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External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital

Prognostic models to predict the deterioration and mortality risk in COVID-19 patients are utterly needed to assist in informed decision making. Most of these models, however, are at high risk of bias, model overfitting, and unclear reporting. Here, we aimed to externally validate the modified (urea...

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Autores principales: Wirth, Adriana, Goetschi, Andrea, Held, Ulrike, Sendoel, Ataman, Stuessi-Helbling, Melina, Huber, Lars Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139628/
https://www.ncbi.nlm.nih.gov/pubmed/35626285
http://dx.doi.org/10.3390/diagnostics12051129
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author Wirth, Adriana
Goetschi, Andrea
Held, Ulrike
Sendoel, Ataman
Stuessi-Helbling, Melina
Huber, Lars Christian
author_facet Wirth, Adriana
Goetschi, Andrea
Held, Ulrike
Sendoel, Ataman
Stuessi-Helbling, Melina
Huber, Lars Christian
author_sort Wirth, Adriana
collection PubMed
description Prognostic models to predict the deterioration and mortality risk in COVID-19 patients are utterly needed to assist in informed decision making. Most of these models, however, are at high risk of bias, model overfitting, and unclear reporting. Here, we aimed to externally validate the modified (urea was omitted) 4C Deterioration Model and 4C Mortality Score in a cohort of Swiss COVID-19 patients and, second, to evaluate whether the inclusion of the neutrophil-to-lymphocyte ratio (NLR) improves the predictive performance of the models. We conducted a retrospective single-centre study with adult patients hospitalized with COVID-19. Both prediction models were updated by including the NLR. Model performance was assessed via the models’ discriminatory performance (area under the curve, AUC), calibration (intercept and slope), and their performance overall (Brier score). For the validation of the 4C Deterioration Model and Mortality Score, 546 and 527 patients were included, respectively. In total, 133 (24.4%) patients met the definition of in-hospital deterioration. Discrimination of the 4C Deterioration Model was AUC = 0.78 (95% CI 0.73–0.82). A total of 55 (10.44%) patients died in hospital. Discrimination of the 4C Mortality Score was AUC = 0.85 (95% CI 0.79–0.89). There was no evidence for an incremental value of the NLR. Our data confirm the role of the modified 4C Deterioration Model and Mortality Score as reliable prediction tools for the risk of deterioration and mortality. There was no evidence that the inclusion of NLR improved model performance.
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spelling pubmed-91396282022-05-28 External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital Wirth, Adriana Goetschi, Andrea Held, Ulrike Sendoel, Ataman Stuessi-Helbling, Melina Huber, Lars Christian Diagnostics (Basel) Article Prognostic models to predict the deterioration and mortality risk in COVID-19 patients are utterly needed to assist in informed decision making. Most of these models, however, are at high risk of bias, model overfitting, and unclear reporting. Here, we aimed to externally validate the modified (urea was omitted) 4C Deterioration Model and 4C Mortality Score in a cohort of Swiss COVID-19 patients and, second, to evaluate whether the inclusion of the neutrophil-to-lymphocyte ratio (NLR) improves the predictive performance of the models. We conducted a retrospective single-centre study with adult patients hospitalized with COVID-19. Both prediction models were updated by including the NLR. Model performance was assessed via the models’ discriminatory performance (area under the curve, AUC), calibration (intercept and slope), and their performance overall (Brier score). For the validation of the 4C Deterioration Model and Mortality Score, 546 and 527 patients were included, respectively. In total, 133 (24.4%) patients met the definition of in-hospital deterioration. Discrimination of the 4C Deterioration Model was AUC = 0.78 (95% CI 0.73–0.82). A total of 55 (10.44%) patients died in hospital. Discrimination of the 4C Mortality Score was AUC = 0.85 (95% CI 0.79–0.89). There was no evidence for an incremental value of the NLR. Our data confirm the role of the modified 4C Deterioration Model and Mortality Score as reliable prediction tools for the risk of deterioration and mortality. There was no evidence that the inclusion of NLR improved model performance. MDPI 2022-05-03 /pmc/articles/PMC9139628/ /pubmed/35626285 http://dx.doi.org/10.3390/diagnostics12051129 Text en © 2022 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
Wirth, Adriana
Goetschi, Andrea
Held, Ulrike
Sendoel, Ataman
Stuessi-Helbling, Melina
Huber, Lars Christian
External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital
title External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital
title_full External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital
title_fullStr External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital
title_full_unstemmed External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital
title_short External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital
title_sort external validation of the modified 4c deterioration model and 4c mortality score for covid-19 patients in a swiss tertiary hospital
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139628/
https://www.ncbi.nlm.nih.gov/pubmed/35626285
http://dx.doi.org/10.3390/diagnostics12051129
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