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Background <p>Acute complicated appendicitis in children is associated with substantial morbidity, including prolonged hospitalization, abscess formation, higher rates of surgical site infection, postoperative ileus, chronic abdominal pain, and increased need for reoperation. Preoperative identification of pediatric patients at elevated risk for complicated appendicitis is essential to optimize surgical management and improve patient and family counseling. This study aimed to identify reliable preoperative predictors of acute complicated appendicitis in childrenand to develop an accurate, clinically practical predictive nomogram.</p> Methods <p>We conducted a retrospective analysis of 735 pediatric patients diagnosed with acute appendicitis who underwent surgical treatment at our institutionbetween October 2019 and September 2025. Patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio. An external validation cohort included 450 patients from another institution. Feature selection was performed using LASSO (Least Absolute Shrinkage and Selection Operator) regression to identify the most significant predictive variables. A multivariate logistic regression model was then developed, incorporating the coefficientsof these selected features to create a predictive nomogram. The model’s performance was rigorously assessed across all cohorts in terms of discriminative ability, calibration, and clinical utility.</p> Results <p>Nine significant preoperative predictors were identified: neutrophil-to-lymphocyte ratio, C-reactive protein level, serum chloride, fibrinogen, appendicolith, free peritoneal effusion, onset time, peritoneal irritation signs, and fever(≥ 38&#xa0;°C). The nomogram demonstrated robust discriminatory performance, with area under the curve (AUC) values of 0.922, 0.916, and 0.906 in the training, internal validation, and external validation cohorts, respectively. Additionally, the model showed excellent calibration and significant clinical utility, as demonstrated by decision curve analysis across all cohorts.</p> Conclusions <p>This study successfully developed and validated a high-performance nomogram that effectively distinguishes between acute complicated and uncomplicated appendicitis in children. This tool may assist clinicians in early risk stratification and could contribute to improved patient outcomes.</p>

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Integration of clinical information for identification of gangrenous or perforated appendicitis in children: a multicenter retrospective cohort study with external validation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Honglong Ma,
  • Junjun Ouyang,
  • Jie Liu,
  • Rui Tang,
  • Xiao Wang,
  • Zhenjie Chu,
  • Zhiyuan Jin,
  • Bangzhi Sui,
  • Guangyu Wang,
  • Jin Chen,
  • Lang Cheng

摘要

Background

Acute complicated appendicitis in children is associated with substantial morbidity, including prolonged hospitalization, abscess formation, higher rates of surgical site infection, postoperative ileus, chronic abdominal pain, and increased need for reoperation. Preoperative identification of pediatric patients at elevated risk for complicated appendicitis is essential to optimize surgical management and improve patient and family counseling. This study aimed to identify reliable preoperative predictors of acute complicated appendicitis in childrenand to develop an accurate, clinically practical predictive nomogram.

Methods

We conducted a retrospective analysis of 735 pediatric patients diagnosed with acute appendicitis who underwent surgical treatment at our institutionbetween October 2019 and September 2025. Patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio. An external validation cohort included 450 patients from another institution. Feature selection was performed using LASSO (Least Absolute Shrinkage and Selection Operator) regression to identify the most significant predictive variables. A multivariate logistic regression model was then developed, incorporating the coefficientsof these selected features to create a predictive nomogram. The model’s performance was rigorously assessed across all cohorts in terms of discriminative ability, calibration, and clinical utility.

Results

Nine significant preoperative predictors were identified: neutrophil-to-lymphocyte ratio, C-reactive protein level, serum chloride, fibrinogen, appendicolith, free peritoneal effusion, onset time, peritoneal irritation signs, and fever(≥ 38 °C). The nomogram demonstrated robust discriminatory performance, with area under the curve (AUC) values of 0.922, 0.916, and 0.906 in the training, internal validation, and external validation cohorts, respectively. Additionally, the model showed excellent calibration and significant clinical utility, as demonstrated by decision curve analysis across all cohorts.

Conclusions

This study successfully developed and validated a high-performance nomogram that effectively distinguishes between acute complicated and uncomplicated appendicitis in children. This tool may assist clinicians in early risk stratification and could contribute to improved patient outcomes.