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新英格兰州退伍军人中分离出的新冠病毒2型(SARS-CoV-2)的COVID-19结局与基因组特征:回顾性分析

COVID-19 Outcomes and Genomic Characterization of SARS-CoV-2 Isolated From Veterans in New England States: Retrospective Analysis.

作者信息

Lee Megan, Sallah Ya Haddy, Petrone Mary, Ringer Matthew, Cosentino Danielle, Vogels Chantal B F, Fauver Joseph R, Alpert Tara D, Grubaugh Nathan D, Gupta Shaili

机构信息

Yale School of Medicine West Haven, CT United States.

Yale School of Public Health New Haven, CT United States.

出版信息

JMIRx Med. 2021 Dec 17;2(4):e31503. doi: 10.2196/31503. eCollection 2021 Oct-Dec.

Abstract

BACKGROUND

Clinical and virologic characteristics of COVID-19 infections in veterans in New England have not been described. The average US veteran is a male older than the general US population. SARS-CoV-2 infection is known to cause poorer outcomes among men and older adults, making the veteran population an especially vulnerable group for COVID-19.

OBJECTIVE

This study aims to evaluate clinical and virologic factors impacting COVID-19 outcomes.

METHODS

This retrospective chart review included 476 veterans in six New England states with confirmed SARS-CoV-2 infection between April and September 2020. Whole genome sequencing was performed on SARS-CoV-2 RNA isolated from these veterans, and the correlation of genomic data to clinical outcomes was evaluated. Clinical and demographic variables were collected by manual chart review and were correlated to the end points of peak disease severity (based on oxygenation requirements), hospitalization, and mortality using multivariate regression analyses.

RESULTS

Of 476 veterans, 274 had complete and accessible charts. Of the 274 veterans, 92.7% (n=254) were men and 83.2% (n=228) were White, and the mean age was 63 years. In the multivariate regression, significant predictors of hospitalization (C statistic 0.75) were age (odds ratio [OR] 1.05, 95% CI 1.03-1.08) and non-White race (OR 2.39, 95% CI 1.13-5.01). Peak severity (C statistic 0.70) also varied by age (OR 1.07, 95% CI 1.03-1.11) and O2 requirement on admission (OR 45.7, 95% CI 18.79-111). Mortality (C statistic 0.87) was predicted by age (OR 1.06, 95% CI 1.01-1.11), dementia (OR 3.44, 95% CI 1.07-11.1), and O2 requirement on admission (OR 6.74, 95% CI 1.74-26.1). Most (291/299, 97.3%) of our samples were dominated by the spike protein D614G substitution and were from SARS-CoV-2 B.1 lineage or one of 37 different B.1 sublineages, with none representing more than 8.7% (26/299) of the cases.

CONCLUSIONS

In a cohort of veterans from the six New England states with a mean age of 63 years and a high comorbidity burden, age was the largest predictor of hospitalization, peak disease severity, and mortality. Non-White veterans were more likely to be hospitalized, and patients who required oxygen on admission were more likely to have severe disease and higher rates of mortality. Multiple SARS-CoV-2 lineages were distributed in patients in New England early in the COVID-19 era, mostly related to viruses from New York State with D614G mutation.

摘要

背景

新英格兰地区退伍军人感染新型冠状病毒肺炎(COVID-19)的临床和病毒学特征尚未得到描述。美国退伍军人的平均年龄高于美国普通人群,且以男性为主。已知严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染在男性和老年人中会导致更差的预后,这使得退伍军人成为COVID-19的特别易感人群。

目的

本研究旨在评估影响COVID-19预后的临床和病毒学因素。

方法

这项回顾性病历审查纳入了2020年4月至9月期间新英格兰六个州476名确诊感染SARS-CoV-2的退伍军人。对从这些退伍军人中分离出的SARS-CoV-2 RNA进行全基因组测序,并评估基因组数据与临床预后的相关性。通过人工查阅病历收集临床和人口统计学变量,并使用多因素回归分析将其与疾病严重程度峰值(基于氧疗需求)、住院和死亡率等终点指标进行关联。

结果

476名退伍军人中,274人有完整且可获取的病历。在这274名退伍军人中,92.7%(n = 254)为男性,83.2%(n = 228)为白人,平均年龄为63岁。在多因素回归分析中,住院的显著预测因素(C统计量为0.75)为年龄(比值比[OR] 1.05,95%置信区间[CI] 1.03 - 1.08)和非白人种族(OR 2.39,95% CI 1.13 - 5.01)。疾病严重程度峰值(C统计量为0.70)也因年龄(OR 1.07,95% CI 1.03 - 1.11)和入院时的氧疗需求(OR 45.7,95% CI 18.79 - 111)而异。死亡率(C统计量为0.87)的预测因素为年龄(OR 1.06,95% CI 1.01 - 1.11)、痴呆(OR 3.44,95% CI 1.07 - 11.1)和入院时的氧疗需求(OR 6.74,95% CI 1.74 - 26.1)。我们的大多数样本(291/299,97.3%)以刺突蛋白D614G替代为主,来自SARS-CoV-2 B.1谱系或37个不同B.1亚谱系之一,单个亚谱系病例数均不超过8.7%(26/299)。

结论

在新英格兰六个州平均年龄为63岁且合并症负担较高的退伍军人队列中,年龄是住院、疾病严重程度峰值和死亡率的最大预测因素。非白人退伍军人住院可能性更大,入院时需要吸氧的患者更易患重症且死亡率更高。在COVID-19流行早期,新英格兰地区患者中存在多种SARS-CoV-2谱系分布,大多与来自纽约州带有D614G突变的病毒相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5fb/10414277/128182cc1533/xmed_v2i4e31503_fig1.jpg

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