CPETecho for early diagnosis and deep phenotyping of HFpEF
Heart failure with preserved ejection fraction (HFpEF) is the most common form of heart failure, with limited therapeutic options and a poor prognosis. Challenges in HFpEF diagnosis, undifferentiated treatment of HFpEF patients despite phenotypical differences, and ignoring non-cardiac contribution to this multisystem disorder underly the unfavorable prognosis. Although exercise intolerance is the primary symptom among HFpEF patients, and current guidelines recommend exercise training, the responsible mechanisms remain unclear.
Combined echocardiography and cardiopulmonary exercise testing (CPETecho) is a non-invasive method that can characterize physiological limits to exercise, including in HFpEF patients. In this study, we aim to (1) evaluate whether routine use of CPETecho can improve the accuracy of HFpEF diagnosis, (2) identify subgroups of HFpEF patients with different exercise limitations (exercise phenotypes), and (3) characterize in detail a ‘muscle phenotype’ of HFpEF limited mostly by peripheral muscle oxygenation instead of cardiac limits.
We will recruit HFpEF patients from third-line hospitals and perform CPETecho, apply machine learning algorithms to define HFpEF phenotypes, and combine near-infrared-spectroscopy and muscle biopsies to assess peripheral oxygen extraction. Our study aims to address the clinical need for improved efficiency in HFpEF diagnosis and to identify HFpEF exercise phenotypes, contributing to the precision of HFpEF treatment.
Funding: FWO
Researcher: De Schutter Stephanie
Promotor: Gevaert Andreas
Co-promotor: Van de Heyning Caroline