Establishment of a risk prediction model for neurogenic bladder dysfunction after spinal cord injury
10.3969/j.issn.1006-5725.2025.13.017
- VernacularTitle:脊髓损伤后并发神经源性膀胱功能障碍的风险预测模型构建
- Author:
Xianqun TAN
1
;
Fenglin ZHANG
1
;
Guangyan ZOU
1
;
Xidong CHEN
1
Author Information
1. 遵义医科大学附属医院康复医学科(贵州遵义 563000)
- Publication Type:Journal Article
- Keywords:
spinal cord injury;
neurogenic bladder dysfunction;
decision tree algorithm;
risk pre-diction model
- From:
The Journal of Practical Medicine
2025;41(13):2058-2064
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the risk factors of neurogenic bladder dysfunction(NB)in patients with spinal cord injury,and establish a risk prediction model of NB in patients with spinal cord injury by decision tree algorithm.Method Clinical data of 176 patients with spinal cord injury admitted from April 2022 to July 2024 were retrospectively analyzed.Patients with spinal cord injury were divided into disorder group and non-disorder group according to whether they were complicated by NB.Multivariate Logistic regression analysis was used to screen the risk factors of NB.Modeler software was used to construct the decision tree model of spinal cord injury patients with concurrent NB,and the 5-fold cross-validation method was used to internally verify the model,and the prediction efficiency of the model was compared.Results Among 176 patients with spinal cord injury,42 patients had concurrent NB,the incidence of NB was 23.86%.Logistic regression analysis showed that the level of spinal cord injury(T10—L2),degree of spinal cord injury(complete injury),course of disease(≥6 months),bladder compliance(abnormal),urinary system infection(yes)and detrusor sphincter disorder(yes)were all independent risk factors for NB in patients with spinal cord injury(P<0.05).Probability forecasting model P=1/[1+e-(-6.008+0.791*X1+3.117*X2+1.492*X3+1.270*X4+1.516*X5+2.158*X6)],models to predict the overall accuracy is 80.5%;The prediction accuracy of the model is 71.7%through the cross-verification of 5 fold.Decision tree model showed that the degree of spinal cord injury had the greatest effect on the complication of NB in patients with spinal cord injury,and the information gain was 0.46.ROC results showed that the AUC values of NB predicted by the two models were close(0.873 vs.0.852,Z=0.875,P=0.469).Conclusion The level of spinal cord injury,degree of spinal cord injury,course of disease,bladder compliance,urinary system infection,detrusor sphincter disorder can all predict the risk of NB.The decision tree model constructed in this study can effectively predict the risk probability of NB in patients with spinal cord injury,and medical staff can make targeted plans according to the above factors to reduce the risk of NB.
