列线图
医学
接收机工作特性
逻辑回归
回顾性队列研究
Lasso(编程语言)
外科
曲线下面积
多元分析
内科学
计算机科学
万维网
作者
Pei Wang,Erhu Fang,Xiang Zhao,Jiexiong Feng
标识
DOI:10.1097/js9.0000000000000993
摘要
Purpose: The aim of this study was to develop a nomogram for predicting the probability of postoperative soiling in patients aged greater than 1 year operated for Hirschsprung disease (HSCR). Materials and methods: The authors retrospectively analyzed HSCR patients with surgical therapy over 1 year of age from January 2000 and December 2019 at our department. Eligible patients were randomly categorized into the training and validation set at a ratio of 7:3. By integrating the least absolute shrinkage and selection operator [LASSO] and multivariable logistic regression analysis, crucial variables were determined for establishment of the nomogram. And, the performance of nomogram was evaluated by C-index, area under the receiver operating characteristic curve, calibration curves, and decision curve analysis. Meanwhile, a validation set was used to further assess the model. Results: This study enrolled 601 cases, and 97 patients suffered from soiling. Three risk factors, including surgical history, length of removed bowel, and surgical procedures were identified as predictive factors for soiling occurrence. The C-index was 0.871 (95% CI: 0.821–0.921) in the training set and 0.878 (95% CI: 0.811–0.945) in the validation set, respectively. And, the AUC was found to be 0.896 (95% CI: 0.855−0.929) in the training set and 0.866 (95% CI: 0.767−0.920) in the validation set. Additionally, the calibration curves displayed a favorable agreement between the nomogram model and actual observations. The decision curve analysis revealed that employing the nomogram to predict the risk of soiling occurrence would be advantageous if the threshold was between 1 and 73% in the training set and 3–69% in the validation set. Conclusion: This study represents the first efforts to develop and validate a model capable of predicting the postoperative risk of soiling in patients aged greater than 1 year operated for HSCR. This model may assist clinicians in determining the individual risk of soiling subsequent to HSCR surgery, aiding in personalized patient care and management.
科研通智能强力驱动
Strongly Powered by AbleSci AI