Remote Monitoring for Patients With Aortic Stenosis

A vizsgálat adatai

Ki végzi

Baker Heart and Diabetes Institute

Azonosító

NCT07690748

A regiszteradat frissítve

2026. július 8.

Eredeti leírás

Remote-AS aims to develop a remote digital monitoring cohort of people with AS and use these data to establish a digital twin intervention to personalise risks and benefits, and optimise the time of surgical or transcatheter aortic valve replacement (AVR) referral. Our digital solution will also seek modelling for optimal care for patients to whom AVR is indicated who choose not to undergo the procedure, supporting a patient-selected observational strategy for managing heart failure symptoms, facilitating patient education and self-care.A teljes eredeti leírásKevesebb

Remote Monitoring for Asymptomatic Patients With Moderate to Severe Aortic Valve Stenosis - Remote-AS

Remote-AS aims to develop a remote digital monitoring cohort of people with AS and use these data to establish a digital twin intervention to personalise risks and benefits, and optimise the time of surgical or transcatheter aortic valve replacement (AVR) referral. Our digital solution will also seek modelling for optimal care for patients to whom AVR is indicated who choose not to undergo the procedure, supporting a patient-selected observational strategy for managing heart failure symptoms, facilitating patient education and self-care.

Objectives of the study are:

* To establish a large-scale interdisciplinary research program to drive implementation of substantial improvements to health care and/or health system effectiveness in patients with aortic stenosis (AS) * To establish a new model of patient-centred management strategy for asymptomatic severe AS to inform the optimal time at which valve intervention should take place * For patients to whom AVR is indicated who choose not to undergo the procedure, to support a patient-selected observational strategy for managing heart failure symptoms * To develop a digital twin with predictive capabilities of artificial intelligence (AI) for guiding the optimal timing of AVR in patients with asymptomatic severe AS

Participants will be patients with asymptomatic moderate to severe native AS (n=160) (based on guideline-recommended diagnosis and care with peak aortic velocity >3.5m/sec).

Participants will undergo:

Wearables: collection of physiological (e.g., blood pressure, heart rate, rhythm) and behavioural (physical activity) data through a wearable device ('smart watch'), collected through the comprehensive remote heart health monitoring and automated feedback delivery system app SMART.

Patient reported outcome measures: KCCQ-CSS; EQ-5D-5L index score; "Toronto Aortic Stenosis" quality of life questionnaires.

Advanced cardiovascular imaging: Cardiovascular magnetic resonance (CMR) imaging; 31phosphorus magnetic resonance spectroscopy (31P-MRS); proton magnetic resonance spectroscopy (1H-MRS); echocardiography.

Comprehensive plasma proteome profiling: Plasma proteomic preparation coupled with the Orbitrap Astral mass spectrometer.

Recording of clinical outcomes.

Bevonási feltételek: Male or female ≥18 years of age; Suitable to undergo MRI scans; With asymptomatic moderate to severe native AS (based on guideline-recommended diagnosis and care); Eligible for Medicare; Ability and willingness to provide written and informed consent and to comply with the requirements of the study.

Kizáró feltételek: Known hypersensitivity to adenosine (ever requiring hospital admission with asthma or chronic obstructive pulmonary disease) or gadolinium; Serious comorbidity other than AS that limits the life expectancy (<2 years), or affects study participation or outcome (severe frailty and mobility issues [Rockwood frailty score >6], severe kidney disease eGFR<30, infiltrative cardiomyopathy); Known heart failure or reduced left ventricular ejection fraction (<50%); Significant renal impairment (eGFR<30ml/min/m2); Moderate or above valvular pathology other than AS; Contra-indications to CMR (including presence of foreign metallic bodies).

ClinicalTrials.gov NCT07690748