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World J Gastroenterol. Jan 21, 2027; 33(3): 124159
Published online Jan 21, 2027. doi: 10.3748/wjg.124159
Online calculators to predict severe Hirschsprung-associated enterocolitis after pull-through surgery for Hirschsprung disease: A multicenter retrospective study
Jing-Feng Tang, Yun Zhou, Zhi-Bin Luo, Ze-Bing Zheng, Meng-Xin Zhang, Shui-Qing Chi, Guo-Qing Cao, Xi Zhang, Shuai Li, Bin Zhong, Shao-Tao Tang
Jing-Feng Tang, Department of Emergency Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Yun Zhou, Zhi-Bin Luo, Meng-Xin Zhang, Shui-Qing Chi, Guo-Qing Cao, Xi Zhang, Shuai Li, Shao-Tao Tang, Department of Pediatric Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Yun Zhou, Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Ze-Bing Zheng, Department of Pediatric Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi 563000, Guizhou Province, China
Bin Zhong, Department of Pediatric Surgery, Ganzhou Maternal and Child Health Hospital, Ganzhou 341100, Jiangxi Province, China
Co-first authors: Jing-Feng Tang and Yun Zhou.
Co-corresponding authors: Bin Zhong and Shao-Tao Tang.
Author contributions: Tang JF and Zhou Y have played important roles in the experimental design as co-first authors; Tang JF, Zhou Y and Luo ZB performed the research; Zheng ZB and Zhang MX performed the statistical analysis; Chi SQ, Cao GQ, Zhang X and Li S collected the cases; Zhong B and Tang ST designed the research study as co-corresponding authors; all authors have read and approved the final version to be published.
AI contribution statement: The authors take full responsibility and accountability for all content of this manuscript, including any portions for which AI tools were used as assistive technologies. All AI-assisted outputs were carefully reviewed, validated, and approved by the authors. AI tools were not used to generate original scientific data, perform independent scientific analyses, or draw scientific conclusions.
Supported by National Natural Science Foundation of China, No. 82571986; and the Open Research Fund of Hubei Key Laboratory of Precision Radiation Oncology, No. 2024ZLJZFL006.
Institutional review board statement: This multicenter retrospective study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (approval No.[2024]0617-01) and the institutional review boards of the other participating centers. Given the retrospective design and use of de-identified data, the requirement for individual informed consent was waived by the ethics committees.
Informed consent statement: Given the retrospective design and use of de-identified data, the requirement for individual informed consent was waived by the Institutional Review Board.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Data sharing statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
Corresponding author: Shao-Tao Tang, PhD, Professor, Chief, Department of Pediatric Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan 430022, Hubei Province, China.
tshaotao83@hust.edu.cn
Received: June 9, 2026
Revised: June 29, 2026
Accepted: July 27, 2026
Published online: January 21, 2027
Processing time: 159 Days and 7.9 Hours
BACKGROUND
Postoperative Hirschsprung-associated enterocolitis (HAEC) is the most common and life-threatening complication after pull-through surgery for Hirschsprung disease (HSCR). Severe HAEC (sHAEC; Grade II and III) is associated with high morbidity and mortality, yet effective models for predicting postoperative sHAEC risk are currently rare.
AIM
To develop and validate a nomogram and online calculator for individualized prediction of postoperative risk of sHAEC.
METHODS
This multicenter retrospective study analyzed HSCR patients undergoing pull-through surgery. Using least absolute shrinkage and selection operator and logistic regression on a training cohort (n = 416), independent risk factors were identified. The nomogram was internally (n = 178) and externally (n = 303) validated. Performance was assessed using the area under the receiver operating characteristic curve, calibration curves, decision curve analysis, and clinical impact curve. An online calculator was created.
RESULTS
Among 897 patients, 175 (19.5%) developed sHAEC during ≥ 2 years` follow-up. Eight independent predictors emerged: (1) Preoperative malnutrition; (2) Down syndrome; (3) Preoperative respiratory infection; (4) Preoperative enterocolitis; (5) Clinical type; (6) Postoperative indwelling rectal tube; (7) Postoperative anastomotic fistula; and (8) Postoperative intestinal obstruction. The model demonstrated strong discrimination [area under the receiver operating characteristic curves: (1) Training 0.906; (2) Internal 0.882; and (3) External 0.842], excellent calibration, and high clinical utility. A web calculator was deployed (http://ms-haec.asia/).
CONCLUSION
The developed nomogram and online calculator, incorporating eight clinical variables, predicted postoperative sHAEC risk. This tool may assist in clinical decision-making and timely intervention, potentially improving outcomes in HSCR.
Core Tip: This multicenter study introduces a novel nomogram and web-based calculator to predict severe Hirschsprung-associated enterocolitis following pull-through surgery. Unlike prior models, it specifically targets American Pediatric Surgical Association Grade II and III Hirschsprung-associated enterocolitis. Integrating eight routine perioperative variables, it identifies postoperative intestinal obstruction as the strongest risk factor. Validated externally with excellent discrimination, this accessible tool empowers clinicians to individualize risk assessments. By identifying high-risk patients early, it facilitates targeted interventions and proactive decision-making, ultimately improving pediatric surgical outcomes.