小柯机器人

英国伦敦大学学院Claire J. Steves课题组揭示长期COVID的特征和预测因素。该项研究成果于2021年3月10日在线发表在《自然—医学》杂志上。

研究人员分析了来自4,182例COVID-19新发病例的数据，其中患者在COVID症状研究应用程序中提前自我报告了他们的症状。共有558名（13.3％）参与者报告症状持续≥28天、189名（4.5％）≥8周、95名（2.3％）≥12周。长期COVID的特征是疲劳、头痛、呼吸困难和失眠症状，并且随着年龄和体重指数以及女性性别的增加而发生的可能性更大。患病第一周出现超过五个症状与长期COVID有关（比值比 = 3.53（2.76-4.50））。

一个简单的模型可以区分7天的短期COVID和长期COVID（总样本量，n = 2,149），其观测者操作特性曲线（ROC）的曲线下面积为76％，并在2,472名阳性患者的独立样本中得以重复。这个模型可用于识别有长期COVID风险的个体，从而进行预防或治疗试验，以及计划响应措施。

据悉，关于持久性COVID-19症状（即所谓的“长期COVID”）的报道正在上升，但对患病率、危险因素或是否有可能在疾病早期预测长期病程知之甚少。

附：英文原文

Title: Attributes and predictors of long COVID

Author: Carole H. Sudre, Benjamin Murray, Thomas Varsavsky, Mark S. Graham, Rose S. Penfold, Ruth C. Bowyer, Joan Capdevila Pujol, Kerstin Klaser, Michela Antonelli, Liane S. Canas, Erika Molteni, Marc Modat, M. Jorge Cardoso, Anna May, Sajaysurya Ganesh, Richard Davies, Long H. Nguyen, David A. Drew, Christina M. Astley, Amit D. Joshi, Jordi Merino, Neli Tsereteli, Tove Fall, Maria F. Gomez, Emma L. Duncan, Cristina Menni, Frances M. K. Williams, Paul W. Franks, Andrew T. Chan, Jonathan Wolf, Sebastien Ourselin, Tim Spector, Claire J. Steves

Issue&Volume: 2021-03-10

Abstract: Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called ‘long COVID’, are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app1. A total of 558 (13.3%) participants reported symptoms lasting ≥28days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio=3.53 (2.76–4.50)). A simple model to distinguish between short COVID and long COVID at 7days (total sample size, n=2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.

DOI: 10.1038/s41591-021-01292-y

Source: https://www.nature.com/articles/s41591-021-01292-y

Nature Medicine：《自然—医学》，创刊于1995年。隶属于施普林格·自然出版集团，最新IF：87.241
官方网址：https://www.nature.com/nm/
投稿链接：https://mts-nmed.nature.com/cgi-bin/main.plex