Cardiac autonomic dynamics during sleep are lost in patients with TIA and stroke

Abstract

Ischaemic stroke is accompanied by important alterations of cardiac autonomic control, which have an impact on stroke outcome. In sleep, cardiac autonomic control oscillates with a predominant sympathetic modulation during REM sleep. We aimed to assess cardiac autonomic control in different sleep stages in patients with ischaemic stroke. Forty‐five patients enrolled in the prospective, multicentre SAS‐CARE study but without significant sleep‐disordered breathing (apnea–hypopnea index < 15/hr) and without atrial fibrillation were included in this analysis. The mean age was 56 years, 68% were male, 76% had a stroke (n = 34, mean National Institutes of Health Stroke Scale [NIHSS] score of 5, 11 involving the insula) and 24% (n = 11) had a transitory ischaemic attack. Cardiac autonomic control was evaluated using three different tools (spectral, symbolic and entropy analysis) according to sleep stages on short segments of 250 beats in all patients. Polysomnographic studies were performed within 7 days and 3 months after the ischaemic event. No significant differences in cardiac autonomic control between sleep stages were observed in the acute phase and after 3 months. Predominant vagal modulation and decreased sympathetic modulation were observed across all sleep stages in ischaemic stroke involving the insula. Patients with ischaemic stroke and transitory ischaemic attack present a loss of cardiac autonomic dynamics during sleep in the first 3 months after the ischaemic event. This change could represent an adaptive phenomenon, protecting the cardiovascular system from the instabilities of autonomic control, or a risk factor for stroke, which precedes the ischaemic event.

Inter-sleep stage variations in corrected QT interval differ between obstructive sleep apnea patients with and without stroke history

“…stroke Tobaldini et al reported predominant vagal modulation and decreased sympathetic modulation across all sleep stages[33]. Based on our observation of RR interval variations as a demonstration of sympathovagal balance, the most notable difference occurs in non-REM sleep…”

“…Brunetti et al observed that compared to controls, acute stroke patients have a predominant parasympathetic tone during wake and REM sleep accompanied by a reduction of sympathetic tone in REM and parasympathetic tone during N3 [ 32 ]. Tobaldini et al reported predominant vagal modulation and decreased sympathetic modulation across all sleep stages [ 33 ]. Based on our observation of RR interval variations as a demonstration of sympathovagal balance, the most notable difference occurs in non-REM sleep specifically in N2 and N3 sleep between OSA patients with and without stroke history.…”

Heart rate variability as an autonomic biomarker in ischemic stroke

“…Some studies have demonstrated that autonomic dysfunction in stroke patients could be prolonged for up to four years after the ictus and is manifested as reduced parasympathetic activity 48,49 . Also, recent studies showed that abnormal time-domain (SDNN, RMSS), frequency-domain (LF, HF, spectral power in the very low-frequency range -VLF) parameters and nonlinear entropy parameters (DFA, ApEN) are predictors for stroke severity, functional outcome, and mortality 50 . Less variability, loss of parasympathetic tonus and HRV parameters altered during the sleep cycle are associated with worse prognosis 50,51 .…”

“…Also, recent studies showed that abnormal time-domain (SDNN, RMSS), frequency-domain (LF, HF, spectral power in the very low-frequency range -VLF) parameters and nonlinear entropy parameters (DFA, ApEN) are predictors for stroke severity, functional outcome, and mortality 50 . Less variability, loss of parasympathetic tonus and HRV parameters altered during the sleep cycle are associated with worse prognosis 50,51 . However, HRV parameters as biomarkers for stroke still require the integration of linear and nonlinear methods to expand the risk modeling and improve its predictive value.…”

Heart rate variability as a predictor of stroke course, functional outcome, and medical complications: A systematic review

“…Additionally, there is no universal recommendation which HRV parameters are best for examining the autonomic nervous system. Although researchers have been traditionally using linear time-domain or frequency-domain parameters ( Sethi et al, 2016 ; Chidambaram et al, 2017 ), more recently, researchers have used non-linear parameters such as approximate entropy, multiscale entropy, detrended fluctuations, and fractal dimensions (FDs) ( Tobaldini et al, 2019a ; Tobaldini et al, 2019b ; He et al, 2019 ) to provide additional or alternative insights into the investigated physiological states. Furthermore, the exact mechanism responsible for poor outcomes in patients with stroke showing reduced HRV remains unclear.…”