ArticleDiagnostics (Basel, Switzerland)2023
Diagnostic Algorithm Based on Machine Learning to Predict Complicated Appendicitis in Children Using CT, Laboratory, and Clinical Features.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Habitat Radiomics and Machine Learning for Preoperative Three-class Classification of Pediatric Acute Appendicitis: A Dual-center Study with External Validation.Journal of imaging informatics in medicine · 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
- Dharma: A novel, clinically grounded machine learning framework for pediatric appendicitis-Diagnosis, severity assessment and evidence-based clinical decision support.PLOS digital health · 2026Article
- Application value of abdominal ultrasonography in the diagnosis of pediatric patients aged 3-12 years with acute appendicitis.World journal of gastrointestinal surgery · 2025Article
- Progress in the application of machine learning in CT diagnosis of acute appendicitis.Abdominal radiology (New York) · 2025Review
- Diagnostic Accuracy of a Machine Learning-Derived Appendicitis Score in Children: A Multicenter Validation Study.Children (Basel, Switzerland) · 2025Article
- National Trends in Hospitalizations for Appendectomy in Children, 2001-2017.Turkish journal of anaesthesiology and reanimation · 2025Article
- Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling.BMC gastroenterology · 2025Article
- Analysis of Incidence and Risk Factors of Complicated Acute Appendicitis in Children: Evidence From a Tertiary Pediatric Center.International journal of pediatrics · 2025Article
- Using shock index, pediatric age adjusted (SIPA) to predict prolonged length of stay in perforated appendicitis: a retrospective review.Pediatric surgery international · 2024Article
- MaskAppendix: Backbone-Enriched Mask R-CNN Based on Grad-CAM for Automatic Appendix Segmentation.Diagnostics (Basel, Switzerland) · 2024Article
- Are Preoperative CT Findings Useful in Predicting the Duration of Laparoscopic Appendectomy in Pediatric Patients? A Single Center Study.Journal of clinical medicine · 2024Article
- Predicting Complicated Appendicitis in Children: Pros and Cons of a New Score Combining Clinical Signs, Laboratory Values, and Ultrasound Images (CLU Score).Diagnostics (Basel, Switzerland) · 2023Article
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Abstract
To establish a diagnostic algorithm for predicting complicated appendicitis in children based on CT and clinical features.
methodsThis retrospective study included 315 children (<18 years old) who were diagnosed with acute appendicitis and underwent appendectomy between January 2014 and December 2018. A decision tree algorithm was used to identify important features associated with the condition and to develop a diagnostic algorithm for predicting complicated appendicitis, including CT and clinical findings in the development cohort (
resultsAll patients with periappendiceal abscesses, periappendiceal inflammatory masses, and free air on CT were diagnosed with complicated appendicitis. In addition, intraluminal air, transverse diameter of the appendix, and ascites were identified as important CT findings for predicting complicated appendicitis. C-reactive protein (CRP) level, white blood cell (WBC) count, erythrocyte sedimentation rate (ESR), and body temperature also showed important associations with complicated appendicitis. The AUC, sensitivity, and specificity of the diagnostic algorithm comprising features were 0.91 (95% CI, 0.86-0.95), 91.8% (84.5-96.4), and 90.0% (82.4-95.1) in the development cohort, and 0.7 (0.63-0.84), 85.9% (75.0-93.4), and 58.5% (44.1-71.9) in test cohort, respectively.
conclusionWe propose a diagnostic algorithm based on a decision tree model using CT and clinical findings. This algorithm can be used to differentiate between complicated and noncomplicated appendicitis and to provide an appropriate treatment plan for children with acute appendicitis.
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