Construction and Validation of a Prediction Model for Time to Flatus Discharge Following Elective Gynecologic Laparoscopic Surgery

Abstract

Background:Postoperative intestinal distension in patients undergoing gynecologic laparoscopic surgery may impair wound healing and restrict respiratory function and mobility, potentially leading to serious complications. Reports on factors influencing flatus discharge after gynecologic laparoscopic surgery are limited, and no prediction model for delayed flatus discharge within 24 hours postoperatively has been previously described in this population. This study addresses this gap and provides a nomogram for clinical prediction of this outcome.Methods:Using R version 4.3.3, 70% of the samples were randomly selected using the caret package as the training set for model development, with the remaining 30% retained as the validation set for internal validation. Least absolute shrinkage and selection operator (LASSO) regression was applied for variable selection, and the retained variables were incorporated into a multivariable logistic regression model. A nomogram was constructed and validated using receiver operating characteristic (ROC) curves and calibration curves. Decision curve analysis (DCA) was performed to assess clinical applicability.Results:A total of 194 patients with complete data were included in the analysis, of whom 74 (38.1%) failed to pass flatus within 24 hours of surgery. Five predictive variables were identified through LASSO regression: analgesic pump usage, postoperative anxiety, early in-bed activity, surgical duration, and postoperative serum potassium level. These five variables were integrated into a nomogram to intuitively predict the risk probability for delayed flatus discharge beyond 24 hours after surgery. The model demonstrated good discriminative performance, with an area under the curve (AUC) of 0.866 (95% confidence interval [CI]: 0.806–0.926) in the training set and 0.812 (95% CI: 0.702–0.922) in the validation set. Calibration curves demonstrated good consistency between predicted and observed values. Clinical DCA indicated a high net clinical benefit across threshold probabilities ranging from 0 to 0.75.Conclusions:The constructed nomogram demonstrates good discrimination, calibration, and clinical applicability for predicting the risk of delayed flatus discharge beyond 24 hours following gynecologic laparoscopic surgery. This tool facilitated individualized risk assessment, informed clinical decision-making, and supported proactive management of high-risk populations.