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Predicting deterioration in dengue using a low cost wearable for continuous clinical monitoring

  • Damien Keng Ming,
  • John Daniels,
  • Ho Quang Chanh,
  • Stefan Karolcik,
  • Bernard Hernandez,
  • Vasileios Manginas,
  • Van Hao Nguyen,
  • Quang Huy Nguyen,
  • Tu Qui Phan,
  • Thi Hue Tai Luong,
  • Huynh Trung Trieu,
  • Alison Helen Holmes,
  • Vinh Tho Phan,
  • Pantelis Georgiou,
  • Sophie Yacoub

摘要

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.