<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

Surgical and non-surgical treatment of paediatric appendicitis: can algorithms help us to predict perforation?

Children’s Clinical University Hospital

Department of Anaesthesiology and Reanimatology

Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The recent interest in and evidence of non-surgical treatment with antibiotic therapy has led to the recurring issue of differentiating acute no-complicated...

Surgical and non-surgical treatment of paediatric appendicitis: can algorithms help us to predict perforation?

Data publikacji: 10 gru 2022

Zakres stron: 595 - 601

DOI: https://doi.org/10.2478/prolas-2022-0092

Słowa kluczowe
diagnostic, treatment algorithm, biomarkers, nacute appendicitis

© 2022 Arnis Eņģelis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Surgical and non-surgical treatment of paediatric appendicitis: can algorithms help us to predict perforation?

Data publikacji: 10 gru 2022

Zakres stron: 595 - 601

DOI: https://doi.org/10.2478/prolas-2022-0092

Słowa kluczowediagnostic, treatment algorithm, biomarkers, nacute appendicitis

© 2022 Arnis Eņģelis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
diagnostic, treatment algorithm, biomarkers, nacute appendicitis