STRONG-AV
Research type
Research Study
Full title
Identification of the most useful markers of Frailty to predict outcomes in patients undergoing Transcatheter Aortic Valve Implantation.
IRAS ID
349259
Contact name
Timothy Bagnall
Contact email
Sponsor organisation
University Hospitals Sussex
Duration of Study in the UK
1 years, 1 months, 1 days
Research summary
Transcatheter Aortic Valve Implantation (TAVI) is a well-established treatment for patients with severe aortic stenosis and has been shown to improve survival and quality of life. Patient selection remains crucial in identifying patients who will have successful short and long-term outcomes following intervention.
Frailty is a clinical syndrome related to the ageing process through which body systems lose physiological reserves to respond to both pathological and iatrogenic stressors. There is growing evidence that suggests that frailty is associated with poorer outcomes following TAVI including death and disability in both the short and long-term. An assessment of frailty is also recommended by national guidelines as part of the decision-making, however, frailty assessments are often relatively subjective with multiple frailty indices/scales used in current clinical practice with no clear guidance for which scale is most appropriate for TAVI patients.
Frailty is a complex disease state, which encompasses physical, functional, biochemical, and cognitive domains. There is growing evidence that frailty can be more objectively assessed by using imaging such as CT, certain metabolic markers and functional tests.
This study has two primary aims. Firstly we will assess whether CT markers of frailty can be used to predict mortality following TAVI and assess their ability to identify frailty compared to the current methods used. Secondly we will prospectively examine whether CT, in addition to other markers of frailty, can be used to identify which patients are likely to gain the greatest symptomatic benefit from TAVI. In the long-term our hope is that this project may also allow us to develop our own Clinical Predictive Model which incorporates these markers.
REC name
London - Surrey Borders Research Ethics Committee
REC reference
25/LO/0131
Date of REC Opinion
27 Feb 2025
REC opinion
Favourable Opinion