AI-Enabled Frailty Risk Prediction in Adult Congenital Heart Disease

Starting soon · Not applicable

Conditions studied: Adult Congenital Heart Disease, Symptom Clusters, Frailty, Risk Prediction Model, Artificial Intelligence-Based Voice Emotion Detection

In brief

The goal of this three-year mixed-methods observational study with an embedded randomized controlled trial is to develop and validate a frailty risk prediction model and evaluate an artificial intelligence-based voice emotion detection-guided counselling intervention in adults with congenital heart disease (ACHD). The main questions it aims to answer are: Are symptom clusters associated with frailty and psychological outcomes in adults with congenital heart disease? Can symptom clusters and psychosocial factors be used to predict frailty risk over time in ACHD patients? Does an AI-based voice emotion detection-guided counselling intervention improve psychological outcomes, fatigue, and quality of life among high-risk ACHD patients? Researchers will compare ACHD patients receiving AI-based voice emotion detection-guided counselling with those receiving usual care to determine whether the intervention reduces depression, anxiety, sleep disturbance, fatigue, and frailty risk, and improves grit and quality of life. Participants will: Complete longitudinal assessments of symptom clusters, frailty, and psychological status at baseline and follow-up time points Participate in qualitative interviews to explore lived experiences related to symptoms and frailty Receive AI-based voice emotion detection-guided counselling (intervention group only in Year 3)

Key facts

Study ID
NCT07479654
Run by
Mackay Memorial Hospital
People needed
410
Starts
2026-03-01
Expected to finish
2028-12-31
Last updated by the study team
2026-03-18

Who can join

Age: 20 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Full record on ClinicalTrials.gov

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