Undiagnosed latent heart failure in frail older individuals: diastolic dysfunction and dysmetabolism
Description: Objective: To determine if integrative cardiogeriatric profile incorporating frailty assessment, echocardiography, biomarkers, physical performance, clinical information and serum metabolome can indicate preclinical HF and predict adverse outcomes in community-living older adults.
Design: Prospective, observational, longitudinal cohort study.
Setting: Community-based study population.
Participants: 1400 community-living male and female outpatients aged 60 years or above with no previous diagnosis of HF.
Study instruments: FRAIL frailty assessment scale, NYHA functional class, echocardiography, biomarkers (NT-proBNP, GDF-15 and GDF-11), physical performance measures (6-minute walk distance, gait speed, handgrip strength), SARC-F sarcopenia index, clinical information, and nutritional assessment.
Main outcome measures:
1) Primary endpoints – HF hospitalisation; adverse cardiovascular events; all-cause and cardiac mortality.
2) Secondary endpoints – change in serum biomarker-stratified metabolomic profile relative to change in FRAIL, NYHA class, physical performance, biomarker level, and/or myocardial function on echocardiography; derivation of metabolome and multi-dimensional biosignature for prediction model of adverse outcomes.
Expected results: Community-living elderly with moderate DD, frailty, poor physical performance, abnormal biomarker levels and adverse metabolomic biosignature represent a population with preclinical HF, and have a worse prognosis including future hospitalisation and mortality than those with mild or no DD, no frailty, good physical performance, and below-threshold level of cardiac biomarkers. A prediction model can be developed to summarise and accurately predict adverse outcomes.
Implications: Focused cardiogeriatric assessment of community-living older adults may identify preclinical HF and individuals at risk of future hospitalisation and death.
Funder: Health and Medical Research Fund
Amount: HKD 1,487,000
Funding type: grant
Funder scheme: HMRF - Advanced Medical Research
Start date: 2018-01-01
Investigator: Erik Yee Mun George FUNG
Institution: Department of Medicine and Therapeutics, The Chinese University of Hong Kong
Funded outputs count: 4
Funder award ID: 07181036
OpenAlex ID: G4881714253