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Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices

We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and d...

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Autores principales: Asteris, Panagiotis G., Kokoris, Styliani, Gavriilaki, Eleni, Tsoukalas, Markos Z., Houpas, Panagiotis, Paneta, Maria, Koutzas, Andreas, Argyropoulos, Theodoros, Alkayem, Nizar Faisal, Armaghani, Danial J., Bardhan, Abidhan, Cavaleri, Liborio, Cao, Maosen, Mansouri, Iman, Mohammed, Ahmed Salih, Samui, Pijush, Gerber, Gloria, Boumpas, Dimitrios T., Tsantes, Argyrios, Terpos, Evangelos, Dimopoulos, Meletios A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797218/
https://www.ncbi.nlm.nih.gov/pubmed/36586431
http://dx.doi.org/10.1016/j.clim.2022.109218
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author Asteris, Panagiotis G.
Kokoris, Styliani
Gavriilaki, Eleni
Tsoukalas, Markos Z.
Houpas, Panagiotis
Paneta, Maria
Koutzas, Andreas
Argyropoulos, Theodoros
Alkayem, Nizar Faisal
Armaghani, Danial J.
Bardhan, Abidhan
Cavaleri, Liborio
Cao, Maosen
Mansouri, Iman
Mohammed, Ahmed Salih
Samui, Pijush
Gerber, Gloria
Boumpas, Dimitrios T.
Tsantes, Argyrios
Terpos, Evangelos
Dimopoulos, Meletios A.
author_facet Asteris, Panagiotis G.
Kokoris, Styliani
Gavriilaki, Eleni
Tsoukalas, Markos Z.
Houpas, Panagiotis
Paneta, Maria
Koutzas, Andreas
Argyropoulos, Theodoros
Alkayem, Nizar Faisal
Armaghani, Danial J.
Bardhan, Abidhan
Cavaleri, Liborio
Cao, Maosen
Mansouri, Iman
Mohammed, Ahmed Salih
Samui, Pijush
Gerber, Gloria
Boumpas, Dimitrios T.
Tsantes, Argyrios
Terpos, Evangelos
Dimopoulos, Meletios A.
author_sort Asteris, Panagiotis G.
collection PubMed
description We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and development of ANN models. We developed a new alpha-index to assess association of each parameter with outcome. We used 166 records for training of computational simulations (training), 41 for documentation of computational simulations (validation), and 41 for reliability check of computational simulations (testing). The first five laboratory indices ranked by importance were Neutrophil-to-lymphocyte ratio, Lactate Dehydrogenase, Fibrinogen, Albumin, and D-Dimers. The best ANN based on these indices achieved accuracy 95.97%, precision 90.63%, sensitivity 93.55%. and F1-score 92.06%, verified in the validation cohort. Our preliminary findings reveal for the first time an ANN to predict ICU hospitalization accurately and early, using only 5 easily accessible laboratory indices.
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spelling pubmed-97972182022-12-29 Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices Asteris, Panagiotis G. Kokoris, Styliani Gavriilaki, Eleni Tsoukalas, Markos Z. Houpas, Panagiotis Paneta, Maria Koutzas, Andreas Argyropoulos, Theodoros Alkayem, Nizar Faisal Armaghani, Danial J. Bardhan, Abidhan Cavaleri, Liborio Cao, Maosen Mansouri, Iman Mohammed, Ahmed Salih Samui, Pijush Gerber, Gloria Boumpas, Dimitrios T. Tsantes, Argyrios Terpos, Evangelos Dimopoulos, Meletios A. Clin Immunol Article We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and development of ANN models. We developed a new alpha-index to assess association of each parameter with outcome. We used 166 records for training of computational simulations (training), 41 for documentation of computational simulations (validation), and 41 for reliability check of computational simulations (testing). The first five laboratory indices ranked by importance were Neutrophil-to-lymphocyte ratio, Lactate Dehydrogenase, Fibrinogen, Albumin, and D-Dimers. The best ANN based on these indices achieved accuracy 95.97%, precision 90.63%, sensitivity 93.55%. and F1-score 92.06%, verified in the validation cohort. Our preliminary findings reveal for the first time an ANN to predict ICU hospitalization accurately and early, using only 5 easily accessible laboratory indices. Elsevier Inc. 2023-01 2022-12-29 /pmc/articles/PMC9797218/ /pubmed/36586431 http://dx.doi.org/10.1016/j.clim.2022.109218 Text en © 2022 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Asteris, Panagiotis G.
Kokoris, Styliani
Gavriilaki, Eleni
Tsoukalas, Markos Z.
Houpas, Panagiotis
Paneta, Maria
Koutzas, Andreas
Argyropoulos, Theodoros
Alkayem, Nizar Faisal
Armaghani, Danial J.
Bardhan, Abidhan
Cavaleri, Liborio
Cao, Maosen
Mansouri, Iman
Mohammed, Ahmed Salih
Samui, Pijush
Gerber, Gloria
Boumpas, Dimitrios T.
Tsantes, Argyrios
Terpos, Evangelos
Dimopoulos, Meletios A.
Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
title Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
title_full Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
title_fullStr Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
title_full_unstemmed Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
title_short Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
title_sort early prediction of covid-19 outcome using artificial intelligence techniques and only five laboratory indices
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797218/
https://www.ncbi.nlm.nih.gov/pubmed/36586431
http://dx.doi.org/10.1016/j.clim.2022.109218
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