Construction and evaluation of predictive model for risk of postoperative fecal soiling in children with Hirschsprung's disease
10.3969/j.issn.1671-8348.2024.01.009
- VernacularTitle:先天性巨结肠患儿术后污粪风险预测模型的构建及评价
- Author:
Huaxing QIN
1
;
Qiuhuan HUANG
;
Haige HUANG
;
Danli QIN
;
Liuxue LU
;
Lilong QIN
;
Zhiqiong MENG
;
Hanjing ZHOU
;
Xiujuan HUANG
Author Information
1. 右江民族医学院附属医院普通外科,广西百色 533000
- Keywords:
Hirschsprung's disease;
child;
fecal soiling;
risk factors;
predictive model
- From:
Chongqing Medicine
2024;53(1):44-49
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the risk factors of postoperative fecal contamination in children pa-tients with Hirschsprung's disease(HSCR),and to construct and evaluate the risk predictive model.Methods The clinical data in 377 children patients with HSCR in 3 class 3A hospitals in Guangxi from Janu-ary 2016 to June 2021were retrospectively analyzed by adopting the convenience sampling method.The pa-tients were divided into the modeling group(n=264)and testing model group(n=113)with a ratio of 7∶3.The risk factors of postoperative fecal soiling were analyzed by the single factor and multiple factors,and the risk predictive model was constructed.The receiver operating characteristic(ROC)curve was used to detect the discriminative ability of the model and the H-L test was used to determine the goodness of fit of the mod-el.The model was prospectively validated in 21 children patients with HSCR from August to December 2021.Results Among 377 children patients with HSCR,the fecal soiling occurred in 131 cases with a incidence rate of 34.75％.The constructed predictive model of fecal contamination risk after HSCR operation:logit(P)=-2.385+1.697 × special type of megacolon+0.929 × Soave+0.105 × length of bowel resection+2.065 × il-literate caregivers+0.808 × caregivers'implementation of postoperative diet+0.867 × postoperative defecation training by caregivers.The area under the curve(AUC)in the modeling group was 0.849,the Yoden index was 0.53,the optimal critical value of the model was 0.32,the sensitivity was 76.00％,and the specificity was 77.00％.The H-L test,X2=6.649,P=0.575.AUC of the testing model group was 0.736,the sensitivity was 81.25％,and the specificity was 78.46％.The prospective validation results showed that the sensitivity and specificity of the model were 66.67％and 100％respectively.Conclusion The constructed model has good i-dentification and predictive ability.
