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Influence of social deprivation index on in-hospital outcomes of COVID-19
While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospita...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887560/ https://www.ncbi.nlm.nih.gov/pubmed/36720999 http://dx.doi.org/10.1038/s41598-023-28362-0 |
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author | Goyal, Parag Schenck, Edward Wu, Yiyuan Zhang, Yongkang Visaria, Aayush Orlander, Duncan Xi, Wenna Díaz, Iván Morozyuk, Dmitry Weiner, Mark Kaushal, Rainu Banerjee, Samprit |
author_facet | Goyal, Parag Schenck, Edward Wu, Yiyuan Zhang, Yongkang Visaria, Aayush Orlander, Duncan Xi, Wenna Díaz, Iván Morozyuk, Dmitry Weiner, Mark Kaushal, Rainu Banerjee, Samprit |
author_sort | Goyal, Parag |
collection | PubMed |
description | While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient’s residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70–0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71–0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79–0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79–0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important. |
format | Online Article Text |
id | pubmed-9887560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98875602023-01-31 Influence of social deprivation index on in-hospital outcomes of COVID-19 Goyal, Parag Schenck, Edward Wu, Yiyuan Zhang, Yongkang Visaria, Aayush Orlander, Duncan Xi, Wenna Díaz, Iván Morozyuk, Dmitry Weiner, Mark Kaushal, Rainu Banerjee, Samprit Sci Rep Article While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient’s residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70–0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71–0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79–0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79–0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important. Nature Publishing Group UK 2023-01-31 /pmc/articles/PMC9887560/ /pubmed/36720999 http://dx.doi.org/10.1038/s41598-023-28362-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Goyal, Parag Schenck, Edward Wu, Yiyuan Zhang, Yongkang Visaria, Aayush Orlander, Duncan Xi, Wenna Díaz, Iván Morozyuk, Dmitry Weiner, Mark Kaushal, Rainu Banerjee, Samprit Influence of social deprivation index on in-hospital outcomes of COVID-19 |
title | Influence of social deprivation index on in-hospital outcomes of COVID-19 |
title_full | Influence of social deprivation index on in-hospital outcomes of COVID-19 |
title_fullStr | Influence of social deprivation index on in-hospital outcomes of COVID-19 |
title_full_unstemmed | Influence of social deprivation index on in-hospital outcomes of COVID-19 |
title_short | Influence of social deprivation index on in-hospital outcomes of COVID-19 |
title_sort | influence of social deprivation index on in-hospital outcomes of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887560/ https://www.ncbi.nlm.nih.gov/pubmed/36720999 http://dx.doi.org/10.1038/s41598-023-28362-0 |
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