RESUMO
Introduction: Testicular torsion (TT) is a common emergency that warrants immediate exploration to prevent infertility or testicular loss. To improve diagnostic reliability, various scoring systems have been published. The aim of this study was to evaluate and validate different testicular torsion scores in a large cohort of children with acute scrotum. Methods: Retrospective analysis of all male children that were admitted for acute scrotum at the Pediatric Surgery Department of the Altonaer Kinderkrankenhaus and University medical Center Hamburg-Eppendorf from 01/2013 to 03/2019. Two testicular torsion scores (Boettcher Alert Score, Testicular Workup for Ischemia and Suspected Torsion Score) were applied to all data sets. Furthermore, an artificial intelligence (AI)-based score was developed and compared to the two current scores. Results: In total, 460 boys were included in the study. Of those, 48 (10.4%) had TT. Children with TT suffered most often from short duration of pain, nausea and vomiting, high riding testicle and absent cremasteric reflex. The BALS and the AI-based score had excellent predictive values and all patients with TT would have been detected. Conclusion: The BAL and the AI score show excellent predictive capabilities and may be used to identify all cases of TT in a pediatric population. The scores are easy to apply. As the BALS was slightly better, we advocate to use this score but to validate our findings in prospective multicenter studies.
RESUMO
Background: Acute appendicitis represents the most frequent reason for abdominal surgery in children. Since diagnosis can be challenging various scoring systems have been published. The aim of this study was to evaluate and validate (and improve) different appendicitis scores in a very large cohort of children with abdominal pain. Methods: Retrospective analysis of all children that have been hospitalized due to suspected appendicitis at the Pediatric Surgery Department of the Altonaer Children's Hospital and University Medical Center Hamburg-Eppendorf from 01/2018 until 11/2019. Four different appendicitis scores (Heidelberg Appendicitis Score, Alvarado Score, Pediatric Appendicitis Score and Tzanakis Score) were applied to all data sets. Furthermore, the best score was improved and artificial intelligence (AI) was applied and compare the current scores. Results: In 23 months, 463 patients were included in the study. Of those 348 (75.2%) were operated for suspected appendicitis and in 336 (96.6%) patients the diagnosis was confirmed histopathologically. The best predictors of appendicitis (simple and perforated) were rebound tenderness, cough/hopping tenderness, ultrasound, and laboratory results. After modifying the HAS, it provided excellent results for simple (PPV 95.0%, NPV 70.0%) and very good for perforated appendicitis (PPV 34.4%, NPV 93.8%), outperforming all other appendicitis score. Discussion: The modified HAS and the AI score show excellent predictive capabilities and may be used to identify most cases of appendicitis and more important to rule out perforated appendicitis. The new scores outperform all other scores and are simple to apply. The modified HAS comprises five features that can all be assessed in the emergency department as opposed to current scores that are relatively complex to utilize in a clinical setting as they include of up to eight features with various weighting factors. In conclusion, the modified HAS and the AI score may be used to identify children with appendicitis, yet prospective studies to validate our findings in a large mutli-center cohorts are needed.
