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英格兰 5700 万成年人的 COVID-19 病程:一项使用电子健康记录的队列研究。

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records.

机构信息

Institute of Health Informatics, University College London, London, UK.

Institute of Health Informatics, University College London, London, UK; UK Research and Innovation Centre for Doctoral Training in AI-enabled Healthcare Systems, University College London, London, UK; University College London Hospitals Biomedical Research Centre, University College London, London, UK.

出版信息

Lancet Digit Health. 2022 Jul;4(7):e542-e557. doi: 10.1016/S2589-7500(22)00091-7. Epub 2022 Jun 9.

Abstract

BACKGROUND

Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework.

METHODS

In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.

FINDINGS

Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1.

INTERPRETATION

Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources.

FUNDING

British Heart Foundation Data Science Centre, led by Health Data Research UK.

摘要

背景

更新的 COVID-19 发病、进展和轨迹估计是减轻大流行努力的基础。为了确定和描述疾病轨迹,我们旨在使用可扩展框架从全国性的电子健康记录 (EHR) 中定义和验证十种 COVID-19 表型。

方法

在这项队列研究中,我们使用了英格兰的八个 NHS 数据集,其中包括 2020 年 1 月 23 日在世的人员。收集了 COVID-19 检测、疫苗接种、初级和二级护理记录以及死亡登记的数据,直到 2021 年 11 月 30 日。我们定义了十种 COVID-19 表型,反映了疾病严重程度的临床相关阶段,涵盖了五个类别:SARS-CoV-2 检测阳性、初级保健诊断、住院、通气方式(四种表型)和死亡(三种表型)。我们构建了患者轨迹,说明了表型之间的转换频率和持续时间。分析按大流行波和疫苗接种状况分层。

发现

在包括的 57032174 名个体中,在 7244925 名个体中发现了 13990423 例 COVID-19 事件,这相当于研究期间 12.7%的感染率。在 7244925 名个体中,有 460737 名(6.4%)住院,158020 名(2.2%)死亡。在住院的 460737 名个体中,有 48847 名(10.6%)入住重症监护病房(ICU),有 69090 名(15.0%)接受非侵入性通气,有 25928 名(5.6%)接受有创通气。在 384135 名住院但不需要通气的患者中,第 1 波的死亡率(77202 名患者中有 23485 名[30.4%])高于第 2 波(191528 名患者中有 44220 名[23.1%]),但 ICU 住院患者的死亡率没有变化。在第 1 波中,在 ICU 外接受通气支持的患者死亡率最高(5063 名患者中有 2569 名[50.7%])。在没有 COVID-19 诊断的情况下,158020 例 COVID-19 相关死亡中有 15486 例(9.8%)发生在首次 COVID-19 事件后 28 天内。在 158020 例死亡中,有 10884 例(6.9%)仅从死亡率数据中确定,之前没有记录过 COVID-19 表型。我们观察到第 2 波的患者轨迹比第 1 波更长。

解释

我们的分析说明了疾病轨迹的广泛范围,这反映在发病率、生存率和临床途径的差异上。我们提供了一个模块化的分析框架,可用于使用多个 EHR 源监测大流行的影响并生成具有临床和政策相关性的证据。

资金

英国心脏基金会数据科学中心,由英国健康数据研究中心领导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0903/9179175/2ff69fa85c29/gr1_lrg.jpg

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