONCLUSION: An effective risk-prediction model was constructed and independent risk factors were identified. Preventive management measures based on this model can reduce risk and provide a scientific basis for clinical practice.
Authors: Xiao-Hui Wang, Yi Wang, Xi Liu, Xiao-Lan Ouyang, Fen Xie, Lu Liao
Institutions: Ganzhou People's Hospital, Gannan Medical University
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7131363440