Comorbidity and Sociodemographic determinants in COVID-19 Mortality in an US Urban Healthcare System

DOI record: { "DOI": "10.1101/2020.06.11.20128926", "URL": "http://dx.doi.org/10.1101/2020.06.11.20128926", "abstract": "<jats:title>ABSTRACT</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>New York City is the US epicenter of the coronavirus disease 2019 (COVID-19) pandemic. Early international data indicated that comorbidity contributes significantly to poor prognosis and fatality in patients infected with SARS-CoV-2. It is not known to what degree medical comorbidity and sociodemographic determinants impact COVID-19 mortality in the US.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Evaluation of de-identified electronic health records of 7,592 COVID-19 patients confirmed by SARS-CoV-2 lab tests in New York City. Medical comorbidites and outcome of mortality, and other covariates, including clinical, sociodemographic, and medication measures were assessed by bivariate and multivariate logistic regression models.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Of common comorbid conditions (hypertension, chronic kidney disease, chronic obstructive pulmonary disease, asthma, obesity, diabetes, HIV, cancer), when adjusted for covariates, chronic kidney disease remained significantly associated with increased odds of mortality. Patients who had more than one comorbidities, former smokers, treated with Azithromycin without Hydroxychloroquine, reside within the boroughs of Brooklyn and Queens Higher had higher odds of death.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Increasing numbers of comorbid factors increase COVID-19 mortality, but several clinical and sociodemographic factors can mitigate risk. Continued evaluation of COVID-19 in large diverse populations is important to characterize individuals at risk and improve clinical outcomes.</jats:p></jats:sec>", "accepted": { "date-parts": [ [ 2020, 6, 12 ] ] }, "author": [ { "ORCID": "http://orcid.org/0000-0003-0938-5157", "affiliation": [], "authenticated-orcid": false, "family": "Wang", "given": "An-Li", "sequence": "first" }, { "affiliation": [], "family": "Zhong", "given": "Xiaobo", "sequence": "additional" }, { "affiliation": [], "family": "Hurd", "given": "Yasmin L", "sequence": "additional" } ], "container-title": [], "content-domain": { "crossmark-restriction": false, "domain": [] }, "created": { "date-parts": [ [ 2020, 6, 12 ] ], "date-time": "2020-06-12T22:45:11Z", "timestamp": 1592001911000 }, "deposited": { "date-parts": [ [ 2022, 10, 28 ] ], "date-time": "2022-10-28T05:45:41Z", "timestamp": 1666935941000 }, "group-title": "Infectious Diseases (except HIV/AIDS)", "indexed": { "date-parts": [ [ 2024, 1, 1 ] ], "date-time": "2024-01-01T17:50:12Z", "timestamp": 1704131412069 }, "institution": [ { "name": "medRxiv" } ], "is-referenced-by-count": 10, "issued": { "date-parts": [ [ 2020, 6, 12 ] ] }, "link": [ { "URL": "https://syndication.highwire.org/content/doi/10.1101/2020.06.11.20128926", "content-type": "unspecified", "content-version": "vor", "intended-application": "similarity-checking" } ], "member": "246", "original-title": [], "posted": { "date-parts": [ [ 2020, 6, 12 ] ] }, "prefix": "10.1101", "published": { "date-parts": [ [ 2020, 6, 12 ] ] }, "publisher": "Cold Spring Harbor Laboratory", "reference": [ { "key": "2021010205300523000_2020.06.11.20128926v1.1", "unstructured": "City of New York. 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