Heart rate variability in patients with atrial fibrillation and hypertension

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

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.

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

BACKGROUND

Low physical activity (PA) measured from 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. These monitors can provide long-term HRV data and, if embedded with an accelerometer, they can also provide PA data. Whether PA or HRV measured from long-term ECG monitors is associated with cognitive function among older adults is unknown.

METHODS

Free-living PA and HRV were measured simultaneously over 14-days using the Zio ® XT Patch among 1590 participants in the Atherosclerosis Risk in Communities Study [aged 72-94 years, 58% female, 32% Black]. Total amount of PA was estimated by total mean amplitude deviation (TMAD) from the 14-day accelerometry raw data. HRV indices (SDNN and rMSSD) were measured from the 14-day ECG raw data. Cognitive factor scores for global cognition, executive function, language, and memory were derived using latent variable methods. Dementia or mild cognitive impairment (MCI) status was adjudicated. 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. Models were adjusted for demographic and medical comorbidities.

RESULTS

Each 1-unit higher in total amount of PA was significantly associated with 0.30 higher global cognition factor scores (95% CI: 0.16-0.44), 0.38 higher executive function factor scores (95% CI: 0.22-0.53), and 62% lower odds of MCI (OR: 0.38, 95% CI: 0.22-0.67) or 75% lower odds of dementia (OR: 0.25, 95% CI: 0.08-0.74) versus unimpaired cognition. Neither HRV measure was significantly associated with cognitive function or dementia.

CONCLUSIONS

PA derived from a 2-week ECG monitor with an embedded accelerometer was significantly associated with higher cognitive test performance and lower odds of MCI/dementia among older adults. By contrast, HRV indices measured over 2 weeks were not significantly associated with cognitive outcomes. More research is needed to define the role of wearable ECG monitors as a tool for digital phenotyping of dementia.

CLINICAL PERSPECTIVE

What Is New?: This cross-sectional study evaluated associations between physical activity (PA) and heart rate variability (HRV) measured over 14 days from a wearable ECG monitor with cognitive function.Higher total amount of PA was associated with higher global cognition and executive function, as well as lower odds of mild cognitive impairment or dementia.HRV indices measured over 2 weeks were not significantly associated with cognitive outcomes.What Are the Clinical Implications?: These findings replicate positive associations between PA and cognitive function using accelerometer data from a wearable ECG monitor with an embedded accelerometer.These findings raise the possibility of using wearable ECG monitors (with embedded accelerometers) as a promising tool for digital phenotyping of dementia.

The autonomic nervous system in atrial fibrillation-pathophysiology and non-invasive assessment

The autonomic nervous system plays a crucial role in atrial fibrillation pathophysiology. Parasympathetic hyperactivity result in a shortening of the action potential duration, a reduction of the conduction wavelength, and as such facilitates reentry in the presence of triggers. Further, autonomic remodeling of atrial myocytes in AF includes progressive sympathetic hyperinnervation by increased atrial sympathetic nerve density and sympathetic atrial nerve sprouting. Knowledge on the pathophysiological process in AF, including the contribution of the autonomic nervous system, may in the near future guide personalized AF management. This review focuses on the role of the autonomic nervous system in atrial fibrillation pathophysiology and non-invasive assessment of the autonomic nervous system.

The impact of visit-to-visit heart rate variability on all-cause mortality in atrial fibrillation

OBJECTIVE

We aimed to investigate the association between visit-to-visit heart rate variability (VVHRV) and all-cause mortality in patients diagnosed with atrial fibrillation (AF). Previous studies have shown a positive correlation between VVHRV and several adverse outcomes. However, the relationship between VVHRV and the prognosis of AF remains uncertain.

METHODS

In our study, we aimed to examine the relationship between VVHRV and mortality rates among 3983 participants with AF, who were part of the AFFIRM study (Atrial Fibrillation Follow-Up Investigation of Rhythm Management). We used the standard deviation of heart rate (HRSD) to measure VVHRV and divided the patients into four groups based on quartiles of HRSD (1st, <5.69; 2nd, 5.69-8.00; 3rd, 8.01-11.01; and 4th, ≥11.02). Our primary endpoint was all-cause death, and we estimated the hazard ratios for mortality using the Cox proportional hazard regressions.

RESULTS

Our analysis included 3983 participants from the AFFIRM study and followed for an average of 3.5 years. During this period, 621 participants died from all causes. In multiple-adjustment models, we found that the lowest and highest quartiles of HRSD independently predicted an increased risk of all-cause mortality compared to the other two quartiles, presenting a U-shaped relationship (1st vs 2nd, hazard ratio = 2.28, 95% CI = 1.63-3.20, p < .01; 1st vs. 3rd, hazard ratio = 2.23, 95% CI = 1.60-3.11, p < .01; 4th vs. 2nd, hazard ratio = 1.82, 95% CI = 1.26-2.61, p < .01; and 4th vs. 3rd, hazard ratio = 1.78, 95% CI = 1.25-2.52, p < .01).

CONCLUSION

In patients with AF, we found that both lower VVHRV and higher VVHRV increased the risk of all-cause mortality, indicating a U-shaped curve relationship.

HEART RATE VARIABILITY PARAMETERS WERE NOT ASSOCIATED WITH 30-DAY ALL-CAUSE MORTALITY IN INTENSIVE CARE UNIT PATIENTS WITH OR WITHOUT ATRIAL FIBRILLATION: A RETROSPECTIVE STUDY OF THE MIMIC-IV DATABASE

ABSTRACT

Objective: Our study aims to evaluate the association between heart rate variability (HRV) and short- and long-term prognosis in patients admitted to intensive care unit (ICU). Methods and Results: Adult patients continuously monitored for over 24 h in ICUs from the the American Medical Information Mart for Intensive Care (MIMIC)-IV Waveform Database were recruited in our study. Twenty HRV-related variables (8 time domain, 6 frequency domain, and 6 nonlinear variables) were calculated based on RR intervals. The association between HRV and all-cause mortality was assessed. Ninety-three patients met the inclusion criteria and were classified into atrial fibrillation (AF) and sinus rhythm (SR) groups, which were further divided into 30-day survivor group and nonsurvivor\groups based on their survival status. The 30-day all-cause mortality rates in AF and SR groups were 36.3% and 14.6%, respectively. All the time domain, frequency domain, and nonlinear HRV parameters did not differ significantly between survivors and nonsurvivors with or without AF (all P > 0.05). Presence of renal failure, malignancy, and elevated blood urea nitrogen level were associated with increased 30-day all-cause mortality in SR patients, while presence of sepsis, infection, higher platelet count, and magnesium level were associated with increased 30-day all-cause mortality in AF patients. Conclusions: Heart rate variability variables were not associated with increased 30-day all-cause mortality in ICU patients with or without AF.

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.

Harmful Impact of Tobacco Smoking and Alcohol Consumption on the Atrial Myocardium

Tobacco smoking and alcohol consumption are widespread exposures that are legal and socially accepted in many societies. Both have been widely recognized as important risk factors for diseases in all vital organ systems including cardiovascular diseases, and with clinical manifestations that are associated with atrial dysfunction, so-called atrial cardiomyopathy, especially atrial fibrillation and stroke. The pathogenesis of atrial cardiomyopathy, atrial fibrillation, and stroke in context with smoking and alcohol consumption is complex and multifactorial, involving pathophysiological mechanisms, environmental, and societal aspects. This narrative review summarizes the current literature regarding alterations in the atrial myocardium that is associated with smoking and alcohol.

Does obstructive sleep apnoea modulate cardiac autonomic function in paroxysmal atrial fibrillation?

PURPOSE

The autonomic nervous system may mediate acute apnoea-induced atrial fibrillation (AF). We compared cardiac autonomic function in paroxysmal atrial fibrillation (PAF) patients with and without obstructive sleep apnoea (OSA).

METHODS

Case control study of 101 patients with PAF recruited at two tertiary centres. All patients underwent in-laboratory polysomnography. ECG signal demonstrating "steady state" sinus rhythm (i.e. with arrhythmic beats and respiratory events excluded) was included in the analysis. Cardiac autonomic function was assessed via measures of heart rate variability (HRV) and reported by sleep stage (REM vs Non-REM) for patients with and without OSA.

RESULTS

Sixty-five (66.3%) of patients were male, mean age 61.5 ± 11.6 years, mean BMI 27.1 ± 4.3 kg/m². Global measures of HRV (triangular index, total power) did not differ between PAF patients with and without OSA in either REM or non-REM sleep. Frequency-domain analysis during non-REM sleep in PAF patients with OSA showed increased cardiac parasympathetic modulation (HF-nu: 39.1 ± 15.7 vs 48.0 ± 14.6, p = 0.008) and reduced cardiac sympathetic modulation (LF-nu 54.1 ± 19.7 vs 43.7 ± 18.0, p = 0.012, LF/HF ratio: 2.1 ± 2.0 vs 1.2 ± 1.0, p = 0.007). Results remained significant after adjusting for age, sex, and BMI (adjusted p values 0.024, 0.045 and 0.018 respectively). There were no differences in HRV parameters during REM sleep.

CONCLUSIONS

This is the first study of HRV in PAF patients with and without OSA. Our results indicate limited differences in HRV between groups. However, this work suggests a chronic increase in parasympathetic nervous modulation and relative reduction in sympathetic modulation in PAF patients with OSA during steady-state non-REM sleep.

Efficient on-site confirmatory testing for atrial fibrillation with derived 12-lead ECG in a wireless body area network

Smartphones that can support and assist the screening of various cardiovascular diseases are gaining popularity in recent years. The timely detection, diagnosis, and treatment of atrial fibrillation (AF) are critical, especially for those who are at risk of stroke. AF detection via screening with wearable devices should always be confirmed by a standard 12-lead electrocardiogram (ECG). However, the inability to perform on-site AF confirmatory testing results in increased patient anxiety, followed by unnecessary diagnostic procedures and treatments. Also, the delay in confirmation procedure may conclude the condition as non-AF while it was indeed present at the time of screening. To overcome these challenges, we propose an efficient on-site confirmatory testing for AF with 12-lead ECG derived from the reduced lead set (RLS) in a wireless body area network (WBAN) environment. The reduction in the number of leads enhances the comfort level of patients as well as minimizes the hurdles associated with continuous telemonitoring applications such as data transmission, storage, and bandwidth of the overall system. The proposed method is characterized by segment-wise regression and a lead selection algorithm, facilitating improved P-wave reconstruction. Further, an efficient AF detection algorithm is proposed by incorporating a novel three-level P-wave evidence score with an RR irregularity evidence score. The proposed on-site AF confirmation test reduces false positives and false negatives by 88% and 53% respectively, compared to single lead screening. In addition, the proposed lead derivation method improves accuracy, F 1 -score, and Matthews correlation coefficient (MCC) for the on-site AF detection compared to existing related methods.

The validity and reliability of ultra-short-term heart rate variability parameters and the influence of physiological covariates

Ultra-short-term (UST) heart rate variability (HRV) metrics have increasingly been proposed as surrogates for short-term HRV metrics. However, the concurrent validity, within-day reliability, and between-day reliability of UST HRV have yet to be comprehensively documented. Thirty-six adults (18 males, age: 26 ± 5 yr, BMI: 24 ± 3 kg/m²) were recruited. Measures of HRV were quantified in a quiet-stance upright orthostatic position via three-lead electrocardiogram (ADInstruments, FE232 BioAmp). All short-term data recordings were 300 s in length and five UST time points (i.e., 30 s, 60 s, 120 s, 180 s, and 240 s) were extracted from the original 300-s recording. Bland-Altman plots with 95% limits of agreement, repeated measures ANOVA and two-tailed paired t tests demarcated differences between UST and short-term recordings. Linear regressions, coefficient of variation, intraclass correlation coefficients, and other tests examined the validity and reliability in both time- and frequency domains. No group differences were noted between all short-term and UST measures, for either time- (all P > 0.202) or frequency-domain metrics (all P > 0.086). A longer recording duration was associated with augmented validity and reliability, which was less impacted by confounding influences from physiological variables (e.g., respiration rate, carbon dioxide end-tidals, and blood pressure). Conclusively, heart rate, time-domain, and relative frequency-domain HRV metrics were acceptable with recordings greater or equal to 60 s, 240 s, and 300 s, respectively. Future studies employing UST HRV metrics should thoroughly understand the methodological requirements to obtain accurate results. Moreover, a conservative approach should be utilized regarding the minimum acceptable recording duration, which ensures valid/reliable HRV estimates are obtained.NEW & NOTEWORTHY A one size fits all methodological approach to quantify HRV metrics appears to be inappropriate, where study design considerations need to be conducted upon a variable-by-variable basis. The present results found 60 s (heart rate), 240 s (time-domain parameters), and 300 s (relative frequency-domain parameters) were required to obtain accurate and reproducible metrics. The lower validity/reliability of the ultra-short-term metrics was attributable to measurement error and/or confounding from extraneous physiological influences (i.e., respiratory and hemodynamic variables).