AI-Enabled Frailty Risk Prediction in Adult Congenital Heart Disease

Официальное название

Precision Risk Prediction of Symptom Clusters and Frailty With AI-Guided Emotion Detection: A Three-Year Study in Adults With Congenital Heart Disease

Обзор

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)

Вмешательства

• Поведенческое AI-Based Voice Emotion Detection-Guided Counselling
  Participants assigned to the intervention arm will receive an artificial intelligence-based voice emotion detection-guided counselling intervention in addition to usual care. The intervention uses voice recordings collected during structured counselling sessions to analyze emotional features, including emotional valence and arousal, through artificial intelligence-based voice emotion detection algorithms. Based on the analyzed emotional profiles, individualized psychological feedback and counsel
• Поведенческое Usual Care (Control)
  Usual Care

Первичные конечные точки

• Depression and Anxiety assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Short Form Scales [Срок оценки: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention]

Вторичные конечные точки (3)

• Chinese version of the Satisfaction with Life Scale; SWLS [Срок оценки: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention]
• Grit-10 [Срок оценки: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention]
• The Chinese Version of Fatigue Assessment Scale; FAS-C [Срок оценки: Baseline, 2 weeks, 1 month, and 3 months after initiation of the intervention]

Критерии участия

Критерии включения

• Adults aged 20 years or older.
• Diagnosed with congenital heart disease by a physician.
• Able to communicate in Mandarin or Taiwanese, with normal cognitive function.

Критерии исключения

• Presence of other congenital anomalies.
• Currently hospitalized for acute decompensation, or having severe cognitive impairment or psychiatric symptoms that preclude completion of questionnaires.
• Pregnant individuals.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Открытое

Основная цель

Лечение

Центры проведения

Список центров уточняется — проверьте первичный протокол.

Идентификаторы

NCT: NCT07479654 · 25MMHIS443e

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

Открыть это исследование на ClinicalTrials.gov ↗