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Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department
BACKGROUND: The study aimed to compare the prognostic accuracy of six different severity-of-illness scoring systems for predicting in-hospital mortality among patients with confirmed SARS-COV2 who presented to the emergency department (ED). The scoring systems assessed were worthing physiological sc...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Jaypee Brothers Medical Publishers
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291668/ https://www.ncbi.nlm.nih.gov/pubmed/37378368 http://dx.doi.org/10.5005/jp-journals-10071-24463 |
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author | Rahmatinejad, Zahra Hoseini, Benyamin Reihani, Hamidreza Hanna, Ameen Abu Pourmand, Ali Tabatabaei, Seyyed Mohammad Rahmatinejad, Fatemeh Eslami, Saeid |
author_facet | Rahmatinejad, Zahra Hoseini, Benyamin Reihani, Hamidreza Hanna, Ameen Abu Pourmand, Ali Tabatabaei, Seyyed Mohammad Rahmatinejad, Fatemeh Eslami, Saeid |
author_sort | Rahmatinejad, Zahra |
collection | PubMed |
description | BACKGROUND: The study aimed to compare the prognostic accuracy of six different severity-of-illness scoring systems for predicting in-hospital mortality among patients with confirmed SARS-COV2 who presented to the emergency department (ED). The scoring systems assessed were worthing physiological score (WPS), early warning score (EWS), rapid acute physiology score (RAPS), rapid emergency medicine score (REMS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA). MATERIALS AND METHODS: A cohort study was conducted using data obtained from electronic medical records of 6,429 confirmed SARS-COV2 patients presenting to the ED. Logistic regression models were fitted on the original severity-of-illness scores to assess the models’ performance using the Area Under the Curve for ROC (AUC-ROC) and Precision-Recall curves (AUC-PR), Brier Score (BS), and calibration plots were used to assess the models’ performance. Bootstrap samples with multiple imputations were used for internal validation. RESULTS: The mean age of the patients was 64 years (IQR:50–76) and 57.5% were male. The WPS, REMS, and NEWS models had AUROC of 0.714, 0.705, and 0.701, respectively. The poorest performance was observed in the RAPS model, with an AUROC of 0.601. The BS for the NEWS, qSOFA, EWS, WPS, RAPS, and REMS was 0.18, 0.09, 0.03, 0.14, 0.15, and 0.11 respectively. Excellent calibration was obtained for the NEWS, while the other models had proper calibration. CONCLUSION: The WPS, REMS, and NEWS have a fair discriminatory performance and may assist in risk stratification for SARS-COV2 patients presenting to the ED. Generally, underlying diseases and most vital signs are positively associated with mortality and were different between the survivors and non-survivors. HOW TO CITE THIS ARTICLE: Rahmatinejad Z, Hoseini B, Reihani H, Hanna AA, Pourmand A, Tabatabaei SM, et al. Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department. Indian J Crit Care Med 2023;27(6):416–425. |
format | Online Article Text |
id | pubmed-10291668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Jaypee Brothers Medical Publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-102916682023-06-27 Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department Rahmatinejad, Zahra Hoseini, Benyamin Reihani, Hamidreza Hanna, Ameen Abu Pourmand, Ali Tabatabaei, Seyyed Mohammad Rahmatinejad, Fatemeh Eslami, Saeid Indian J Crit Care Med Original Article BACKGROUND: The study aimed to compare the prognostic accuracy of six different severity-of-illness scoring systems for predicting in-hospital mortality among patients with confirmed SARS-COV2 who presented to the emergency department (ED). The scoring systems assessed were worthing physiological score (WPS), early warning score (EWS), rapid acute physiology score (RAPS), rapid emergency medicine score (REMS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA). MATERIALS AND METHODS: A cohort study was conducted using data obtained from electronic medical records of 6,429 confirmed SARS-COV2 patients presenting to the ED. Logistic regression models were fitted on the original severity-of-illness scores to assess the models’ performance using the Area Under the Curve for ROC (AUC-ROC) and Precision-Recall curves (AUC-PR), Brier Score (BS), and calibration plots were used to assess the models’ performance. Bootstrap samples with multiple imputations were used for internal validation. RESULTS: The mean age of the patients was 64 years (IQR:50–76) and 57.5% were male. The WPS, REMS, and NEWS models had AUROC of 0.714, 0.705, and 0.701, respectively. The poorest performance was observed in the RAPS model, with an AUROC of 0.601. The BS for the NEWS, qSOFA, EWS, WPS, RAPS, and REMS was 0.18, 0.09, 0.03, 0.14, 0.15, and 0.11 respectively. Excellent calibration was obtained for the NEWS, while the other models had proper calibration. CONCLUSION: The WPS, REMS, and NEWS have a fair discriminatory performance and may assist in risk stratification for SARS-COV2 patients presenting to the ED. Generally, underlying diseases and most vital signs are positively associated with mortality and were different between the survivors and non-survivors. HOW TO CITE THIS ARTICLE: Rahmatinejad Z, Hoseini B, Reihani H, Hanna AA, Pourmand A, Tabatabaei SM, et al. Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department. Indian J Crit Care Med 2023;27(6):416–425. Jaypee Brothers Medical Publishers 2023-06 /pmc/articles/PMC10291668/ /pubmed/37378368 http://dx.doi.org/10.5005/jp-journals-10071-24463 Text en Copyright © 2023; The Author(s). https://creativecommons.org/licenses/by-nc/4.0/© The Author(s). 2023 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and non-commercial reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Original Article Rahmatinejad, Zahra Hoseini, Benyamin Reihani, Hamidreza Hanna, Ameen Abu Pourmand, Ali Tabatabaei, Seyyed Mohammad Rahmatinejad, Fatemeh Eslami, Saeid Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department |
title | Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department |
title_full | Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department |
title_fullStr | Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department |
title_full_unstemmed | Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department |
title_short | Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department |
title_sort | comparison of six scoring systems for predicting in-hospital mortality among patients with sars-cov2 presenting to the emergency department |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291668/ https://www.ncbi.nlm.nih.gov/pubmed/37378368 http://dx.doi.org/10.5005/jp-journals-10071-24463 |
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