Bioimpedance-Based Heart Failure Deterioration Prediction Using a Prototype Fluid Accumulation Vest-Mobile Phone...

Area of Science:

• Cardiology
• Biomedical Engineering
• Digital Health

Background:

• Recurrent heart failure (HF) events are a significant challenge for patients post-discharge.
• Existing methods for detecting HF decompensation lack patient-centered technological integration.
• Transthoracic bioimpedance offers a noninvasive method to assess pulmonary fluid retention.

Purpose of the Study:

• To evaluate the feasibility of daily measurements using a novel wearable fluid accumulation vest (FAV) and mobile phone transmission.
• To determine if an automated algorithm analyzing thoracic bioimpedance can predict recurrent HF events.

Main Methods:

• Prospective enrollment of patients admitted for acute decompensated heart failure (ADHF).
• Participants used a FAV-mobile phone system for daily bioimpedance measurements over 45 days.
• An algorithm analyzed bioimpedance data to predict HF events (readmission, diuretic uptitration) over 75 days.

Main Results:

• 64 HF events occurred among 106 participants; prior HF history was the only significant predictor (P=.04).
• The algorithm demonstrated 87% sensitivity, 70% specificity, and 72% accuracy in identifying recurrent HF events in 57 participants with sufficient data.
• Patients successfully measured and transmitted daily bioimpedance data via the FAV-mobile phone dyad.

Conclusions:

• Daily transthoracic bioimpedance measurement and transmission are feasible for patients post-ADHF using a FAV-mobile phone system.
• Automated analysis of thoracic bioimpedance shows promise in identifying patients at high risk for recurrent HF events.
• This technology can support proactive management and potentially reduce hospital readmissions for heart failure.