Идёт набор NCT07443670

Voice Analysis to Detect Pulmonary Arterial Pressure Changes in Heart Failure

— Наблюдательное Heart Failure

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают: В протоколе указаны: Daily Voice Recording.
Кому может быть актуально: Состояния в реестре: Heart Failure. Базовые параметры: от 18 лет · Все.
Что важно проверить: Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится: США, Германия
Следующий шаг: Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →

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Официальное название

Voice Analysis Using Artificial Intelligence to Detect Changes in Pulmonary Arterial Pressure in Patients With Heart Failure and an Implanted Pressure Sensor

Обзор

VAPP-HF is a prospective, multi-center, observational study assessing whether daily voice recordings analyzed by a machine learning algorithm can detect changes in pulmonary arterial (PA) pressure in heart failure patients with implanted PA pressure sensors (e.g., CardioMEMS, Cordella). Patients across three sites in Germany and the United States provide daily voice recordings via a mobile app for 12 weeks while continuing standard PA pressure monitoring and heart failure care. Voice data is analyzed retrospectively after study completion; no clinical decisions are based on voice analysis during the study. The primary endpoint is the sensitivity and specificity of the AI-based voice analysis in detecting PA pressure changes at defined thresholds.

Подробное описание

Implanted PA pressure sensors enable early detection of heart failure decompensation but are costly and invasive. Fluid retention in heart failure may affect the vocal apparatus, producing measurable voice changes that could serve as a non-invasive alternative for monitoring pulmonary congestion.

Participants record daily voice samples consisting of sustained vowel sounds and a standardized reading passage via the Noah Labs mobile app. PA pressure readings are collected daily per standard care. Voice recordings and clinical data are analyzed retrospectively using classical machine learning and deep learning approaches. No additional clinical visits are required.

Вмешательства

Другое Daily Voice Recording
Patients record daily voice samples (sustained vowels and a standardized reading passage) using the Noah Labs mobile app. PA pressure readings are collected daily per standard care using the implanted sensor. Voice recordings are analyzed retrospectively using machine learning algorithms after study completion.

Первичные конечные точки

Sensitivity of AI Voice Analysis in Detecting PA Pressure Changes [Срок оценки: 12 weeks]

Вторичные конечные точки (3)

orrelation Between Voice Predictions and Clinical Events [Срок оценки: 12 weeks]
Predictive Accuracy of Machine Learning Models [Срок оценки: 12 weeks]
Adherence to Daily Voice Recording [Срок оценки: 12 weeks]

Критерии участия

Критерии включения

Age 18 years or older
Successful implantation of a PA pressure sensor and monitored by a participating study center
Willingness to record a short predefined text daily for 3 months using a smartphone or tablet
Ability to comfortably read aloud the study passage in English or German
Written informed consent obtained

Критерии исключения

Pregnant, breastfeeding, or unwilling to practice birth control during participation
Condition that in the opinion of the investigator would compromise patient safety or data quality
Pathological voice changes due to surgery or injury
Planned invasive cardiac procedures during the study period
COPD requiring home oxygen therapy
Chronic kidney disease requiring dialysis
Cognitive dysfunction limiting ability to perform daily voice recording
Inability to read English or German
Physical inability to use the recording device

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

Здоровые добровольцы: Нет