Year: 2022
Type: dissertation
Study design: Observational Study
Abstract: One of the greatest achievements of humanity was the tremendous increase in lifespan. However, this increase has not been followed by a similar increase in healthspan. To expand healthspan, new biomarkers of aging and disease are being developed to improve the knowledge regarding the aging process and the emergence of diseases. A highly accessible source of non-invasive biomarkers is the dynamics of heart rate. The analysis of this dynamics provides indirect access to the state of the autonomic nervous system, the integrity of the heart’s main pacemaker – the sinoatrial node –, and the interactions between the two. The Heart Rate Variability (HRV) temporal and frequency approaches correspond to the traditional and most widely used methods to measure heart rate dynamics. However, they have failed to permeate clinical practice due to inconsistent results among high-risk groups, such as in the elderly and in patients with cardiovascular diseases. Phase-Rectified Signal Averaging (PRSA) and Heart Rate Fragmentation (HRF) are two newer approaches developed to address some of the major problems that are associated with the HRV approach. In this dissertation, we investigate the changes in heart rate dynamics with age, with the severity of atrial fibrillation (AF), and with prevalent congestive heart failure (CHF), using HRV, PRSA, and HRF indices. We also provide an in-depth revision on the physiological mechanisms linking changes in these dynamical indices and the referred contexts. We found HRF indices to be more associated with the aging process and AF severity than PRSA and HRV indices. Whereas, PRSA and HRV indices were slightly more associated with CHF. Nonetheless, when HRF indices were added to PRSA and HRV linear regression models of CHF, the performance of the resulting models improved. We also provide an estimate of the minimum electrocardiogram duration for computation of HRF indices, which we found to be 2 to 10 minutes.
Author: Pires, Mafalda Helena de Albuquerque Martins Pereira
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7036527527