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美国退伍军人在 COVID-19 大流行期间的超额死亡率:一项个体水平队列研究。

Excess mortality in US Veterans during the COVID-19 pandemic: an individual-level cohort study.

机构信息

Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.

Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA.

出版信息

Int J Epidemiol. 2023 Dec 25;52(6):1725-1734. doi: 10.1093/ije/dyad136.

Abstract

BACKGROUND

Most analyses of excess mortality during the COVID-19 pandemic have employed aggregate data. Individual-level data from the largest integrated healthcare system in the US may enhance understanding of excess mortality.

METHODS

We performed an observational cohort study following patients receiving care from the Department of Veterans Affairs (VA) between 1 March 2018 and 28 February 2022. We estimated excess mortality on an absolute scale (i.e. excess mortality rates, number of excess deaths) and a relative scale by measuring the hazard ratio (HR) for mortality comparing pandemic and pre-pandemic periods, overall and within demographic and clinical subgroups. Comorbidity burden and frailty were measured using the Charlson Comorbidity Index and Veterans Aging Cohort Study Index, respectively.

RESULTS

Of 5 905 747 patients, the median age was 65.8 years and 91% were men. Overall, the excess mortality rate was 10.0 deaths/1000 person-years (PY), with a total of 103 164 excess deaths and pandemic HR of 1.25 (95% CI 1.25-1.26). Excess mortality rates were highest among the most frail patients (52.0/1000 PY) and those with the highest comorbidity burden (16.3/1000 PY). However, the largest relative mortality increases were observed among the least frail (HR 1.31, 95% CI 1.30-1.32) and those with the lowest comorbidity burden (HR 1.44, 95% CI 1.43-1.46).

CONCLUSIONS

Individual-level data offered crucial clinical and operational insights into US excess mortality patterns during the COVID-19 pandemic. Notable differences emerged among clinical risk groups, emphasizing the need for reporting excess mortality in both absolute and relative terms to inform resource allocation in future outbreaks.

摘要

背景

大多数关于 COVID-19 大流行期间超额死亡率的分析都采用了综合数据。来自美国最大的综合医疗系统的个体水平数据可能有助于更好地理解超额死亡率。

方法

我们对 2018 年 3 月 1 日至 2022 年 2 月 28 日期间在退伍军人事务部(VA)接受治疗的患者进行了一项观察性队列研究。我们通过测量大流行和大流行前期间死亡率的风险比(HR),从绝对规模(即超额死亡率、超额死亡人数)和相对规模来估计超额死亡率,总体上以及在人口统计学和临床亚组内。使用 Charlson 合并症指数和退伍军人老龄化队列研究指数分别衡量合并症负担和脆弱性。

结果

在 5905747 名患者中,中位年龄为 65.8 岁,91%为男性。总体而言,超额死亡率为 10.0 人/1000 人年(PY),共有 103164 人超额死亡,大流行 HR 为 1.25(95%CI 1.25-1.26)。在最脆弱的患者(52.0/1000 PY)和合并症负担最高的患者(16.3/1000 PY)中,超额死亡率最高。然而,在最不脆弱的患者(HR 1.31,95%CI 1.30-1.32)和合并症负担最低的患者(HR 1.44,95%CI 1.43-1.46)中,观察到最大的相对死亡率增加。

结论

个体水平数据为了解美国 COVID-19 大流行期间的超额死亡率模式提供了重要的临床和运营见解。在临床风险组之间出现了显著差异,强调在未来的疫情中需要以绝对和相对的方式报告超额死亡率,以为资源分配提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/10749763/40191cfb6509/dyad136f1.jpg

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