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Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data
The current study assessed performance of the new Veterans Affairs (VA) women cardiovascular disease (CVD) risk score in predicting women veterans’ 60-day CVD event risk using VA COVID-19 shared cohort data. The study data included 17,264 women veterans—9658 White, 6088 African American, and 1518 Hi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8508488/ https://www.ncbi.nlm.nih.gov/pubmed/34639306 http://dx.doi.org/10.3390/ijerph181910005 |
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author | Jeon-Slaughter, Haekyung Chen, Xiaofei Ramanan, Bala Tsai, Shirling |
author_facet | Jeon-Slaughter, Haekyung Chen, Xiaofei Ramanan, Bala Tsai, Shirling |
author_sort | Jeon-Slaughter, Haekyung |
collection | PubMed |
description | The current study assessed performance of the new Veterans Affairs (VA) women cardiovascular disease (CVD) risk score in predicting women veterans’ 60-day CVD event risk using VA COVID-19 shared cohort data. The study data included 17,264 women veterans—9658 White, 6088 African American, and 1518 Hispanic women veterans—ever treated at US VA hospitals and clinics between 24 February and 25 November 2020. The VA women CVD risk score discriminated patients with CVD events at 60 days from those without CVD events with accuracy (area under the curve) of 78%, 50%, and 83% for White, African American, and Hispanic women veterans, respectively. The VA women CVD risk score itself showed good accuracy in predicting CVD events at 60 days for White and Hispanic women veterans, while it performed poorly for African American women veterans. The future studies are needed to identify non-traditional factors and biomarkers associated with increased CVD risk specific to African American women and incorporate them to the CVD risk assessment. |
format | Online Article Text |
id | pubmed-8508488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85084882021-10-13 Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data Jeon-Slaughter, Haekyung Chen, Xiaofei Ramanan, Bala Tsai, Shirling Int J Environ Res Public Health Article The current study assessed performance of the new Veterans Affairs (VA) women cardiovascular disease (CVD) risk score in predicting women veterans’ 60-day CVD event risk using VA COVID-19 shared cohort data. The study data included 17,264 women veterans—9658 White, 6088 African American, and 1518 Hispanic women veterans—ever treated at US VA hospitals and clinics between 24 February and 25 November 2020. The VA women CVD risk score discriminated patients with CVD events at 60 days from those without CVD events with accuracy (area under the curve) of 78%, 50%, and 83% for White, African American, and Hispanic women veterans, respectively. The VA women CVD risk score itself showed good accuracy in predicting CVD events at 60 days for White and Hispanic women veterans, while it performed poorly for African American women veterans. The future studies are needed to identify non-traditional factors and biomarkers associated with increased CVD risk specific to African American women and incorporate them to the CVD risk assessment. MDPI 2021-09-23 /pmc/articles/PMC8508488/ /pubmed/34639306 http://dx.doi.org/10.3390/ijerph181910005 Text en © 2021 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 Jeon-Slaughter, Haekyung Chen, Xiaofei Ramanan, Bala Tsai, Shirling Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data |
title | Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data |
title_full | Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data |
title_fullStr | Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data |
title_full_unstemmed | Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data |
title_short | Assessing Performance of the Veterans Affairs Women Cardiovascular Risk Model in Predicting a Short-Term Risk of Cardiovascular Disease Incidence Using United States Veterans Affairs COVID-19 Shared Data |
title_sort | assessing performance of the veterans affairs women cardiovascular risk model in predicting a short-term risk of cardiovascular disease incidence using united states veterans affairs covid-19 shared data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8508488/ https://www.ncbi.nlm.nih.gov/pubmed/34639306 http://dx.doi.org/10.3390/ijerph181910005 |
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