Influencing Factors and Construction of Risk Prediction Model of Urinary Retention After Operation for Severe Uterine Prolapse

XIANG Yuancui; LI Haoran; MA Jinping; ZHANG Hui; WANG Yali; LI Hongjuan

doi:10.3969/j.issn.1004-437X.2026.12.016

Abstract：Objective To analyze the influencing factors of urinary retention after the operation of severe uterine prolapse,and to construct a risk prediction model based on this.Methods The clinical data of 492 patients with severe uterine prolapse who underwent surgical treatment in Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2016 to November 2023 were retrospectively analyzed.They were divided into modeling group(328 cases)and validation group(164 cases)in a 2∶1 ratio.The patients in the modeling group were further divided into urinary retention group(65 cases)and non urinary retention group(263 cases)according to whether with urinary retention after operation.The influencing factors of urinary retention after severe uterine prolapse was analyzed by using multivariate logistic regression analysis,and a risk prediction nomogram model was constructed based on this.The Bootstrap method was used to internally validate the nomogram model,and the calibration curve was drawn to evaluate the calibration of the model.The receiver operating characteristic(ROC)curve was drawn to evaluate the prediction efficiency of the model,and the decision curve was drawn to verify the clinical net benefit rate of the model.The model was externally verified using a verification group data.Results There was no statistically significant difference in general information between the modeling group and the validation group(P＞0.05).The proportions of diabetes history,cesarean section history,indwelling catheter time＞3 d,postoperative urinary system infection,removal of urinary catheter when bladder emptiness and postoperative self-rating anxiety scale(SAS)score in the urinary retention group were higher than those in the non urinary retention group(P＜0.05),and the proportions of preoperative urination training and postoperative acupoint massage were lower than those in the non urinary retention group(P＜0.05).Multivariate logistic regression analysis showed that the diabetes history,cesarean section history,postoperative SAS score,indwelling catheter time＞3 d,postoperative urinary system infection,removal of urinary catheter when bladder emptiness were all risk factors for urinary retention after the severe uterine prolapse operation(P＜0.05),and the preoperative urine training and postoperative acupoint massage were protective factors(P＜0.05).A risk prediction nomogram model was constructed based on the above influencing factors,and the consistency indexes of the modeling group and verification group were 0.884 and 0.861,respectively,and the calibration curve and the ideal curve fitted well.The ROC curve results showed that the area under the curve(AUC),sensitivity and specificity of the modeling group in predicting urinary retention after severe uterine prolapse were 0.882(95％CI:0.843-0.915),84.62％and 80.61％,respectively,and the AUC,sensitivity and specificity of the verification group were 0.848(95％CI:0.783～0.899),81.82％and 83.21％,respectively.The decision curve showed that the modeling group had a higher net benefit value when the risk threshold probability was 1％-97％,and the validation group had a higher net benefit value when the risk threshold probability was 1％-91％.Conclusion Diabetes history,cesarean section history,preoperative urination training,postoperative SAS score,indwelling catheter time＞3 d,postoperative urinary system infection,removal of urinary catheter when bladder emptiness and postoperative acupoint massage are all influencing factors of urinary retention after the severe uterine prolapse,and the nomogram prediction model constructed based on the above influencing factors has good calibration and prediction efficiency,and it has high clinical application value.