Key result
Biopsychological interventions alter HRV, and reduced SDNN change predicts higher MS-related fatigue.
Why the study?
Fatigue in MS is associated with autonomic nervous system dysfunction, but the relative sensitivity of linear and nonlinear HRV parameters in capturing specific dysfunction remains unclear.
Do biopsychological interventions alter heart rate variability, and do HRV changes predict fatigue in multiple sclerosis?
Do biopsychological interventions alter heart rate variability, and do HRV changes predict fatigue in multiple sclerosis?
Heart rate variability can monitor autonomic activity during psychological interventions and measure reduced autonomic adaptability associated with trait fatigue in multiple sclerosis.
HRV may index trait fatigue in MS; leaves open whether interventions altering it improve outcomes.
Fatigue is a debilitating symptom in multiple sclerosis (MS) associated with autonomic nervous system (ANS) dysfunction. Heart rate variability (HRV) provides a non-invasive measure of ANS function; yet the relative sensitivity of linear and nonlinear HRV parameters in capturing specific ANS (dys)function remains unclear. This study investigated the factorial structure of HRV parameters, their response to biopsychological interventions, and their relationship with MS-related fatigue. Data from two clinical trials ( N = 78) were pooled. Exploratory factor analysis (EFA) was applied to time-domain, frequency-domain, and nonlinear HRV parameters. Repeated-measures ANOVAs examined the effects of self-alert training (SAT; activating), deep breathing (DB; relaxing), and progressive muscle relaxation (PMR; intermediate) on HRV, controlling for age, depression, and disability. Subsequent regression analyses investigated whether HRV changes during a vigilance task predicted MS-related fatigue. EFA revealed two factors, likely reflecting parasympathetic (PNS) or sympathetic (SNS) activity. SAT decreased HRV parameters loaded onto both factors, DB increased parameters related to the factor interpreted as mainly reflecting SNS activity, and PMR affected both factors. Reduced SDNN change during the vigilance task predicted higher trait fatigue, whereas state fatigue was not associated with HRV. HRV offers the potential to monitor PNS-SNS-related activity during psychological interventions and to measure reduced autonomic adaptability in MS-related trait fatigue.
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Garis et al. (2026) studied Multiple sclerosis (n=78). Self-alert training, deep breathing, and progressive muscle relaxation was evaluated on Heart rate variability parameters and multiple sclerosis-related fatigue. Biopsychological interventions altered heart rate variability factors, and reduced SDNN change during a vigilance task predicted higher multiple sclerosis-related trait fatigue.
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