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The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients

Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has caused a global burden for health care systems due to high morbidity and mortality rates, leading to caseloads that episodically surpass hospital resources. Due to different disease manifestations, the triage of patients at high risk for a...

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Autores principales: Levenfus, Ian, Ullmann, Enrico, Petrowski, Katja, Rose, Jutta, Huber, Lars C., Stüssi-Helbling, Melina, Schuurmans, Macé M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947178/
https://www.ncbi.nlm.nih.gov/pubmed/35328157
http://dx.doi.org/10.3390/diagnostics12030604
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author Levenfus, Ian
Ullmann, Enrico
Petrowski, Katja
Rose, Jutta
Huber, Lars C.
Stüssi-Helbling, Melina
Schuurmans, Macé M.
author_facet Levenfus, Ian
Ullmann, Enrico
Petrowski, Katja
Rose, Jutta
Huber, Lars C.
Stüssi-Helbling, Melina
Schuurmans, Macé M.
author_sort Levenfus, Ian
collection PubMed
description Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has caused a global burden for health care systems due to high morbidity and mortality rates, leading to caseloads that episodically surpass hospital resources. Due to different disease manifestations, the triage of patients at high risk for a poor outcome continues to be a major challenge for clinicians. The AIFELL score was developed as a simple decision instrument for emergency rooms to distinguish COVID-19 patients in severe disease stages from less severe COVID-19 and non-COVID-19 cases. In the present study, we aimed to evaluate the AIFELL score as a prediction tool for clinical deterioration and disease severity in hospitalized COVID-19 patients. During the second wave of the COVID-19 pandemic in Switzerland, we analyzed consecutively hospitalized patients at the Triemli Hospital Zurich from the end of November 2020 until mid-February 2021. Statistical analyses were performed for group comparisons and to evaluate significance. AIFELL scores of patients developing severe COVID-19 stages IIb and III during hospitalization were significantly higher upon admission compared to those patients not surpassing stages I and IIa. Group comparisons indicated significantly different AIFELL scores between each stage. In conclusion, the AIFELL score at admission was useful to predict the disease severity and progression in hospitalized COVID-19 patients.
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spelling pubmed-89471782022-03-25 The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients Levenfus, Ian Ullmann, Enrico Petrowski, Katja Rose, Jutta Huber, Lars C. Stüssi-Helbling, Melina Schuurmans, Macé M. Diagnostics (Basel) Article Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has caused a global burden for health care systems due to high morbidity and mortality rates, leading to caseloads that episodically surpass hospital resources. Due to different disease manifestations, the triage of patients at high risk for a poor outcome continues to be a major challenge for clinicians. The AIFELL score was developed as a simple decision instrument for emergency rooms to distinguish COVID-19 patients in severe disease stages from less severe COVID-19 and non-COVID-19 cases. In the present study, we aimed to evaluate the AIFELL score as a prediction tool for clinical deterioration and disease severity in hospitalized COVID-19 patients. During the second wave of the COVID-19 pandemic in Switzerland, we analyzed consecutively hospitalized patients at the Triemli Hospital Zurich from the end of November 2020 until mid-February 2021. Statistical analyses were performed for group comparisons and to evaluate significance. AIFELL scores of patients developing severe COVID-19 stages IIb and III during hospitalization were significantly higher upon admission compared to those patients not surpassing stages I and IIa. Group comparisons indicated significantly different AIFELL scores between each stage. In conclusion, the AIFELL score at admission was useful to predict the disease severity and progression in hospitalized COVID-19 patients. MDPI 2022-02-27 /pmc/articles/PMC8947178/ /pubmed/35328157 http://dx.doi.org/10.3390/diagnostics12030604 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
Levenfus, Ian
Ullmann, Enrico
Petrowski, Katja
Rose, Jutta
Huber, Lars C.
Stüssi-Helbling, Melina
Schuurmans, Macé M.
The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients
title The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients
title_full The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients
title_fullStr The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients
title_full_unstemmed The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients
title_short The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients
title_sort aifell score as a predictor of coronavirus disease 2019 (covid-19) severity and progression in hospitalized patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947178/
https://www.ncbi.nlm.nih.gov/pubmed/35328157
http://dx.doi.org/10.3390/diagnostics12030604
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