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

Sleep disorders as both risk factors for, and a consequence of, stroke: A narrative review

BACKGROUND AND PURPOSE

Sleep disorders are increasingly implicated as risk factors for stroke, as well as a determinant of stroke outcome. They can also occur secondary to the stroke itself. In this review, we describe the variety of different sleep disorders associated with stroke and analyze their effect on stroke risk and outcome.

METHODS

A search term-based literature review ("sleep," "insomnia," "narcolepsy," "restless legs syndrome," "periodic limb movements during sleep," "excessive daytime sleepiness" AND "stroke" OR "cerebrovascular" in PubMed; "stroke" and "sleep" in ClinicalTrials.gov) was performed. English articles from 1990 to March 2023 were considered.

RESULTS

Increasing evidence suggests that sleep disorders are risk factors for stroke. In addition, sleep disturbance has been reported in half of all stroke sufferers; specifically, an increase is not only sleep-related breathing disorders but also periodic limb movements during sleep, narcolepsy, rapid eye movement (REM) sleep behavior disorder, insomnia, sleep duration, and circadian rhythm sleep-wake disorders. Poststroke sleep disturbance has been associated with worse outcome.

CONCLUSION

Sleep disorders are risk factors for stroke and associated with worse stroke outcome. They are also a common consequence of stroke. Recent guidelines suggest screening for sleep disorders after stroke. It is possible that treatment of sleep disorders could both reduce stroke risk and improve stroke outcome, although further data from clinical trials are required.

Cardiovascular remodeling in active and controlled acromegaly: association with sleep-disordered breathing

PURPOSE

We hypothesized that an unfavorable cardiovascular profile in acromegaly is associated with sleep-disordered breathing (SDB), while acromegaly control improves both respiratory sleep characteristics and the cardiovascular profile.

METHODS

The patients underwent the assessment of breathing during sleep and cardiovascular profile assessment at the start of the study including arterial stiffness, blood pressure, echocardiography, nocturnal heart rate variability (HRV). The assessment was repeated in patients with acromegaly at 1 year after transsphenoidal adenectomy (TSA).

RESULTS

A total of 47 patients with acromegaly and 55 control subjects were enrolled. At one year after TSA, 22 patients with acromegaly were reassessed. Multiple linear regression analysis with adjustment for age, sex and body mass index (BMI) showed the associations of insulin growth-like factor 1 (IGF-1) with obstructive apnea index (OAI: β=0.035/h, p<0.001), but not with cardiovascular parameters, in patients with acromegaly. The analysis of combined acromegaly and control dataset with adjustment for age, sex and BMI showed the association the presence of acromegaly with diastolic blood pressure (DBP; β=17.99 mmHg, p<0.001), ejection fraction (EF; β=6.23%, p=0.009), left heart remodeling (left ventricle posterior wall: β=0.81 mm, p=0.045) and the association of the presence of SDB (apnea-hypopnea index≥15/h) with left ventricular function (EF: -4.12%, p=0.040; end systolic volume: 10.12 ml, p=0.004). Control of acromegaly was accompanied by the decrease in OAI (5.9 [0.8, 14.5]/h and 1.7 [0.2, 5.1]/h, p=0.004) and nocturnal heart rate (66.1 [59.2, 69.8] bpm and 61.7 [54.0, 67.2] bpm, p=0.025) and by the increase in blood pressure (DBP: 78.0 [70.3, 86.0] mm Hg and 80.0 [80.0, 90.0] mm Hg, p=0.012).

CONCLUSION

The comorbidities of acromegaly, including sleep-disordered breathing, appear to have a long-term effect on cardiovascular remodeling in active acromegaly. Future studies should investigate the applicability of the treatment of SDB for the reduction of cardiovascular risk in acromegaly.

Blood pressure variability, nocturnal heart rate variability and endothelial function predict recurrent cerebro-cardiovascular events following ischemic stroke

Introduction

Cardiovascular parameters characterizing blood pressure (BP), heart rate (HR), endothelial function and arterial stiffness predict cerebro-cardiovascular events (CCVE) in the general population. Considering the paucity of data in stroke patients, we assessed these parameters as potential predictors of recurrent CCVE at acute stroke stroke.

Patients and methods

This is a secondary outcome analysis of a prospective observational longitudinal Sleep Deficiency & Stroke Outcome Study (ClinicalTrials.gov Identifier: NCT02559739). The study consecutively recruited acute ischemic stroke patients. Cardiovascular parameters (blood pressure variability [BPV], heart rate variability [HRV], endothelial function, and arterial stiffness) were assessed within the first week post-stroke. Future CCVE were recorded over a 3-year follow-up. Multivariate Cox regression analysis was used to investigate the prognostic value of 48 cardiovascular parameters regarding CCVE risk.

Results

Out of 447 recruited patients, 359 were included in this analysis. 20% of patients developed a future CCVE. A high variability of systolic BP (n = 333) and nocturnal HR (non-linear parameters; n = 187) at acute stroke predicted CCVE risk after adjustment for demographic parameters, cardiovascular risk factors and mean BP or HR, respectively. Endothelial dysfunction (n = 105) at acute stroke predicted CCVE risk after adjustment for age and sex, but not after adjustment for cardiovascular risk factors. Diurnal HR and arterial stiffness at acute stroke were not associated with CCVE risk.

Conclusion

High blood pressure variability, high nocturnal HRV and endothelial function contribute to the risk for future CCVE after stroke.

Data lake-driven analytics identify nocturnal non-dipping of heart rate as predictor of unfavorable stroke outcome at discharge

BACKGROUND

Post-stroke heart rate (HR) and heart rate variability (HRV) changes have been proposed as outcome predictors after stroke. We used data lake-enabled continuous electrocardiograms to assess post-stroke HR and HRV, and to determine the utility of HR and HRV to improve machine learning-based predictions of stroke outcome.

METHODS

In this observational cohort study, we included stroke patients admitted to two stroke units in Berlin, Germany, between October 2020 and December 2021 with final diagnosis of acute ischemic stroke or acute intracranial hemorrhage and collected continuous ECG data through data warehousing. We created circadian profiles of several continuously recorded ECG parameters including HR and HRV parameters. The pre-defined primary outcome was short-term unfavorable functional outcome after stroke indicated through modified Rankin Scale (mRS) score of > 2.

RESULTS

We included 625 stroke patients, 287 stroke patients remained after matching for age and National Institute of Health Stroke Scale (NIHSS; mean age 74.5 years, 45.6% female, 88.9% ischemic, median NIHSS 5). Both higher HR and nocturnal non-dipping of HR were associated with unfavorable functional outcome (p < 0.01). The examined HRV parameters were not associated with the outcome of interest. Nocturnal non-dipping of HR ranked highly in feature importance of various machine learning models.

CONCLUSIONS

Our data suggest that a lack of circadian HR modulation, specifically nocturnal non-dipping, is associated with short-term unfavorable functional outcome after stroke, and that including HR into machine learning-based prediction models may lead to improved stroke outcome prediction.

Association of Obstructive Sleep Apnea and Atrial Fibrillation in Acute Ischemic Stroke: A Cross-Sectional Study

Background: There is a growing body of evidence suggesting a link between obstructive sleep apnea (OSA) and atrial fibrillation (AF). The primary objective of this study is to evaluate the association between OSA and AF in acute ischemic stroke. The secondary objective is to describe the clinical features of patients with acute ischemic stroke and concomitant OSA. Methods: We enrolled consecutive patients with acute ischemic stroke. All patients underwent full-night cardiorespiratory polygraphy. To determine if there is an association between AF and OSA, we compared the observed frequency of this association with the expected frequency from a random co-occurrence of the two conditions. Subsequently, patients with and without OSA were compared. Results: A total of 174 patients were enrolled (mean age 67.3 ± 11.6 years; 95 males). OSA and AF were present in 89 and 55 patients, respectively. The association OSA + AF was observed in 33/174 cases, which was not statistically different compared to the expected co-occurrence of the two conditions. Patients with OSA showed a higher neck circumference and body mass index, a higher prevalence of hypertension and dysphagia, and a higher number of central apneas/hypoapneas. In the multivariate analysis, dysphagia and hypertension were independent predictors of OSA. A positive correlation was observed between OSA severity, BMI, and neck circumference. The number of central apneas/hypoapneas was positively correlated with stroke severity. Conclusions: Our data suggest that OSA and AF are highly prevalent but not associated in acute stroke. Our findings support the hypothesis that OSA acts as an independent risk factor for stroke.

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

Background: Heart rate variability (HRV) is a non-invasive marker of autonomic nervous system function that is based on the analysis of length differences between subsequent RR intervals of the electrocardiogram. The aim of this systematic review was to assess the current knowledge gap in the utility of HRV parameters and their value as predictors of the acute stroke course. Methods: A systematic review was performed in accordance with the PRISMA guidelines. Relevant articles published between 1 January 2016 and 1 November 2022 available in the PubMed, Web of Science, Scopus, and Cochrane Library databases were obtained using a systematic search strategy. The following keywords were used to screen the publications: "heart rate variability" AND/OR "HRV" AND "stroke." The eligibility criteria that clearly identified and described outcomes and outlined restrictions on HRV measurement were pre-established by the authors. Articles assessing the relationship between HRV measured in the acute phase of stroke and at least one stroke outcome were considered. The observation period did not exceed 12 months. Studies that included patients with medical conditions influencing HRV with no established stroke etiology and non-human subjects were excluded from the analysis. To minimize the risk of bias, disagreements throughout the search and analysis were resolved by two independent supervisors. Results: Of the 1,305 records obtained from the systematic search based on keywords, 36 were included in the final review. These publications provided insight into the usability of linear and non-linear HRV analysis in predicting the course, complications, and mortality of stroke. Furthermore, some modern techniques, such as HRV biofeedback, for the improvement of cognition performance after a stroke are discussed. Discussion: The present study showed that HRV could be considered a promising biomarker of a stroke outcome and its complications. However, further research is needed to establish a methodology for appropriate quantification and interpretation of HRV-derived parameters.

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

Obstructive sleep apnea (OSA) is related to the progression of cardiovascular diseases (CVD); it is an independent risk factor for stroke and is also prevalent post-stroke. Furthermore, heart rate corrected QT (QTc) is an important predictor of the risk of arrhythmia and CVD. Thus, we aimed to investigate QTc interval variations in different sleep stages in OSA patients and whether nocturnal QTc intervals differ between OSA patients with and without stroke history. 18 OSA patients (apnea-hypopnea index (AHI)≥15) with previously diagnosed stroke and 18 OSA patients (AHI≥15) without stroke history were studied. Subjects underwent full polysomnography including an electrocardiogram measured by modified lead II configuration. RR, QT, and QTc intervals were calculated in all sleep stages. Regression analysis was utilized to investigate possible confounding effects of sleep stages and stroke history on QTc intervals. Compared to patients without previous stroke history, QTc intervals were significantly higher (β = 34, p<0.01) in patients with stroke history independent of age, sex, body mass index, and OSA severity. N3 sleep (β = 5.8, p<0.01) and REM sleep (β = 2.8, p<0.01) increased QTc intervals in both patient groups. In addition, QTc intervals increased progressively (p<0.05) towards deeper sleep in both groups; however, the magnitude of changes compared to the wake stage was significantly higher (p<0.05) in patients with stroke history. The findings of this study indicate that especially in deeper sleep, OSA patients with a previous stroke have an elevated risk for QTc prolongation further increasing the risk for ventricular arrhythmogenicity and sudden cardiac death.

Stroke-Heart Syndrome: Recent Advances and Challenges

After ischemic stroke, there is a significant burden of cardiovascular complications, both in the acute and chronic phase. Severe adverse cardiac events occur in 10% to 20% of patients within the first few days after stroke and comprise a continuum of cardiac changes ranging from acute myocardial injury and coronary syndromes to heart failure or arrhythmia. Recently, the term stroke–heart syndrome was introduced to provide an integrated conceptual framework that summarizes neurocardiogenic mechanisms that lead to these cardiac events after stroke. New findings from experimental and clinical studies have further refined our understanding of the clinical manifestations, pathophysiology, and potential long‐term consequences of the stroke–heart syndrome. Local cerebral and systemic mediators, which mainly involve autonomic dysfunction and increased inflammation, may lead to altered cardiomyocyte metabolism, dysregulation of (tissue‐resident) leukocyte populations, and (micro‐) vascular changes. However, at the individual patient level, it remains challenging to differentiate between comorbid cardiovascular conditions and stroke‐induced heart injury. Therefore, further research activities led by joint teams of basic and clinical researchers with backgrounds in both cardiology and neurology are needed to identify the most relevant therapeutic targets that can be tested in clinical trials.

Heart rate variability as an autonomic biomarker in ischemic stroke

Stroke is one of the leading causes of mortality and disability worldwide. Autonomic dysfunction after ischemic stroke is frequently associated with cardiac complications and high mortality. The brain-heart axis is a good model for understanding autonomic interaction between the autonomic central network and the cardiovascular system. Heart rate variability (HRV) analysis is a non-invasive approach for understanding cardiac autonomic regulation. In stroke patients, HRV parameters are altered in the acute and chronic stages of the disease, having a prognostic value. In this literature review we summarize the main concepts about the autonomic nervous system and HRV as autonomic biomarkers in ischemic stroke.