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Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction
INTRODUCTION: Including race as a biological construct in risk prediction models may guide clinical decisions in ways that cause harm and widen racial disparities. This study reports on using race versus social determinants of health (SDoH) in predicting the associations between cardiometabolic dise...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal of Preventive Medicine. Published by Elsevier Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9212800/ https://www.ncbi.nlm.nih.gov/pubmed/35725136 http://dx.doi.org/10.1016/j.amepre.2022.01.034 |
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author | Howell, Carrie R. Zhang, Li Yi, Nengjun Mehta, Tapan Garvey, W. Timothy Cherrington, Andrea L. |
author_facet | Howell, Carrie R. Zhang, Li Yi, Nengjun Mehta, Tapan Garvey, W. Timothy Cherrington, Andrea L. |
author_sort | Howell, Carrie R. |
collection | PubMed |
description | INTRODUCTION: Including race as a biological construct in risk prediction models may guide clinical decisions in ways that cause harm and widen racial disparities. This study reports on using race versus social determinants of health (SDoH) in predicting the associations between cardiometabolic disease severity (assessed using cardiometabolic disease staging) and COVID-19 hospitalization. METHODS: Electronic medical record data on patients with a positive COVID-19 polymerase chain reaction test in 2020 and a previous encounter in the electronic medical record where cardiometabolic disease staging clinical data (BMI, blood glucose, blood pressure, high-density lipoprotein cholesterol, and triglycerides) were available from 2017 to 2020, were analyzed in 2021. Associations between cardiometabolic disease staging and COVID-19 hospitalization adding race and SDoH (individual and neighborhood level [e.g., Social Vulnerability Index]) in different models were examined. Area under the curve was used to assess predictive performance. RESULTS: A total of 2,745 patients were included (mean age of 58 years, 59% female, 47% Black). In the cardiometabolic disease staging model, area under the curve was 0.767 vs 0.777 when race was included. Adding SDoH to the cardiometabolic model improved the area under the curve to 0.809 (p<0.001), whereas the addition of SDoH and race increased the area under the curve to 0.811. In race-stratified models, the area under the curve for non-Hispanic Blacks was 0.781, whereas the model for non-Hispanic Whites performed better with an area under the curve of 0.821. CONCLUSIONS: Cardiometabolic disease staging was predictive of hospitalization after a positive COVID-19 test. Adding race did not markedly increase the predictive ability; however, adding SDoH to the model improved the area under the curve to ≥0.80. Future research should include SDoH with biological variables in prediction modeling to capture social experience of race. |
format | Online Article Text |
id | pubmed-9212800 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Journal of Preventive Medicine. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92128002022-06-22 Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction Howell, Carrie R. Zhang, Li Yi, Nengjun Mehta, Tapan Garvey, W. Timothy Cherrington, Andrea L. Am J Prev Med Research Brief INTRODUCTION: Including race as a biological construct in risk prediction models may guide clinical decisions in ways that cause harm and widen racial disparities. This study reports on using race versus social determinants of health (SDoH) in predicting the associations between cardiometabolic disease severity (assessed using cardiometabolic disease staging) and COVID-19 hospitalization. METHODS: Electronic medical record data on patients with a positive COVID-19 polymerase chain reaction test in 2020 and a previous encounter in the electronic medical record where cardiometabolic disease staging clinical data (BMI, blood glucose, blood pressure, high-density lipoprotein cholesterol, and triglycerides) were available from 2017 to 2020, were analyzed in 2021. Associations between cardiometabolic disease staging and COVID-19 hospitalization adding race and SDoH (individual and neighborhood level [e.g., Social Vulnerability Index]) in different models were examined. Area under the curve was used to assess predictive performance. RESULTS: A total of 2,745 patients were included (mean age of 58 years, 59% female, 47% Black). In the cardiometabolic disease staging model, area under the curve was 0.767 vs 0.777 when race was included. Adding SDoH to the cardiometabolic model improved the area under the curve to 0.809 (p<0.001), whereas the addition of SDoH and race increased the area under the curve to 0.811. In race-stratified models, the area under the curve for non-Hispanic Blacks was 0.781, whereas the model for non-Hispanic Whites performed better with an area under the curve of 0.821. CONCLUSIONS: Cardiometabolic disease staging was predictive of hospitalization after a positive COVID-19 test. Adding race did not markedly increase the predictive ability; however, adding SDoH to the model improved the area under the curve to ≥0.80. Future research should include SDoH with biological variables in prediction modeling to capture social experience of race. American Journal of Preventive Medicine. Published by Elsevier Inc. 2022-07 2022-06-17 /pmc/articles/PMC9212800/ /pubmed/35725136 http://dx.doi.org/10.1016/j.amepre.2022.01.034 Text en © 2022 American Journal of Preventive Medicine. Published by Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Research Brief Howell, Carrie R. Zhang, Li Yi, Nengjun Mehta, Tapan Garvey, W. Timothy Cherrington, Andrea L. Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction |
title | Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction |
title_full | Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction |
title_fullStr | Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction |
title_full_unstemmed | Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction |
title_short | Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction |
title_sort | race versus social determinants of health in covid-19 hospitalization prediction |
topic | Research Brief |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9212800/ https://www.ncbi.nlm.nih.gov/pubmed/35725136 http://dx.doi.org/10.1016/j.amepre.2022.01.034 |
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