Ming Damien Keng, Daniels John, Chanh Ho Quang, Karolcik Stefan, Hernandez Bernard, Manginas Vasileios, Nguyen Van Hao, Nguyen Quang Huy, Phan Tu Qui, Luong Thi Hue Tai, Trieu Huynh Trung, Holmes Alison Helen, Phan Vinh Tho, Georgiou Pantelis, Yacoub Sophie
Centre for Antimicrobial Optimisation, Imperial College London, London, UK.
Centre for Bio-Inspired Technology, Imperial College London, London, UK.
NPJ Digit Med. 2024 Nov 2;7(1):306. doi: 10.1038/s41746-024-01304-4.
Close vital signs monitoring is crucial for the clinical management of patients with dengue. We investigated performance of a non-invasive wearable utilising photoplethysmography (PPG), to provide real-time risk prediction in hospitalised individuals. We performed a prospective observational clinical study in Vietnam between January 2020 and October 2022: 153 patients were included in analyses, providing 1353 h of PPG data. Using a multi-modal transformer approach, 10-min PPG waveform segments and basic clinical data (age, sex, clinical features on admission) were used as features to continuously forecast clinical state 2 h ahead. Prediction of low-risk states (17,939/80,843; 22.1%), defined by NEWS2 and mSOFA < 6, was associated with an area under the precision-recall curve of 0.67 and an area under the receiver operator curve of 0.83. Implementation of such interventions could provide cost-effective triage and clinical care in dengue, offering opportunities for safe ambulatory patient management.
密切监测生命体征对于登革热患者的临床管理至关重要。我们研究了一种利用光电容积脉搏波描记法(PPG)的无创可穿戴设备在住院患者中进行实时风险预测的性能。我们于2020年1月至2022年10月在越南进行了一项前瞻性观察性临床研究:153名患者纳入分析,提供了1353小时的PPG数据。采用多模态变压器方法,将10分钟的PPG波形片段和基本临床数据(年龄、性别、入院时的临床特征)作为特征,用于提前2小时连续预测临床状态。由NEWS2和改良序贯器官衰竭评估(mSOFA)<6定义的低风险状态预测(17939/80843;22.1%),其精确召回曲线下面积为0.67,受试者工作特征曲线下面积为0.83。实施此类干预措施可为登革热提供具有成本效益的分诊和临床护理,为安全的门诊患者管理提供机会。