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长新冠对健康相关生活质量的影响:一项使用患者报告结局指标的OpenSAFELY人群队列研究(OpenPROMPT)。

Impact of long COVID on health-related quality-of-life: an OpenSAFELY population cohort study using patient-reported outcome measures (OpenPROMPT).

作者信息

Carlile Oliver, Briggs Andrew, Henderson Alasdair D, Butler-Cole Ben F C, Tazare John, Tomlinson Laurie A, Marks Michael, Jit Mark, Lin Liang-Yu, Bates Chris, Parry John, Bacon Sebastian C J, Dillingham Iain, Dennison William A, Costello Ruth E, Walker Alex J, Hulme William, Goldacre Ben, Mehrkar Amir, MacKenna Brian, Herrett Emily, Eggo Rosalind M

机构信息

London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.

出版信息

Lancet Reg Health Eur. 2024 Apr 24;40:100908. doi: 10.1016/j.lanepe.2024.100908. eCollection 2024 May.

Abstract

BACKGROUND

Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. We aimed to evaluate and estimate the differences in health impacts of long COVID across sociodemographic categories and quantify this in Quality-Adjusted Life-Years (QALYs), widely used measures across health systems.

METHODS

With the approval of NHS England, we utilised OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID.

FINDINGS

The total OpenPROMPT cohort consisted of 7575 individuals who consented to data collection, with which we used data from 6070 participants who completed a baseline research questionnaire where 24.6% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a higher likelihood or odds of reporting loss in quality-of-life (Odds Ratio (OR): 4.7, 95% CI: 3.72-5.93) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 17.7, 95% CI: 10.37-30.33) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss.

INTERPRETATION

We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease.

FUNDING

This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

摘要

背景

新冠后遗症是一个影响患者健康、医疗服务和劳动力的重大问题。为了优化未来针对新冠疫情的干预措施设计,并更好地规划和分配卫生资源,量化这种新情况的健康和经济负担至关重要。我们旨在评估和估计新冠后遗症在不同社会人口学类别中的健康影响差异,并以质量调整生命年(QALYs,卫生系统中广泛使用的衡量指标)进行量化。

方法

在英国国家医疗服务体系(NHS)英格兰地区的批准下,我们利用了OpenPROMPT,这是一项英国队列研究,用于测量新冠后遗症对健康相关生活质量(HRQoL)的影响。OpenPROMPT通过智能手机应用程序邀请参与者对患者报告结局量表(PROMs)做出回应,并于2022年11月至2023年10月期间招募参与者。我们使用经过验证的欧洲五维度健康量表(EuroQol EQ - 5D)问卷及英国价值集,通过线性混合模型为有和没有新冠后遗症的受访者制定失能分数(1 - 效用),并计算新冠后遗症患者随后的质量调整生命月(QALMs)。

研究结果

OpenPROMPT队列总共包括7575名同意数据收集的个体,我们使用了其中6070名完成基线研究问卷的参与者的数据,其中24.6%的人自我报告有新冠后遗症。在多变量回归分析中,新冠后遗症对健康相关生活质量有持续影响,与未报告有新冠后遗症的人相比,报告生活质量下降的可能性或几率更高(优势比(OR):4.7,95%置信区间:3.72 - 5.93)。在所有调查回复中,报告有残疾是健康相关生活质量下降的最大预测因素(OR:17.7,95%置信区间:10.37 - 30.33)。自我报告有新冠后遗症与质量调整生命月损失0.37相关。

解读

我们发现新冠后遗症对生活质量有重大影响,这对患者和医疗服务构成了重大负担。我们强调需要持续为新冠后遗症提供支持和研究,因为与患有多发性硬化症、心力衰竭和肾病等疾病的患者相比,新冠后遗症患者的健康相关生活质量得分较低。

资金来源

本研究由英国国家卫生与保健研究所(NIHR)资助(OpenPROMPT:COV - LT2 - 0073)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52c6/11059448/8116b56ee10e/gr1.jpg

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