Digital health technologies versus traditional methods for cardiovascular risk assessment in asymptomatic adults: a systematic review and network meta-analysis of diagnostic accuracy and clinical outcomes.
Jing Wang, Xinxiao Li, Chuqing Luo et al.
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In 30 seconds
This systematic review and network meta-analysis evaluated the effectiveness of digital health technologies compared to traditional methods for cardiovascular risk assessment in asymptomatic adults. Analyzing 32 studies with over 11 million participants, the results indicated that digital technologies significantly improved diagnostic accuracy and clinical outcomes, with wearable devices achieving a pooled AUC of 0.92 for arrhythmia detection and reducing all-cause mortality by 38% (pooled RR, 0.62).
Key findings
- Wearable devices had the highest pooled AUC for arrhythmia detection at 0.92.
- Digital health interventions reduced all-cause mortality by 38% (pooled RR, 0.62).
- Traditional risk scores had a significantly lower pooled AUC of 0.75.
- AI-ML algorithms ranked first for clinical outcomes with a SUCRA of 72.8%.
Why it matters
The findings highlight the potential of digital health technologies to enhance cardiovascular risk assessment, which could lead to improved patient outcomes and more effective management of cardiovascular disease, a leading cause of mortality worldwide.