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Nomogram for soiling prediction in postsurgery hirschsprung children: a retrospective study
Pei Wang1, Erhu Fang, Xiang Zhao
1Department of Pediatric Surgery, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology; Hubei Clinical Center of Hirschsprung Disease and Allied Disorders, Wuhan, People's Republic of China.
This study developed a nomogram to predict postoperative soiling in Hirschsprung disease (HSCR) patients over one year old. The model identifies surgical history, bowel length, and procedure type as key risk factors, aiding personalized patient care.
Area of Science:
- Pediatric Surgery
- Gastroenterology
- Medical Informatics
Background:
- Hirschsprung disease (HSCR) is a congenital condition requiring surgical intervention.
- Postoperative soiling is a common complication following HSCR surgery, impacting patient outcomes.
- Predictive tools are needed to identify patients at higher risk for this complication.
Purpose of the Study:
- To develop and validate a nomogram for predicting the probability of postoperative soiling in patients over one year old who underwent surgery for HSCR.
- To identify significant predictive factors for postoperative soiling in this patient population.
Main Methods:
- Retrospective analysis of 601 HSCR patients (age > 1 year) who underwent surgical therapy between 2000 and 2019.
- Patients were divided into training (70%) and validation (30%) sets.
- Least Absolute Shrinkage and Selection Operator (LASSO) and multivariable logistic regression were used to identify predictive variables for nomogram construction.
- Model performance was assessed using C-index, Area Under the ROC Curve (AUC), calibration curves, and decision curve analysis.
Main Results:
- Three hundred and one patients were analyzed, with 97 experiencing postoperative soiling.
- Key predictive factors for soiling included surgical history, length of resected bowel, and specific surgical procedures.
- The nomogram demonstrated strong predictive performance with a C-index of 0.871 (training) and 0.878 (validation), and AUC of 0.896 (training) and 0.866 (validation).
- Calibration curves indicated good agreement between predicted and observed soiling probabilities.
Conclusions:
- This study presents the first validated nomogram for predicting postoperative soiling risk in HSCR patients over one year of age.
- The developed model can assist clinicians in assessing individual soiling risk, facilitating personalized management strategies.
- This tool has the potential to improve patient care and outcomes following HSCR surgery.
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