Voice-Analysis App for Heart Failure
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How successful is the Voice-Analysis App Promising as Early Warning System for Heart Failure Decompensation in a patient? what does the studies says?
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@sampreeti A voice can carry a long distance, but in patients with heart failure (HF) a voice can also carry otherwise hidden signs useful for predicting short-term risk for worsening disease, even acute decompensation. Potentially, it only has to reach a smartphone to do it, suggests a preliminary study of a mobile app designed to alert patients and clinicians to such looming HF events, if possible in time to avert them.
The proprietary app and analysis system (HearO, Cordio Medical), used daily at home by 180 patients with stable HF, demonstrated 82% accuracy in picking out vocal signals of early congestion that would soon be followed by a need for intensified therapy or acute decompensation.
In practice, clinicians receiving the system's alerts about altered fluid status would intervene with medication adjustments before the patient deteriorates and possibly heads for the emergency department. That would be the plan; there were no interventions in the current study, which was designed only to explore the strategy's feasibility and accuracy.
The system could emerge as "a useful tool in remote monitoring of heart failure patients, providing early warning of worsening heart failure," said William Abraham, MD, from Ohio State University Wexner Medical Center, Columbus.
"It has the potential to reduce acute decompensated heart failure hospitalizations and improve patient quality-of-life and economic outcomes. But, of course, we have to show that now in larger and randomized clinical studies."
Abraham presented the Cordio HearO Community Study preliminary results today at the Heart Failure Association of the European Society of Cardiology (HFA-ESC) sessions, held virtually and live in Madrid, Spain. It follows a recent small study that showed the same app could identify vocal signals linked to altered fluid status in patients with HF hospitalized with acute decompensation.
In the current study, researchers prospectively tracked any worsening-HF events that hit patients within a month after the system sent them an alert suggesting early changes in fluid status. Then, they retrospectively assessed the strategy's predictive accuracy for an initial episode.
The system correctly predicted 32 of 39 first HF events, for an 82% sensitivity and a false-positive rate of 18%. On an annualized basis, Abraham said, the patients experienced an estimated two to three false alarms per year, alerts that were not followed by HF events. For context, the standard practice of monitoring the patient's weight "has a sensitivity of about 10% to 20%. So this performs very well as a noninvasive technology."