Please use this identifier to cite or link to this item:
10.2478/prolas-2022-0092
Title: | Surgical and non-surgical treatment of paediatric appendicitis : can algorithms help us to predict perforation? |
Authors: | Eņģelis, Arnis Kakar, Mohit Zviedre, Astra Laizāns, Paulis Zurmutaī, Timurs Bormotovs, Jurijs Pētersons, Aigars Department of Paediatric Surgery Department of Doctoral Studies |
Keywords: | diagnostic;treatment algorithm;biomarkers;acute appendicitis;3.2 Clinical medicine;1.1. Scientific article indexed in Web of Science and/or Scopus database |
Issue Date: | 10-Dec-2022 |
Citation: | Eņģelis , A , Kakar , M , Zviedre , A , Laizāns , P , Zurmutaī , T , Bormotovs , J & Pētersons , A 2022 , ' Surgical and non-surgical treatment of paediatric appendicitis : can algorithms help us to predict perforation? ' , Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences. , vol. 76 , no. 5/6 , pp. 595-601 . https://doi.org/10.2478/prolas-2022-0092 |
Abstract: | The recent interest in and evidence of non-surgical treatment with antibiotic therapy has led to the recurring issue of differentiating acute no-complicated appendicitis (AnA) and acute complicated appendicitis (AcA) when these are presented in an emergency department. To create the initial version of an acute appendicitis (AA) diagnostic and treatment algorithm, we analysed treatment results of 178 children with AnA and AcA treated at the Children's Clinical University Hospital in Rīga, in the period between 2010 and 2013. Evaluation of the clinical symptoms, laboratory and radiological findings was included in development of the algorithm. The algorithm was created in 2016 and accepted by the hospital administration. We present the algorithm's updated version of 2020. The introduction of diagnostic scores and algorithms has standardised and improved the diagnosis of paediatric AA. New diagnostic tests with higher sensitivity and specificity may improve the accuracy of diagnostic algorithms. Measuring multiple effective biomarkers simultaneously may improve the accuracy of diagnostic algorithms and predict the severity of paediatric AA. Machine learning algorithms may be able to process a much larger amount of data and provide a faster conclusion, helping the surgeon make the right decision in diagnosing appendicitis in children and prevent unnecessary surgery. |
Description: | Publisher Copyright: © 2022 Arnis Engelis et al., published by Sciendo. |
DOI: | 10.2478/prolas-2022-0092 |
ISSN: | 2255-890X |
Appears in Collections: | Research outputs from Pure / Zinātniskās darbības rezultāti no ZDIS Pure |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Surgical_and_non_surgical_treatment.pdf | 2.33 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.