Kisiel Marta A, Lee Seika, Malmquist Sara, Rykatkin Oliver, Holgert Sebastian, Janols Helena, Janson Christer, Zhou Xingwu
Department of Medical Sciences, Occupational and Environmental Medicine, Uppsala University, 751 85 Uppsala, Sweden.
Department of Neurobiology, Care Sciences and Society, Primary Care Medicine, Karolinska Institute, 171 77 Stockholm, Sweden.
J Clin Med. 2023 May 23;12(11):3617. doi: 10.3390/jcm12113617.
BACKGROUND/AIM: This study aimed to distinguish different phenotypes of long COVID through the post-COVID syndrome (PCS) score based on long-term persistent symptoms following COVID-19 and evaluate whether these symptoms affect general health and work ability. In addition, the study identified predictors for severe long COVID.
This cluster analysis included cross-sectional data from three cohorts of patients after COVID-19: non-hospitalized (n = 401), hospitalized (n = 98) and those enrolled at the post-COVID outpatient's clinic (n = 85). All the subjects responded to the survey on persistent long-term symptoms and sociodemographic and clinical factors. K-Means cluster analysis and ordinal logistic regression were used to create PCS scores that were used to distinguish patients' phenotypes.
506 patients with complete data on persistent symptoms were divided into three distinct phenotypes: none/mild (59%), moderate (22%) and severe (19%). The patients with severe phenotype, with the predominating symptoms were fatigue, cognitive impairment and depression, had the most reduced general health status and work ability. Smoking, snuff, body mass index (BMI), diabetes, chronic pain and symptom severity at COVID-19 onset were factors predicting severe phenotype.
This study suggested three phenotypes of long COVID, where the most severe was associated with the highest impact on general health status and working ability. This knowledge on long COVID phenotypes could be used by clinicians to support their medical decisions regarding prioritizing and more detailed follow-up of some patient groups.
背景/目的:本研究旨在通过基于新冠病毒感染后长期持续症状的新冠后综合征(PCS)评分来区分长期新冠的不同表型,并评估这些症状是否会影响总体健康和工作能力。此外,该研究还确定了严重长期新冠的预测因素。
这项聚类分析纳入了三组新冠病毒感染后患者的横断面数据:非住院患者(n = 401)、住院患者(n = 98)以及在新冠后门诊就诊的患者(n = 85)。所有受试者均对关于持续长期症状以及社会人口统计学和临床因素的调查做出了回应。采用K均值聚类分析和有序逻辑回归来创建用于区分患者表型的PCS评分。
506例有持续症状完整数据的患者被分为三种不同的表型:无/轻度(59%)、中度(22%)和重度(19%)。具有严重表型的患者,其主要症状为疲劳、认知障碍和抑郁,总体健康状况和工作能力下降最为明显。吸烟、鼻烟、体重指数(BMI)、糖尿病、慢性疼痛以及新冠病毒感染发病时的症状严重程度是预测严重表型的因素。
本研究提示了长期新冠的三种表型,其中最严重的表型对总体健康状况和工作能力的影响最大。临床医生可利用这些关于长期新冠表型的知识,为其在对某些患者群体进行优先排序和更详细随访方面的医疗决策提供支持。