Borhani Soheil, Silva Ikaro, Damiano Robert J, Feng Ting, Wang Chunxue, Liu Luoluo, Salvati Emmanuele, Mariani Sara, Conroy Bryan
Philips North America, Cambridge, MA, USA.
Sci Rep. 2025 Aug 11;15(1):29443. doi: 10.1038/s41598-025-15208-0.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can lead to post-acute sequelae of SARS-CoV-2 infection (PASC), or Long COVID, a chronic multisystemic condition with diverse symptoms and no objective diagnostic test. In this retrospective study, we developed a data-driven method to objectively detect persistent physiological changes using wearable device data in a large cohort of over 12,000 US military personnel. We analyzed physiological data from 663 symptomatic COVID-19 positive cases and 2,513 asymptomatic COVID-19 negative controls. Our method identified persistent physiological changes in 9.4% of COVID-19 positive individuals, most commonly manifesting as elevated nightly heart rate and reductions in some heart rate variability metrics. Our findings demonstrate that wearable technology can be used to objectively detect chronic physiological changes beyond the acute phase of COVID-19 illness. Although our method requires further clinical validation, it could potentially provide objective metrics to help standardize Long COVID diagnosis criteria.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染可导致SARS-CoV-2感染的急性后遗症(PASC),即长新冠,这是一种具有多种症状且无客观诊断测试的慢性多系统疾病。在这项回顾性研究中,我们开发了一种数据驱动的方法,以使用来自超过12000名美国军事人员的大型队列中的可穿戴设备数据来客观检测持续的生理变化。我们分析了663例有症状的新冠病毒阳性病例和2513例无症状的新冠病毒阴性对照的生理数据。我们的方法在9.4%的新冠病毒阳性个体中识别出持续的生理变化,最常见的表现为夜间心率升高和一些心率变异性指标降低。我们的研究结果表明,可穿戴技术可用于客观检测新冠病毒疾病急性期之后的慢性生理变化。尽管我们的方法需要进一步的临床验证,但它可能会提供客观指标,以帮助标准化长新冠的诊断标准。