Cargando…
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...
Autores principales: | , , , , , , |
---|---|
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 |
_version_ | 1784674377247227904 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8947178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT levenfusian theaifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT ullmannenrico theaifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT petrowskikatja theaifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT rosejutta theaifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT huberlarsc theaifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT stussihelblingmelina theaifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT schuurmansmacem theaifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT levenfusian aifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT ullmannenrico aifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT petrowskikatja aifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT rosejutta aifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT huberlarsc aifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT stussihelblingmelina aifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients AT schuurmansmacem aifellscoreasapredictorofcoronavirusdisease2019covid19severityandprogressioninhospitalizedpatients |