Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2022 May 19;17(5):e0268528. doi: 10.1371/journal.pone.0268528. eCollection 2022.
There is growing evidence that racial and ethnic minorities bear a disproportionate burden from COVID-19. Temporal changes in the pandemic epidemiology and diversity in the clinical course require careful study to identify determinants of poor outcomes. We analyzed 6255 hospitalized individuals with PCR-confirmed SARS-CoV-2 infection from one of 5 hospitals in the University of Pennsylvania Health System between March 2020 and March 2021, using electronic health records to assess risk factors and outcomes through 8 weeks post-admission. Discharge, readmission and mortality outcomes were analyzed in a multi-state model with multivariable Cox models for each transition. Mortality varied markedly over time, with cumulative incidence (95% CI) 30 days post-admission of 19.1% (16.9, 21.3) in March-April 2020, 5.7% (4.2, 7.5) in July-October 2020 and 10.5% (9.1,12.0) in January-March 2021; 26% of deaths occurred after discharge. Average age (SD) at admission varied from 62.7 (17.6) to 54.8 (19.9) to 60.5 (18.1); mechanical ventilation use declined from 21.3% to 9-11%. Compared to Caucasian, Black race was associated with more severe disease at admission, higher rates of co-morbidities and residing in a low-income zip code. Between-race risk differences in mortality risk diminished in multivariable models; while admitting hospital, increasing age, admission early in the pandemic, and severe disease and low blood pressure at admission were associated with increased mortality hazard. Hispanic ethnicity was associated with fewer baseline co-morbidities and lower mortality hazard (0.57, 95% CI: 0.37, .087). Multi-state modeling allows for a unified framework to analyze multiple outcomes throughout the disease course. Morbidity and mortality for hospitalized COVID-19 patients varied over time but post-discharge mortality remained non-trivial. Black race was associated with more risk factors for morbidity and with treatment at hospitals with lower mortality. Multivariable models suggest there are not between-race differences in outcomes. Future work is needed to better understand the identified between-hospital differences in mortality.
越来越多的证据表明，少数族裔承受着不成比例的 COVID-19 负担。大流行期间流行病学的时间变化和临床过程中的多样性需要仔细研究，以确定不良结局的决定因素。我们分析了 2020 年 3 月至 2021 年 3 月期间宾夕法尼亚大学卫生系统的 5 家医院之一的 6255 名经 PCR 确诊的 SARS-CoV-2 感染住院患者的电子健康记录，以评估入院后 8 周的风险因素和结局。使用多状态模型分析出院、再入院和死亡率结局，并对每个转变使用多变量 Cox 模型进行分析。死亡率随时间显著变化，入院后 30 天的累积发病率（95%CI）在 2020 年 3 月至 4 月为 19.1%（16.9，21.3），2020 年 7 月至 10 月为 5.7%（4.2，7.5），2021 年 1 月至 3 月为 10.5%（9.1，12.0）；26%的死亡发生在出院后。入院时的平均年龄（SD）从 62.7（17.6）到 54.8（19.9）到 60.5（18.1）不等；机械通气使用率从 21.3%下降到 9-11%。与白种人相比，黑种人入院时疾病更严重，合并症发生率更高，居住在低收入邮政编码地区。多变量模型中，不同种族之间的死亡率风险差异缩小；然而，住院医院、年龄增长、大流行早期入院以及入院时严重疾病和低血压与死亡率增加有关。西班牙裔与较少的基线合并症和较低的死亡率风险相关（0.57，95%CI：0.37，0.087）。多状态模型允许在疾病过程中分析多个结局的统一框架。住院 COVID-19 患者的发病率和死亡率随时间而变化，但出院后死亡率仍然不容忽视。黑种人入院时与更多的发病风险因素和死亡率较低的医院治疗相关。多变量模型表明，不同种族之间的结局没有差异。需要进一步研究以更好地了解确定的医院间死亡率差异。
