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社会决定因素可预测 20899 例接受 COVID-19 调查的多民族队列患者的数据结局。

Social Determinants Predict Outcomes in Data From a Multi-Ethnic Cohort of 20,899 Patients Investigated for COVID-19.

机构信息

Department of Urology, Icahn School of Medicine at Mount Sinai Hospitals, New York, NY, United States.

The Center for Scientific Diversity, The Icahn School of Medicine at Mount Sinai, New York, NY, United States.

出版信息

Front Public Health. 2020 Nov 24;8:571364. doi: 10.3389/fpubh.2020.571364. eCollection 2020.

DOI:10.3389/fpubh.2020.571364
PMID:33324596
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7722480/
Abstract

The COVID-19 pandemic exploits existing inequalities in social determinants of health (SDOH) in disease burden and access to healthcare. Few studies have examined these emerging disparities using indicators of SDOH. To evaluate predictors of COVID-19 test positivity, morbidity, and mortality and their implications for inequalities in SDOH and for future policies and health care improvements. A cross sectional analysis was performed on all patients tested for COVID-19 on the basis of symptoms with either a history of travel to at risk regions or close contact with a confirmed case, across the Mount Sinai Health System (MSHS) up until April 26th 2020. Primary outcome was death from COVID-19 and secondary outcomes were test positivity, and morbidity (e.g., hospitalization and intubation caused by COVID-19). Of 20,899 tested patients, 8,928 tested positive, 1,701 were hospitalized, 684 were intubated, and 1,179 died from COVID-19. Age, sex, race/ethnicity, New York City borough (derived from first 3 digits of zip-code), and English as preferred language were significant predictors of test positivity, hospitalization, intubation and COVID-19 mortality following multivariable logistic regression analyses. People residing in poorer boroughs were more likely to be burdened by and die from COVID-19. Our results highlight the importance of integrating comprehensive SDOH data into healthcare efforts with at-risk patient populations.

摘要

新冠疫情利用了社会决定健康因素(SDOH)在疾病负担和医疗保健获取方面的现有不平等。很少有研究使用 SDOH 指标来检查这些新出现的差异。为了评估 COVID-19 检测阳性、发病率和死亡率的预测因素,以及它们对 SDOH 不平等的影响,以及对未来政策和医疗保健改善的影响。对截至 2020 年 4 月 26 日,在西奈山卫生系统(MSHS)内,根据有旅行史或与确诊病例有密切接触史的症状,对所有接受 COVID-19 检测的患者进行了横断面分析。主要结局是 COVID-19 死亡,次要结局是检测阳性和发病率(例如 COVID-19 引起的住院和插管)。在 20899 名接受检测的患者中,8928 名检测呈阳性,1701 名住院,684 名插管,1179 名死于 COVID-19。年龄、性别、种族/族裔、纽约市行政区(从邮政编码的前 3 位数字推断)和首选英语是检测阳性、住院、插管和 COVID-19 死亡率的多变量逻辑回归分析的显著预测因素。居住在较贫困行政区的人更有可能受到 COVID-19 的影响并因此死亡。我们的研究结果强调了将全面的 SDOH 数据纳入有风险的患者群体的医疗保健工作中的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ece/7722480/f290dc9cc77b/fpubh-08-571364-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ece/7722480/f290dc9cc77b/fpubh-08-571364-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ece/7722480/f290dc9cc77b/fpubh-08-571364-g0001.jpg

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