ArticleFrontiers in pediatrics2024
Nomogram prediction model for length of hospital stay following laparoscopic appendectomy in pediatric patients: a retrospective study.
Article in Frontiers in pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Impact of peritoneal fluid culture findings on postoperative outcomes in pediatric patients with complicated appendicitis.Pediatric surgery international · 2026Article
- Machine Learning-Predicted Length of Hospital Stay in Pediatric Appendicitis: An Exploratory Comparative Study of Clinical and Ultrasound-Based Models with Explainable Artificial Intelligence and Bayesian Analysis.Medical sciences (Basel, Switzerland) · 2026Article
- Explainable Machine Learning for Predicting Complicated Appendicitis and Expected Hospital Length of Stay in Children: An Exploratory Single-Center Study.Medicina (Kaunas, Lithuania) · 2026Article
- Neutrophil percentage-to-albumin ratio for preoperative risk stratification of complicated appendicitis in children: a retrospective study.BMC gastroenterology · 2025Article
- Association between preoperative neutrophil-to-lymphocyte ratio and length of stay in pediatric patients undergoing laparoscopic appendectomy: a retrospective cohort study.BMC pediatrics · 2025Article
- Development of a prediction model for antimicrobial stewardship pharmacy consultations to identify high-risk pediatric patients: a retrospective study across two centers.BMC infectious diseases · 2025Article
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5 authors.
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Abstract
Objective: The aim of this research was to develop and internally validate a nomogram for forecasting the length of hospital stay following laparoscopic appendectomy in pediatric patients diagnosed with appendicitis. Methods: We developed a prediction model based on a training dataset of 415 pediatric patients with appendicitis, and hospitalization data were collected retrospectively from January 2021 and December 2022. The primary outcome measure in this study was hospital length of stay (LOS), with prolonged LOS defined as admission for a duration equal to or exceeding the 75th percentile of LOS, including the discharge day. Risk factor analysis was conducted through univariate and multivariate logistic regression analyses. Based on the regression coefficients, a nomogram prediction model was developed. The discriminative performance of the predicting model was evaluated using the C-index, and an adjusted C-index was computed through bootstrapping validation. Calibration curves were generated to assess the accuracy of the nomogram. Decision curve analysis was conducted to determine the clinical utility of the predicting model. Results: Predictors contained in the prediction nomogram included Age, neutrophil-to-lymphocyte ratio, C-reactive protein level, operative time, appendiceal fecalith, and drainage tube. The C-index of the prediction nomogram was determined to be 0.873 (95% CI: 0.838-0.908), with a corrected C-index of 0.8625 obtained through bootstrapping validation (1,000 resamples), indicating the model's favorable discrimination. Calibration curves illustrated a strong agreement between predicted and observed outcomes. According to the decision curve analysis of the nomogram, the predictive model demonstrates a net benefit at threshold probabilities exceeding 2%. Conclusion: This nomogram, incorporating variables such as Age, neutrophil-to-lymphocyte ratio, C-reactive protein level, operative time, appendiceal fecalith, and drainage tube, offers a convenient method for assessing the duration of hospitalization in pediatric patients with appendicitis.
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