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The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7707101/ https://www.ncbi.nlm.nih.gov/pubmed/33313029 http://dx.doi.org/10.3389/fped.2020.592892 |
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author | Stiel, Carolin Elrod, Julia Klinke, Michaela Herrmann, Jochen Junge, Carl-Martin Ghadban, Tarik Reinshagen, Konrad Boettcher, Michael |
author_facet | Stiel, Carolin Elrod, Julia Klinke, Michaela Herrmann, Jochen Junge, Carl-Martin Ghadban, Tarik Reinshagen, Konrad Boettcher, Michael |
author_sort | Stiel, Carolin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7707101 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77071012020-12-11 The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study Stiel, Carolin Elrod, Julia Klinke, Michaela Herrmann, Jochen Junge, Carl-Martin Ghadban, Tarik Reinshagen, Konrad Boettcher, Michael Front Pediatr Pediatrics 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. Frontiers Media S.A. 2020-11-17 /pmc/articles/PMC7707101/ /pubmed/33313029 http://dx.doi.org/10.3389/fped.2020.592892 Text en Copyright © 2020 Stiel, Elrod, Klinke, Herrmann, Junge, Ghadban, Reinshagen and Boettcher. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pediatrics Stiel, Carolin Elrod, Julia Klinke, Michaela Herrmann, Jochen Junge, Carl-Martin Ghadban, Tarik Reinshagen, Konrad Boettcher, Michael The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study |
title | The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study |
title_full | The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study |
title_fullStr | The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study |
title_full_unstemmed | The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study |
title_short | The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study |
title_sort | modified heidelberg and the ai appendicitis score are superior to current scores in predicting appendicitis in children: a two-center cohort study |
topic | Pediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7707101/ https://www.ncbi.nlm.nih.gov/pubmed/33313029 http://dx.doi.org/10.3389/fped.2020.592892 |
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