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Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques
In December 2019, cases of pneumonia were detected in Wuhan, China, which were caused by the highly contagious coronavirus. This study is aimed at comparing the confusion regarding the selection of effective diagnostic methods to make a mutual comparison among existing SARS-CoV-2 diagnostic tests an...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411452/ https://www.ncbi.nlm.nih.gov/pubmed/32802146 http://dx.doi.org/10.1155/2020/1560250 |
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author | Sayan, Murat Sarigul Yildirim, Figen Sanlidag, Tamer Uzun, Berna Uzun Ozsahin, Dilber Ozsahin, Ilker |
author_facet | Sayan, Murat Sarigul Yildirim, Figen Sanlidag, Tamer Uzun, Berna Uzun Ozsahin, Dilber Ozsahin, Ilker |
author_sort | Sayan, Murat |
collection | PubMed |
description | In December 2019, cases of pneumonia were detected in Wuhan, China, which were caused by the highly contagious coronavirus. This study is aimed at comparing the confusion regarding the selection of effective diagnostic methods to make a mutual comparison among existing SARS-CoV-2 diagnostic tests and at determining the most effective one. Based on available published evidence and clinical practice, diagnostic tests of coronavirus disease (COVID-19) were evaluated by multi-criteria decision-making (MCDM) methods, namely, fuzzy preference ranking organization method for enrichment evaluation (fuzzy PROMETHEE) and fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS). Computerized tomography of chest (chest CT), the detection of viral nucleic acid by polymerase chain reaction, cell culture, CoV-19 antigen detection, CoV-19 antibody IgM, CoV-19 antibody IgG, and chest X-ray were evaluated by linguistic fuzzy scale to compare among the diagnostic tests. This scale consists of selected parameters that possessed different weights which were determined by the experts' opinions of the field. The results of our study with both proposed MCDM methods indicated that the most effective diagnosis method of COVID-19 was chest CT. It is interesting to note that the methods that are consistently used in the diagnosis of viral diseases were ranked in second place for the diagnosis of COVID-19. However, each country should use appropriate diagnostic solutions according to its own resources. Our findings also show which diagnostic systems can be used in combination. |
format | Online Article Text |
id | pubmed-7411452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-74114522020-08-13 Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques Sayan, Murat Sarigul Yildirim, Figen Sanlidag, Tamer Uzun, Berna Uzun Ozsahin, Dilber Ozsahin, Ilker Comput Math Methods Med Research Article In December 2019, cases of pneumonia were detected in Wuhan, China, which were caused by the highly contagious coronavirus. This study is aimed at comparing the confusion regarding the selection of effective diagnostic methods to make a mutual comparison among existing SARS-CoV-2 diagnostic tests and at determining the most effective one. Based on available published evidence and clinical practice, diagnostic tests of coronavirus disease (COVID-19) were evaluated by multi-criteria decision-making (MCDM) methods, namely, fuzzy preference ranking organization method for enrichment evaluation (fuzzy PROMETHEE) and fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS). Computerized tomography of chest (chest CT), the detection of viral nucleic acid by polymerase chain reaction, cell culture, CoV-19 antigen detection, CoV-19 antibody IgM, CoV-19 antibody IgG, and chest X-ray were evaluated by linguistic fuzzy scale to compare among the diagnostic tests. This scale consists of selected parameters that possessed different weights which were determined by the experts' opinions of the field. The results of our study with both proposed MCDM methods indicated that the most effective diagnosis method of COVID-19 was chest CT. It is interesting to note that the methods that are consistently used in the diagnosis of viral diseases were ranked in second place for the diagnosis of COVID-19. However, each country should use appropriate diagnostic solutions according to its own resources. Our findings also show which diagnostic systems can be used in combination. Hindawi 2020-08-06 /pmc/articles/PMC7411452/ /pubmed/32802146 http://dx.doi.org/10.1155/2020/1560250 Text en Copyright © 2020 Murat Sayan et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Sayan, Murat Sarigul Yildirim, Figen Sanlidag, Tamer Uzun, Berna Uzun Ozsahin, Dilber Ozsahin, Ilker Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques |
title | Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques |
title_full | Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques |
title_fullStr | Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques |
title_full_unstemmed | Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques |
title_short | Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques |
title_sort | capacity evaluation of diagnostic tests for covid-19 using multicriteria decision-making techniques |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411452/ https://www.ncbi.nlm.nih.gov/pubmed/32802146 http://dx.doi.org/10.1155/2020/1560250 |
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