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Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter
IMPORTANCE: As the United States continues to accumulate COVID-19 cases and deaths, and disparities persist, defining the impact of risk factors for poor outcomes across patient groups is imperative. OBJECTIVE: Our objective is to use real-world healthcare data to quantify the impact of demographic,...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043490/ https://www.ncbi.nlm.nih.gov/pubmed/33851193 http://dx.doi.org/10.1101/2021.04.06.21254728 |
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author | Manohar, Jyothi Abedian, Sajjad Martini, Rachel Kulm, Scott Salvatore, Mirella Ho, Kaylee Christos, Paul Campion, Thomas Imperato-McGinley, Julianne Ibrahim, Said Evering, Teresa H. Phillips, Erica Tamimi, Rulla Bea, Vivian Balogun, Onyinye D. Sboner, Andrea Elemento, Olivier Davis, Melissa Boneta |
author_facet | Manohar, Jyothi Abedian, Sajjad Martini, Rachel Kulm, Scott Salvatore, Mirella Ho, Kaylee Christos, Paul Campion, Thomas Imperato-McGinley, Julianne Ibrahim, Said Evering, Teresa H. Phillips, Erica Tamimi, Rulla Bea, Vivian Balogun, Onyinye D. Sboner, Andrea Elemento, Olivier Davis, Melissa Boneta |
author_sort | Manohar, Jyothi |
collection | PubMed |
description | IMPORTANCE: As the United States continues to accumulate COVID-19 cases and deaths, and disparities persist, defining the impact of risk factors for poor outcomes across patient groups is imperative. OBJECTIVE: Our objective is to use real-world healthcare data to quantify the impact of demographic, clinical, and social determinants associated with adverse COVID-19 outcomes, to identify high-risk scenarios and dynamics of risk among racial and ethnic groups. DESIGN: A retrospective cohort of COVID-19 patients diagnosed between March 1 and August 20, 2020. Fully adjusted logistical regression models for hospitalization, severe disease and mortality outcomes across 1-the entire cohort and 2- within self-reported race/ethnicity groups. SETTING: Three sites of the NewYork-Presbyterian health care system serving all boroughs of New York City. Data was obtained through automated data abstraction from electronic medical records. PARTICIPANTS: During the study timeframe, 110,498 individuals were tested for SARS-CoV-2 in the NewYork-Presbyterian health care system; 11,930 patients were confirmed for COVID-19 by RT-PCR or covid-19 clinical diagnosis. MAIN OUTCOMES AND MEASURES: The predictors of interest were patient race/ethnicity, and covariates included demographics, comorbidities, and census tract neighborhood socio-economic status. The outcomes of interest were COVID-19 hospitalization, severe disease, and death. RESULTS: Of confirmed COVID-19 patients, 4,895 were hospitalized, 1,070 developed severe disease and 1,654 suffered COVID-19 related death. Clinical factors had stronger impacts than social determinants and several showed race-group specificities, which varied among outcomes. The most significant factors in our all-patients models included: age over 80 (OR=5.78, p= 2.29x10(−24)) and hypertension (OR=1.89, p=1.26x10(−10)) having the highest impact on hospitalization, while Type 2 Diabetes was associated with all three outcomes (hospitalization: OR=1.48, p=1.39x10(−04); severe disease: OR=1.46, p=4.47x10(−09); mortality: OR=1.27, p=0.001). In race-specific models, COPD increased risk of hospitalization only in Non-Hispanics (NH)-Whites (OR=2.70, p=0.009). Obesity (BMI 30+) showed race-specific risk with severe disease NH-Whites (OR=1.48, p=0.038) and NH-Blacks (OR=1.77, p=0.025). For mortality, Cancer was the only risk factor in Hispanics (OR=1.97, p=0.043), and heart failure was only a risk in NH-Asians (OR=2.62, p=0.001). CONCLUSIONS AND RELEVANCE. Comorbidities were more influential on COVID-19 outcomes than social determinants, suggesting clinical factors are more predictive of adverse trajectory than social factors. |
format | Online Article Text |
id | pubmed-8043490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-80434902021-04-14 Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter Manohar, Jyothi Abedian, Sajjad Martini, Rachel Kulm, Scott Salvatore, Mirella Ho, Kaylee Christos, Paul Campion, Thomas Imperato-McGinley, Julianne Ibrahim, Said Evering, Teresa H. Phillips, Erica Tamimi, Rulla Bea, Vivian Balogun, Onyinye D. Sboner, Andrea Elemento, Olivier Davis, Melissa Boneta medRxiv Article IMPORTANCE: As the United States continues to accumulate COVID-19 cases and deaths, and disparities persist, defining the impact of risk factors for poor outcomes across patient groups is imperative. OBJECTIVE: Our objective is to use real-world healthcare data to quantify the impact of demographic, clinical, and social determinants associated with adverse COVID-19 outcomes, to identify high-risk scenarios and dynamics of risk among racial and ethnic groups. DESIGN: A retrospective cohort of COVID-19 patients diagnosed between March 1 and August 20, 2020. Fully adjusted logistical regression models for hospitalization, severe disease and mortality outcomes across 1-the entire cohort and 2- within self-reported race/ethnicity groups. SETTING: Three sites of the NewYork-Presbyterian health care system serving all boroughs of New York City. Data was obtained through automated data abstraction from electronic medical records. PARTICIPANTS: During the study timeframe, 110,498 individuals were tested for SARS-CoV-2 in the NewYork-Presbyterian health care system; 11,930 patients were confirmed for COVID-19 by RT-PCR or covid-19 clinical diagnosis. MAIN OUTCOMES AND MEASURES: The predictors of interest were patient race/ethnicity, and covariates included demographics, comorbidities, and census tract neighborhood socio-economic status. The outcomes of interest were COVID-19 hospitalization, severe disease, and death. RESULTS: Of confirmed COVID-19 patients, 4,895 were hospitalized, 1,070 developed severe disease and 1,654 suffered COVID-19 related death. Clinical factors had stronger impacts than social determinants and several showed race-group specificities, which varied among outcomes. The most significant factors in our all-patients models included: age over 80 (OR=5.78, p= 2.29x10(−24)) and hypertension (OR=1.89, p=1.26x10(−10)) having the highest impact on hospitalization, while Type 2 Diabetes was associated with all three outcomes (hospitalization: OR=1.48, p=1.39x10(−04); severe disease: OR=1.46, p=4.47x10(−09); mortality: OR=1.27, p=0.001). In race-specific models, COPD increased risk of hospitalization only in Non-Hispanics (NH)-Whites (OR=2.70, p=0.009). Obesity (BMI 30+) showed race-specific risk with severe disease NH-Whites (OR=1.48, p=0.038) and NH-Blacks (OR=1.77, p=0.025). For mortality, Cancer was the only risk factor in Hispanics (OR=1.97, p=0.043), and heart failure was only a risk in NH-Asians (OR=2.62, p=0.001). CONCLUSIONS AND RELEVANCE. Comorbidities were more influential on COVID-19 outcomes than social determinants, suggesting clinical factors are more predictive of adverse trajectory than social factors. Cold Spring Harbor Laboratory 2021-04-07 /pmc/articles/PMC8043490/ /pubmed/33851193 http://dx.doi.org/10.1101/2021.04.06.21254728 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Manohar, Jyothi Abedian, Sajjad Martini, Rachel Kulm, Scott Salvatore, Mirella Ho, Kaylee Christos, Paul Campion, Thomas Imperato-McGinley, Julianne Ibrahim, Said Evering, Teresa H. Phillips, Erica Tamimi, Rulla Bea, Vivian Balogun, Onyinye D. Sboner, Andrea Elemento, Olivier Davis, Melissa Boneta Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter |
title | Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter |
title_full | Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter |
title_fullStr | Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter |
title_full_unstemmed | Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter |
title_short | Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter |
title_sort | social and clinical determinants of covid-19 outcomes: modeling real-world data from a pandemic epicenter |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043490/ https://www.ncbi.nlm.nih.gov/pubmed/33851193 http://dx.doi.org/10.1101/2021.04.06.21254728 |
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