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Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines
BACKGROUND: There is overwhelming volume of confirmed cases of COVID-19, despite this numerous knowledge gaps remain in the diagnosis, management, and prognostication of this novel coronavirus infection, making prevention and control a challenge. METHODS: This retrospective cohort study included pat...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767625/ http://dx.doi.org/10.1093/eurheartj/ehab724.2494 |
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author | Ong, R Chacon, C Javier, S |
author_facet | Ong, R Chacon, C Javier, S |
author_sort | Ong, R |
collection | PubMed |
description | BACKGROUND: There is overwhelming volume of confirmed cases of COVID-19, despite this numerous knowledge gaps remain in the diagnosis, management, and prognostication of this novel coronavirus infection, making prevention and control a challenge. METHODS: This retrospective cohort study included patients with real-time reverse transcriptase polymerase chain reaction (rRT-PCR)-confirmed COVID-19. Binary logistic regression was used to determine the association between the cardiac biomarkers and in-hospital mortality. ROC, AUC, and cutoff analyses were used to determine optimal cutoff values for the cardiac biomarkers. RESULTS: A total of 90 subjects with a complete panel of cardiac biomarkers out of the 224 rRT-PCR confirmed cases were included. The median age was 57 years (IQR, 47–67 years), majority were males. Sixty-six (77.6%) subjects survived while 19 (22.4%) expired. The most common presenting symptom was fever (75.6%), and the most common comorbidity was hypertension (67.8%). Spearman rho correlation analysis showed moderate positive association of high sensitivity troponin I (hsTnI) with in-hospital mortality (R, 0.434, p = <0.001). Multivariate binary logistic regression analysis showed that creatine kinase and hsTnI were independently associated with in-hospital mortality (OR, 4.103 [95% CI, 1.241–13.563], p=0.021; and OR, 7.899 [95% CI, 2.430–25.675], p=0.001, respectively). ROC curve analysis showed that hsTnI was a good predictor for in-hospital mortality (AUC, 0.829 [95% CI, 0.735–0.923], p = <0.001) and that creatine kinase was a poor predictor (AUC, 0.677 [95% CI, 0.531–0.823], p=0.018). Optimal cutoff point derived from the ROC curve for hsTnI was 0.010 ng/ml (J, 0.574) with a sensitivity of 84% (TPR, 0.842 [95% CI, 0.604–0.966]), specificity of 73% (TNR, 0.732 [95% CI, 0.614–0.386]), and an adjusted negative predictive value of 99% (Known prevalence*adjusted NPV, 0.989), a positive likelihood ratio of 20% (LR+, 3.147 [95% CI, 2.044–4.844]) and a negative likelihood ratio of 30% (LR−, 0.216 [95% CI, 0.076–0.615]). CONCLUSION: High sensitivity troponin I level was a good tool with a very high negative predictive value in significantly predicting in-hospital mortality among rRT-PCR positive COVID-19 patients. FUNDING ACKNOWLEDGEMENT: Type of funding sources: None. |
format | Online Article Text |
id | pubmed-8767625 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-87676252022-01-20 Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines Ong, R Chacon, C Javier, S Eur Heart J Abstract Supplement BACKGROUND: There is overwhelming volume of confirmed cases of COVID-19, despite this numerous knowledge gaps remain in the diagnosis, management, and prognostication of this novel coronavirus infection, making prevention and control a challenge. METHODS: This retrospective cohort study included patients with real-time reverse transcriptase polymerase chain reaction (rRT-PCR)-confirmed COVID-19. Binary logistic regression was used to determine the association between the cardiac biomarkers and in-hospital mortality. ROC, AUC, and cutoff analyses were used to determine optimal cutoff values for the cardiac biomarkers. RESULTS: A total of 90 subjects with a complete panel of cardiac biomarkers out of the 224 rRT-PCR confirmed cases were included. The median age was 57 years (IQR, 47–67 years), majority were males. Sixty-six (77.6%) subjects survived while 19 (22.4%) expired. The most common presenting symptom was fever (75.6%), and the most common comorbidity was hypertension (67.8%). Spearman rho correlation analysis showed moderate positive association of high sensitivity troponin I (hsTnI) with in-hospital mortality (R, 0.434, p = <0.001). Multivariate binary logistic regression analysis showed that creatine kinase and hsTnI were independently associated with in-hospital mortality (OR, 4.103 [95% CI, 1.241–13.563], p=0.021; and OR, 7.899 [95% CI, 2.430–25.675], p=0.001, respectively). ROC curve analysis showed that hsTnI was a good predictor for in-hospital mortality (AUC, 0.829 [95% CI, 0.735–0.923], p = <0.001) and that creatine kinase was a poor predictor (AUC, 0.677 [95% CI, 0.531–0.823], p=0.018). Optimal cutoff point derived from the ROC curve for hsTnI was 0.010 ng/ml (J, 0.574) with a sensitivity of 84% (TPR, 0.842 [95% CI, 0.604–0.966]), specificity of 73% (TNR, 0.732 [95% CI, 0.614–0.386]), and an adjusted negative predictive value of 99% (Known prevalence*adjusted NPV, 0.989), a positive likelihood ratio of 20% (LR+, 3.147 [95% CI, 2.044–4.844]) and a negative likelihood ratio of 30% (LR−, 0.216 [95% CI, 0.076–0.615]). CONCLUSION: High sensitivity troponin I level was a good tool with a very high negative predictive value in significantly predicting in-hospital mortality among rRT-PCR positive COVID-19 patients. FUNDING ACKNOWLEDGEMENT: Type of funding sources: None. Oxford University Press 2021-10-14 /pmc/articles/PMC8767625/ http://dx.doi.org/10.1093/eurheartj/ehab724.2494 Text en Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2021. For permissions, please email: journals.permissions@oup.com. https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_modelThis article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. |
spellingShingle | Abstract Supplement Ong, R Chacon, C Javier, S Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines |
title | Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines |
title_full | Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines |
title_fullStr | Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines |
title_full_unstemmed | Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines |
title_short | Cardiac biomarkers as prognosticators among SARS-CoV-19 patients in a tertiary hospital in Philippines |
title_sort | cardiac biomarkers as prognosticators among sars-cov-19 patients in a tertiary hospital in philippines |
topic | Abstract Supplement |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767625/ http://dx.doi.org/10.1093/eurheartj/ehab724.2494 |
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