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The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia

We sought to analyze the prognostic value of laboratory and clinical data, and an artificial intelligence (AI)-based algorithm for Coronavirus disease 2019 (COVID-19) severity scoring, on CT-scans of patients hospitalized with COVID-19. Moreover, we aimed to determine personalized probabilities of c...

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Autores principales: Szabó, István Viktor, Simon, Judit, Nardocci, Chiara, Kardos, Anna Sára, Nagy, Norbert, Abdelrahman, Renad-Heyam, Zsarnóczay, Emese, Fejér, Bence, Futácsi, Balázs, Müller, Veronika, Merkely, Béla, Maurovich-Horvat, Pál
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628928/
https://www.ncbi.nlm.nih.gov/pubmed/34842822
http://dx.doi.org/10.3390/tomography7040058
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author Szabó, István Viktor
Simon, Judit
Nardocci, Chiara
Kardos, Anna Sára
Nagy, Norbert
Abdelrahman, Renad-Heyam
Zsarnóczay, Emese
Fejér, Bence
Futácsi, Balázs
Müller, Veronika
Merkely, Béla
Maurovich-Horvat, Pál
author_facet Szabó, István Viktor
Simon, Judit
Nardocci, Chiara
Kardos, Anna Sára
Nagy, Norbert
Abdelrahman, Renad-Heyam
Zsarnóczay, Emese
Fejér, Bence
Futácsi, Balázs
Müller, Veronika
Merkely, Béla
Maurovich-Horvat, Pál
author_sort Szabó, István Viktor
collection PubMed
description We sought to analyze the prognostic value of laboratory and clinical data, and an artificial intelligence (AI)-based algorithm for Coronavirus disease 2019 (COVID-19) severity scoring, on CT-scans of patients hospitalized with COVID-19. Moreover, we aimed to determine personalized probabilities of clinical deterioration. Data of symptomatic patients with COVID-19 who underwent chest-CT-examination at the time of hospital admission between April and November 2020 were analyzed. COVID-19 severity score was automatically quantified for each pulmonary lobe as the percentage of affected lung parenchyma with the AI-based algorithm. Clinical deterioration was defined as a composite of admission to the intensive care unit, need for invasive mechanical ventilation, use of vasopressors or in-hospital mortality. In total 326 consecutive patients were included in the analysis (mean age 66.7 ± 15.3 years, 52.1% male) of whom 85 (26.1%) experienced clinical deterioration. In the multivariable regression analysis prior myocardial infarction (OR = 2.81, 95% CI = 1.12–7.04, p = 0.027), immunodeficiency (OR = 2.08, 95% CI = 1.02–4.25, p = 0.043), C-reactive protein (OR = 1.73, 95% CI = 1.32–2.33, p < 0.001) and AI-based COVID-19 severity score (OR = 1.08; 95% CI = 1.02–1.15, p = 0.013) appeared to be independent predictors of clinical deterioration. Personalized probability values were determined. AI-based COVID-19 severity score assessed at hospital admission can provide additional information about the prognosis of COVID-19, possibly serving as a useful tool for individualized risk-stratification.
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spelling pubmed-86289282021-11-30 The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia Szabó, István Viktor Simon, Judit Nardocci, Chiara Kardos, Anna Sára Nagy, Norbert Abdelrahman, Renad-Heyam Zsarnóczay, Emese Fejér, Bence Futácsi, Balázs Müller, Veronika Merkely, Béla Maurovich-Horvat, Pál Tomography Article We sought to analyze the prognostic value of laboratory and clinical data, and an artificial intelligence (AI)-based algorithm for Coronavirus disease 2019 (COVID-19) severity scoring, on CT-scans of patients hospitalized with COVID-19. Moreover, we aimed to determine personalized probabilities of clinical deterioration. Data of symptomatic patients with COVID-19 who underwent chest-CT-examination at the time of hospital admission between April and November 2020 were analyzed. COVID-19 severity score was automatically quantified for each pulmonary lobe as the percentage of affected lung parenchyma with the AI-based algorithm. Clinical deterioration was defined as a composite of admission to the intensive care unit, need for invasive mechanical ventilation, use of vasopressors or in-hospital mortality. In total 326 consecutive patients were included in the analysis (mean age 66.7 ± 15.3 years, 52.1% male) of whom 85 (26.1%) experienced clinical deterioration. In the multivariable regression analysis prior myocardial infarction (OR = 2.81, 95% CI = 1.12–7.04, p = 0.027), immunodeficiency (OR = 2.08, 95% CI = 1.02–4.25, p = 0.043), C-reactive protein (OR = 1.73, 95% CI = 1.32–2.33, p < 0.001) and AI-based COVID-19 severity score (OR = 1.08; 95% CI = 1.02–1.15, p = 0.013) appeared to be independent predictors of clinical deterioration. Personalized probability values were determined. AI-based COVID-19 severity score assessed at hospital admission can provide additional information about the prognosis of COVID-19, possibly serving as a useful tool for individualized risk-stratification. MDPI 2021-11-01 /pmc/articles/PMC8628928/ /pubmed/34842822 http://dx.doi.org/10.3390/tomography7040058 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Szabó, István Viktor
Simon, Judit
Nardocci, Chiara
Kardos, Anna Sára
Nagy, Norbert
Abdelrahman, Renad-Heyam
Zsarnóczay, Emese
Fejér, Bence
Futácsi, Balázs
Müller, Veronika
Merkely, Béla
Maurovich-Horvat, Pál
The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia
title The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia
title_full The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia
title_fullStr The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia
title_full_unstemmed The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia
title_short The Predictive Role of Artificial Intelligence-Based Chest CT Quantification in Patients with COVID-19 Pneumonia
title_sort predictive role of artificial intelligence-based chest ct quantification in patients with covid-19 pneumonia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628928/
https://www.ncbi.nlm.nih.gov/pubmed/34842822
http://dx.doi.org/10.3390/tomography7040058
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