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。我们研究了利用光电容积脉搏波 （PPG） 的无创可穿戴设备的性能，以提供住院个体的实时风险预测。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 名患者被纳入分析，提供 1353 小时的 PPG 数据。使用多模态变压器方法，使用 10 min PPG 波形段和基本临床数据 （年龄、性别、入院临床特征） 作为特征，提前 2 小时连续预测临床状态。由 NEWS2 和 mSOFA < 6 定义的低风险状态 （17,939/80,843;22.1%） 的预测与精确率-召回曲线下面积 0.67 和受试者操作员曲线下面积 0.83 相关。实施此类干预措施可以在登革热中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。