Investigating the effects of beta-blockers on circadian heart rhythm using heart rate variability in ischemic heart disease with preserved ejection fraction

Saleem, Shiza; Khandoker, Ahsan H.; Alkhodari, Mohanad; Hadjileontiadis, Leontios J.; Jelinek, Herbert F.

doi:10.1038/s41598-023-32963-0

Cited by 5 publications

(3 citation statements)

References 80 publications

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“…HRV is influenced by both components of the autonomic nervous system [7] and represents an individual's ability to adapt to changes in their environment (i.e., faster heart rate with stressor) [9]. Certain diseases and medications can impact HRV, including stroke [43], atrial fibrillation [44], and cardiac medications [45]. Having a history of stroke or atrial fibrillation is also associated with a cognitive decline and risk of dementia [46].…”

Section: Discussionmentioning

confidence: 99%

Associations of Physical Activity and Heart Rate Variability from a Two-Week ECG Monitor with Cognitive Function and Dementia: The ARIC Neurocognitive Study

Marino,

Wu,

Etzkorn

et al. 2024

Sensors

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Low physical activity (PA) measured by accelerometers and low heart rate variability (HRV) measured from short-term ECG recordings are associated with worse cognitive function. Wearable long-term ECG monitors are now widely used, and some devices also include an accelerometer. The objective of this study was to evaluate whether PA or HRV measured from long-term ECG monitors was associated with cognitive function among older adults. A total of 1590 ARIC participants had free-living PA and HRV measured over 14 days using the Zio® XT Patch [aged 72–94 years, 58% female, 32% Black]. Cognitive function was measured by cognitive factor scores and adjudicated dementia or mild cognitive impairment (MCI) status. Adjusted linear or multinomial regression models examined whether higher PA or higher HRV was cross-sectionally associated with higher factor scores or lower odds of MCI/dementia. Each 1-unit increase in the total amount of PA was associated with higher global cognition (β = 0.30, 95% CI: 0.16–0.44) and executive function scores (β = 0.38, 95% CI: 0.22–0.53) and lower odds of MCI (OR = 0.38, 95% CI: 0.22–0.67) or dementia (OR = 0.25, 95% CI: 0.08–0.74). HRV (i.e., SDNN and rMSSD) was not associated with cognitive function. More research is needed to define the role of wearable ECG monitors as a tool for digital phenotyping of dementia.

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Section: Discussionmentioning

confidence: 99%

Associations of Physical Activity and Heart Rate Variability from a Two-Week ECG Monitor with Cognitive Function and Dementia: The ARIC Neurocognitive Study

Marino,

Wu,

Etzkorn

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…There are many factors that both influence an individual’s HRV baseline and are associated with perturbations from an individual’s baseline. Increased age [ 74 ]; male sex [ 74 ]; increased BMI [ 74 ]; poor sleep time and quality [ 75 ]; stress [ 9 ] and anticipation of a stressful event [ 76 ]; consumption of alcohol and/or nicotine [ 77 , 78 ]; dehydration [ 79 ]; acute sickness [ 80 ]; post-vaccination symptomatology [ 81 ]; acute and chronic pain [ 82 , 83 , 84 ]; concussion and post-concussion recovery [ 85 , 86 , 87 ]; travel or training camps [ 8 , 51 ]; medications including but not limited to beta-blockers [ 88 ], angiotensin-converting enzyme inhibitors [ 89 ], contraceptive medications [ 90 ], and antidepressants [ 91 ]; and many psychiatric and physiological diseases [ 91 , 92 ] can be associated with a reduced HRV. Weight loss in overweight and obese individuals is associated with an improved HRV from their original baseline [ 93 ].…”

Section: Factors Interacting With Heart Rate Variabilitymentioning

confidence: 99%

Heart Rate Variability Applications in Strength and Conditioning: A Narrative Review

Addleman,

Lackey,

DeBlauw

et al. 2024

JFMK

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Heart rate variability (HRV) is defined as the fluctuation of time intervals between adjacent heartbeats and is commonly used as a surrogate measure of autonomic function. HRV has become an increasingly measured variable by wearable technology for use in fitness and sport applications. However, with its increased use, a gap has arisen between the research and the application of this technology in strength and conditioning. The goal of this narrative literature review is to discuss current evidence and propose preliminary guidelines regarding the application of HRV in strength and conditioning. A literature review was conducted searching for HRV and strength and conditioning, aiming to focus on studies with time-domain measurements. Studies suggest that HRV is a helpful metric to assess training status, adaptability, and recovery after a training program. Although reduced HRV may be a sign of overreaching and/or overtraining syndrome, it may not be a sensitive marker in aerobic-trained athletes and therefore has different utilities for different athletic populations. There is likely utility to HRV-guided programming compared to predefined programming in several types of training. Evidence-based preliminary guidelines for the application of HRV in strength and conditioning are discussed. This is an evolving area of research, and more data are needed to evaluate the best practices for applying HRV in strength and conditioning.

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“…When assessing HRV, accounting for medications affecting HRV is crucial and is sometimes an important exclusion factor. For example, the results of both hydrophilic and lipophilic β-blockers on HRV suggest a relative complex, but rather positive, association [ 102 , 103 ], as they seem to improve the baroreflex control of HR leading to an increase in RMSSD, pNN50 and HF power with a decrease in the LF/HF ratio [ 104 ], possibly through vagal facilitation [ 105 ] and a more favorable sympathovagal balance. β-blockers are, accordingly, suggested to accelerate HRV recovery in acute heart disease (e.g., heart infraction) patients [ 106 ].…”

Section: Research Implicationsmentioning

confidence: 99%

Heart Rate Variability as a Translational Dynamic Biomarker of Altered Autonomic Function in Health and Psychiatric Disease

et al. 2023

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The autonomic nervous system (ANS) is responsible for the precise regulation of tissue functions and organs and, thus, is crucial for optimal stress reactivity, adaptive responses and health in basic and challenged states (survival). The fine-tuning of central ANS activity relies on the internal central autonomic regulation system of the central autonomic network (CAN), while the peripheral activity relies mainly on the two main and interdependent peripheral ANS tracts, the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS). In disease, autonomic imbalance is associated with decreased dynamic adaptability and increased morbidity and mortality. Acute or prolonged autonomic dysregulation, as observed in stress-related disorders, affects CAN core centers, thereby altering downstream peripheral ANS function. One of the best established and most widely used non-invasive methods for the quantitative assessment of ANS activity is the computerized analysis of heart rate variability (HRV). HRV, which is determined by different methods from those used to determine the fluctuation of instantaneous heart rate (HR), has been used in many studies as a powerful index of autonomic (re)activity and an indicator of cardiac risk and ageing. Psychiatric patients regularly show altered autonomic function with increased HR, reduced HRV and blunted diurnal/circadian changes compared to the healthy state. The aim of this article is to provide basic knowledge on ANS function and (re)activity assessment and, thus, to support a much broader use of HRV as a valid, transdiagnostic and fully translational dynamic biomarker of stress system sensitivity and vulnerability to stress-related disorders in neuroscience research and clinical psychiatric practice. In particular, we review the functional levels of central and peripheral ANS control, the main neurobiophysiologic theoretical models (e.g., polyvagal theory, neurovisceral integration model), the precise autonomic influence on cardiac function and the definition and main aspects of HRV and its different measures (i.e., time, frequency and nonlinear domains). We also provide recommendations for the proper use of electrocardiogram recordings for HRV assessment in clinical and research settings and highlight pathophysiological, clinical and research implications for a better functional understanding of the neural and molecular mechanisms underlying healthy and malfunctioning brain–heart interactions in individual stress reactivity and psychiatric disorders.

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Investigating the effects of beta-blockers on circadian heart rhythm using heart rate variability in ischemic heart disease with preserved ejection fraction

Cited by 5 publications

References 80 publications

Associations of Physical Activity and Heart Rate Variability from a Two-Week ECG Monitor with Cognitive Function and Dementia: The ARIC Neurocognitive Study

Associations of Physical Activity and Heart Rate Variability from a Two-Week ECG Monitor with Cognitive Function and Dementia: The ARIC Neurocognitive Study

Heart Rate Variability Applications in Strength and Conditioning: A Narrative Review

Heart Rate Variability as a Translational Dynamic Biomarker of Altered Autonomic Function in Health and Psychiatric Disease

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