Wang Yide, Xue Qianqian, Li Zheng, Li Fengsen
Department of Integrated Pulmonology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
Department of Integrated Pulmonology, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China; Xinjiang National Clinical Research Base of Traditional Chinese Medicine, Xinjiang Medical University, Urumqi, Xinjiang, China.
J Rehabil Med. 2025 Mar 27;57:jrm42726. doi: 10.2340/jrm.v57.42726.
Investigating the role of telerehabilitation in aiding recovery and societal reintegration for COVID-19 survivors, this study aims to identify distinct subphenotypes among survivors and assess their responsiveness to telerehabilitation.
A secondary analysis of a multicentre, parallel-group randomized controlled trial from April 2020 through to follow-up in 2021.
SUBJECTS/PATIENTS: The study included 377 COVID-19 survivors (47.1% male), with a mean age of 56.4 years.
Data from the Telerehabilitation Programme for COVID-19 (TERECO) were analysed using Latent Class Analysis to identify subphenotypes based on baseline characteristics. Clinical outcomes were compared between subphenotypes and treatment groups.
Latent Class Analysis identified 2 phenotypes: Phenotype 1 (52.9%) characterized by impaired lung function and Phenotype 2 (47.1%) with better lung function. Among those receiving corticosteroids, only Phenotype 1 showed significant benefits from the TERECO intervention. Discrimination accuracy using forced expiratory volume in 1 s (FEV1) and peak expiratory flow was high (AUC = 0.936).
Two distinct phenotypes were identified in COVID-19 survivors, suggesting potential improvements in clinical trial design and personalized treatment strategies based on initial pulmonary function. This insight can guide more targeted rehabilitation approaches, enhancing recovery outcomes for specific survivor groups.
为研究远程康复在帮助新冠肺炎幸存者康复及重新融入社会中的作用，本研究旨在识别幸存者中的不同亚表型，并评估他们对远程康复的反应。
对一项多中心、平行组随机对照试验进行二次分析，该试验从2020年4月持续至2021年随访阶段。
研究对象/患者：该研究纳入了377名新冠肺炎幸存者（男性占47.1%），平均年龄为56.4岁。
使用潜在类别分析对新冠肺炎远程康复计划（TERECO）的数据进行分析，以根据基线特征识别亚表型。比较亚表型与治疗组之间的临床结果。
潜在类别分析确定了2种表型：表型1（52.9%）的特征是肺功能受损，表型2（47.1%）的肺功能较好。在接受皮质类固醇治疗的患者中，只有表型1从TERECO干预中显示出显著益处。使用第1秒用力呼气量（FEV1）和呼气峰值流速的判别准确性很高（AUC = 0.936）。
在新冠肺炎幸存者中确定了两种不同的表型，这表明基于初始肺功能的临床试验设计和个性化治疗策略可能会有所改进。这一见解可以指导更有针对性的康复方法，提高特定幸存者群体的康复效果。
