Heart rate variability (HRV), a measure of autonomic nervous system function, has shown potential as a predictor of cardiovascular events, including stroke. Decreased HRV is associated with elevated cardiovascular risk and may reflect autonomic dysfunction and inflammation, which are known contributors to stroke. Given the significant health impact of stroke, evaluating HRV as a predictor for stroke risk has gained increasing attention in cardiovascular research [2, 8,].

Objectives

This systematic review aimed to assess the association between HRV and stroke risk in human populations. Specifically, it sought to identify HRV parameters most predictive of stroke and evaluate factors influencing this association, such as age, inflammation, and comorbidities.

Methodology

We conducted a systematic search of studies examining HRV and stroke risk across databases, including PubMed, Cochrane Library, and Embase, for publications between January 2000 and January 2024. Studies were selected based on HRV measurements and reported stroke outcomes in human populations. Data on HRV parameters, population characteristics, and stroke incidence were extracted, and meta-analyses were conducted where feasible. Effect sizes were calculated using hazard ratios and relative risks with 95% confidence intervals, and heterogeneity was assessed through the I² statistic [7, 10, 14].

 

Results

The review identified that lower nighttime HRV is significantly associated with an increased risk of cardiovascular events, including stroke and myocardial infarction. Individuals in the lowest HRV quartile had up to a twofold increase in stroke risk compared to those with higher HRV. Additionally, elevated inflammatory biomarkers, such as hs-CRP, were inversely correlated with HRV, indicating that chronic inflammation may exacerbate autonomic dysfunction, thereby elevating cardiovascular risk. These findings underscore the potential of nighttime HRV as a non-invasive predictor for early cardiovascular risk assessment.

Conclusion 

This systematic review supports using HRV as a predictor of stroke risk, underscoring its potential role in early cardiovascular risk assessment. Reduced HRV, particularly SDNN, could be a non-invasive biomarker to identify individuals at elevated stroke risk. Further research is warranted to standardize HRV measurement protocols and evaluate their applicability in diverse populations.