AI-enabled, continuous monitoring wearables show promise in allowing physicians to predict decompensation events in post-acute heart failure patients, according to a Veterans Administration-funded study published this month in the Journal of the American College of Cardiology.

Researchers reported they were able to detect subtle anomalies in patients’ vitals by retroactively running data from wearable monitoring devices through sophisticated machine-based learning algorithms.

The correlation between detected anomalies and documented decompensation events was strong enough that researchers believe it may be possible to develop consumer-driven approaches, such as wearable real-time monitors connected to a hospital’s or payer’s centralized monitoring system, that could improve quality of care, help physicians to better identify impending heart failure, give patients more early warning time and increase their survival chances.

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