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Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19

BACKGROUND: Whether the National Early Warning Score 2 (NEWS2) can effectively discriminate the severe/critical state of patients with coronavirus disease 2019 (COVID-19) at the prehospital stage remains unknown. We aimed to assess the performance of NEWS2 in rapidly discriminating severe/critical C...

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Autores principales: Li, Chen, Wang, Kaili, Wu, Liang, Song, Bing, Tan, Junyuan, Su, Haibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392258/
https://www.ncbi.nlm.nih.gov/pubmed/37489620
http://dx.doi.org/10.1080/07853890.2023.2239829
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author Li, Chen
Wang, Kaili
Wu, Liang
Song, Bing
Tan, Junyuan
Su, Haibin
author_facet Li, Chen
Wang, Kaili
Wu, Liang
Song, Bing
Tan, Junyuan
Su, Haibin
author_sort Li, Chen
collection PubMed
description BACKGROUND: Whether the National Early Warning Score 2 (NEWS2) can effectively discriminate the severe/critical state of patients with coronavirus disease 2019 (COVID-19) at the prehospital stage remains unknown. We aimed to assess the performance of NEWS2 in rapidly discriminating severe/critical COVID-19 and its relationship with prehospital medical services. METHODS: Six illness severity scores of 414 patients were calculated at the prehospital stage. Receiver operating characteristic curves were generated to explore the ability of these scores to discriminate severe/critical patients from mild/moderate patients. A logistic regression analysis was conducted to evaluate independent predictors associated with severe/critical state. RESULTS: The age, numbers of comorbidities, prehospital care workload, consumption of medical human resources, and illness severity scores of severe/critical patients were higher than those of mild/moderate patients (p < 0.05). When NEWS2 scores >2, the sensitivity, specificity, positive predictive value, and negative predictive value were 93.5%, 90.7%, 74.1%, and 98.0%, respectively. The C-statistic of NEWS2 (0.963) was higher than that of quick Sequential Organ Failure Assessment (0.680, p < 0.001), CRB-65 (0.879, p < 0.001), Rapid Acute Physiology Score (0.692, p < 0.001), and Rapid Emergency Medicine Score (0.879, p < 0.001). NEWS2 was positively correlated with the numbers of prehospital treatment measures (r = 0.732, p < 0.001), numbers of medical staff (r = 0.615, p < 0.001), and total transport time (r = 0.595, p < 0.001). Age ≥65 years (OR = 5.43, p = 0.016), hypertension (OR = 5.39, p < 0.001), active malignancy (OR = 5.94, p = 0.005), and NEWS2 scores >2 (OR = 124.88, p < 0.001) were independent predictors to discriminate severe/critical patients. Oxygen saturation (SpO(2)) (OR =1.87, p < 0.001) was the unique independent predictor to discriminate false positive patients from true positive patients. CONCLUSIONS: Prehospital NEWS2 can accurately and rapidly discriminate severe/critical COVID-19 during the Omicron variant wave. High levels of NEWS2 indicate an increase in prehospital care workload and consumption of medical human resources.
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spelling pubmed-103922582023-08-02 Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19 Li, Chen Wang, Kaili Wu, Liang Song, Bing Tan, Junyuan Su, Haibin Ann Med Infectious Diseases BACKGROUND: Whether the National Early Warning Score 2 (NEWS2) can effectively discriminate the severe/critical state of patients with coronavirus disease 2019 (COVID-19) at the prehospital stage remains unknown. We aimed to assess the performance of NEWS2 in rapidly discriminating severe/critical COVID-19 and its relationship with prehospital medical services. METHODS: Six illness severity scores of 414 patients were calculated at the prehospital stage. Receiver operating characteristic curves were generated to explore the ability of these scores to discriminate severe/critical patients from mild/moderate patients. A logistic regression analysis was conducted to evaluate independent predictors associated with severe/critical state. RESULTS: The age, numbers of comorbidities, prehospital care workload, consumption of medical human resources, and illness severity scores of severe/critical patients were higher than those of mild/moderate patients (p < 0.05). When NEWS2 scores >2, the sensitivity, specificity, positive predictive value, and negative predictive value were 93.5%, 90.7%, 74.1%, and 98.0%, respectively. The C-statistic of NEWS2 (0.963) was higher than that of quick Sequential Organ Failure Assessment (0.680, p < 0.001), CRB-65 (0.879, p < 0.001), Rapid Acute Physiology Score (0.692, p < 0.001), and Rapid Emergency Medicine Score (0.879, p < 0.001). NEWS2 was positively correlated with the numbers of prehospital treatment measures (r = 0.732, p < 0.001), numbers of medical staff (r = 0.615, p < 0.001), and total transport time (r = 0.595, p < 0.001). Age ≥65 years (OR = 5.43, p = 0.016), hypertension (OR = 5.39, p < 0.001), active malignancy (OR = 5.94, p = 0.005), and NEWS2 scores >2 (OR = 124.88, p < 0.001) were independent predictors to discriminate severe/critical patients. Oxygen saturation (SpO(2)) (OR =1.87, p < 0.001) was the unique independent predictor to discriminate false positive patients from true positive patients. CONCLUSIONS: Prehospital NEWS2 can accurately and rapidly discriminate severe/critical COVID-19 during the Omicron variant wave. High levels of NEWS2 indicate an increase in prehospital care workload and consumption of medical human resources. Taylor & Francis 2023-07-25 /pmc/articles/PMC10392258/ /pubmed/37489620 http://dx.doi.org/10.1080/07853890.2023.2239829 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
spellingShingle Infectious Diseases
Li, Chen
Wang, Kaili
Wu, Liang
Song, Bing
Tan, Junyuan
Su, Haibin
Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19
title Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19
title_full Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19
title_fullStr Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19
title_full_unstemmed Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19
title_short Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19
title_sort prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with covid-19
topic Infectious Diseases
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392258/
https://www.ncbi.nlm.nih.gov/pubmed/37489620
http://dx.doi.org/10.1080/07853890.2023.2239829
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