Antti M. Kiviniemi

Physiological Background of the Loss of Fractal Heart Rate Dynamics

Background—Altered fractal heart rate (HR) dynamics occur during various disease states, but the physiological background of abnormal fractal HR behavior is not well known. We tested the hypothesis that the fractal organization of human HR dynamics is determined by the balance between sympathetic and vagal outflow. Methods and Results—A short-term fractal scaling exponent (&agr;1) of HR dynamics, analyzed by the detrended fluctuation analysis (DFA) method, and the high-frequency (HF) and low-frequency (LF) spectral components of R-R intervals (0.15 to 0.4 Hz; n=13), along with muscle sympathetic nervous activity (MSNA) from the peroneus nerve (n=11), were assessed at rest and during cold face and cold hand immersion in healthy subjects. During cold face immersion, HF power increased (from 6.9±1.3 to 7.6±1.2 ln ms2, P<0.01), as did MSNA (from 32±17 to 44±14 bursts/100 heartbeats, P<0.001), and LF/HF ratio decreased (P<0.01). Cold hand immersion resulted in a similar increase in MSNA (from 34±17 to 52±19 bursts/100 heartbeats, P<0.001) but a decrease in HF spectral power (from 7.0±1.3 to 6.5±1.1 ln ms2, P<0.05) and an increase in the LF/HF ratio (P<0.05). The fractal scaling index &agr;1 decreased in all subjects (from 0.85±0.27 to 0.67±0.30, P<0.0001) during cold face immersion but increased during cold hand immersion (from 0.77±0.22 to 0.97±0.20, P<0.01). Conclusions—The fractal organization of human HR dynamics is determined by a delicate interplay between sympathetic and vagal outflow, with the breakdown of fractal HR behavior toward more random dynamics occurring during coactivation of sympathetic and vagal outflow.

Improved Stratification of Autonomic Regulation for risk prediction in post-infarction patients with preserved left ventricular function (ISAR-Risk)

Aims To investigate the combination of heart rate turbulence (HRT) and deceleration capacity (DC) as risk predictors in post-infarction patients with left ventricular ejection fraction (LVEF) > 30%. Methods and results We enrolled 2343 consecutive survivors of acute myocardial infarction (MI) (<76 years) in sinus rhythm. HRT and DC were obtained from 24 h Holter recordings. Patients with both abnormal HRT (slope ≤ 2.5 ms/RR and onset ≥ 0%) and abnormal DC (≤4.5 ms) were considered suffering from severe autonomic failure (SAF) and prospectively classified as high risk. Primary and secondary endpoints were all-cause, cardiac, and sudden cardiac mortality within the first 5 years of follow-up. During follow-up, 181 patients died; 39 deaths occurred in 120 patients with LVEF ≤ 30%, and 142 in 2223 patients with LVEF>30% (cumulative 5-year mortality rates of 37.9% and 7.8%, respectively). Among patients with LVEF > 30%, SAF identified another high-risk group of 117 patients with 37 deaths (cumulative 5-year mortality rates of 38.6% and 6.1%, respectively). Merging both high-risk groups (i.e. LVEF ≤ 30% and/or SAF) doubled the sensitivity of mortality prediction compared with LVEF ≤ 30% alone (21.1% vs. 42.1%, P < 0.001) while preserving 5-year mortality rate (38.2%). Conclusion In post-MI patients with LVEF>30%, SAF identifies a high-risk group equivalent in size and mortality risk to patients with LVEF ≤ 30%.

Individual responses to aerobic exercise: The role of the autonomic nervous system

It is well established that regular aerobic exercise training reduces all-cause mortality and improves a number of health outcomes. However, a marked heterogeneity in the training-induced changes, e.g. in terms of aerobic fitness, has been observed in healthy human subjects, even with highly standardized training programs. Mean improvements in aerobic fitness, expressed as maximal oxygen consumption, have been about 10-15% of the baseline values, but the training-induced changes have ranged from almost none to a 40% increase. The exact nature of the mechanisms responsible for this heterogeneity in response to regular aerobic exercise is not well known. In this review, we consider evidence of the association between the autonomic nervous system (ANS), aerobic fitness and aerobic training-induced changes in fitness. Results of recent studies support the hypothesis that assessment of ANS functioning includes important information concerning acute and chronic physiological processes before, during and after aerobic exercise training stimulus. Moreover, we show that daily assessment of ANS activity could serve as an indicator of appropriate physiological condition for aerobic training.

Sudden cardiac death after myocardial infarction in patients with type 2 diabetes

BACKGROUND Type 2 diabetes mellitus is a well-established risk factor for atherosclerosis, but its contribution to sudden cardiac death (SCD) risk after myocardial infarction (MI) is not well defined. OBJECTIVE The purpose of this study was to compare the incidence and time-dependent risk of SCD in diabetic patients versus nondiabetic patients during 5-year follow-up after acute MI. METHODS A total of 3,276 patients were enrolled at the time of acute MI between 1996 and 2005. Mean age at entry was 60 ± 11 years, and the cohort was followed until 2009. At entry into the study, diabetes was present in 629 (19.2%) patients. The primary endpoint was SCD, and the secondary endpoints were non-SCD and all-cause mortality. RESULTS Among diabetic patients, the incidence of SCD was higher (5.9%) than in nondiabetic patients (1.7%), with a hazard ratio (HR) of 3.8 (95% confidence interval [CI] 2.4-5.8; P <.001) and adjusted HR of 2.3 (95% CI 1.4-3.8; P <.01). In diabetic patients with left ventricular ejection fraction >35%, the incidence of SCD was nearly identical to that of nondiabetic patients with ventricular ejection fraction ≤35% (4.1% vs 4.9%; P = .48). An excess in the incidence of non-SCD began to appear among diabetic patients within the first 6 months of follow-up (P <.001) but not in the incidence of SCD (P = .09). The excess in SCD among diabetic patients began to appear more than 6 months after the index event. CONCLUSION Patients with type 2 diabetes are at higher risk for SCD after MI than are nondiabetic patients. The incidence of SCD in post-MI type 2 diabetic patients with left ventricular ejection fraction >35% is equal to that of nondiabetic patients with left ventricular ejection fraction <35%.

Recovery Pattern of Baroreflex Sensitivity after Exercise

PURPOSE To test the association between exercise mode and the recovery pattern of baroreflex sensitivity (BRS) after exercise. METHODS The study population included healthy male subjects (N = 12, age: 31 +/- 3 yr). Four different interventions were performed in a randomized order: 1) aerobic exercise session on a bicycle ergometer, 2) light resistance exercise session, 3) heavy resistance exercise session, and 4) control intervention with no exercise. All interventions lasted 40 min. R-R intervals and continuous blood pressure were measured before (10 min) and 30-180 min after the interventions. BRSLF was calculated by the transfer function method from the low-frequency band (LF, 0.04-0.15 Hz) of the R-R intervals and systolic blood pressure spectra. RESULTS BRSLF had blunted until 30 min after aerobic and light resistance exercise (11.1 +/- 4.3 and 10.0 +/- 3.6 vs 17.5 +/- 7.0 ms.mm Hg(-1), P = 0.002 for both, compared with the control intervention, respectively). However, BRSLF was significantly blunted until 60 min after heavy resistance exercise (9.3 +/- 2.3 vs 15.1 +/- 4.7 ms.mm Hg(-1), P = 0.005, compared with the control intervention). The high-frequency power of R-R intervals (0.15-0.4 Hz) was significantly reduced, and the LF power of systolic blood pressure oscillation was significantly augmented 30 min after heavy resistance exercise (P < 0.01 for both), whereas both indices were restored to the control level by 30 min after aerobic and light resistance exercise. CONCLUSION BRS after acute exercise is associated with exercise intensity, showing relatively rapid recovery after aerobic and light resistance exercise and delayed recovery after heavy resistance exercise. The delayed BRS pattern after heavy resistance exercise is regulated by delicate interplay between the withdrawal of vagal outflow and the probably increased sympathetic vasomotor tone documented by measurements of heart rate and blood pressure variability.

Novel spectral indexes of heart rate variability as predictors of sudden and non-sudden cardiac death after an acute myocardial infarction

Background. Various indexes of 24‐hour heart rate variability (HRV) have been able to predict all‐cause mortality after an acute myocardial infarction (AMI), but their value in predicting specific modes of cardiac death has been limited. Aim. The aim of this study was to assess the role of two novel spectral indexes of HRV as predictors of either sudden (SCD) or non‐sudden cardiac death after an AMI. Method. We used two novel methods of spectral analysis of HRV: 1) the high‐frequency (HF) spectral component, Vindex, calculated as an average HF power from the most linear portion of HF power versus the R‐R interval regression curve, and 2) the prevalent low‐frequency oscillation of heart rate (PLF). Vindex, conventional HRV measures, and PLF were analyzed from 24‐hour Holter recordings of 590 patients with a recent AMI. Results. During the mean follow‐up of 39±14 months, SCD occurred in 3% (n = 17) and non‐sudden cardiac death in 5% (n = 28) of the patients. In univariate analysis, Vindex was the most potent predictor of SCD (RR: 6.0, 95% CI: 1.7–20.7, P<0.01), also remaining the most powerful predictor of SCD after adjustment for clinical variables and ejection fraction (RR: 4.2, 95% CI: 1.2–15.2, P<0.05). PLF was a potent predictor of non‐sudden cardiac death (RR: 13.9, 95% CI: 5.9–32.5, P<0.001), but it did not predict SCD. Conclusions. Novel spectral HRV analysis methods, Vindex and PLF, provide significant information of the risk of the specific mode of death after an AMI.

Physical activity and heart rate variability measured simultaneously during waking hours

Heart rate (HR) variability (HRV) during ambulatory recordings may be affected by individual differences in daily physical activity (PA). However, the influence of various levels of PA on different measures of HRV is not exactly known. We examined the association between simultaneously measured HRV and objective PA data obtained with an accelerometer during waking hours among 45 healthy adults. Bouts of PA were identified from minute-by-minute accelerometer data as metabolic equivalent (METs) values and calculated as mean METs for 30 min. HRV was analyzed concurrently. Within-individual correlation analyses and sign tests were performed to study the relationships between various HRV indexes and PA. The mean PA time was 15:44 +/- 1:01 h, and the mean MET was 1.91 +/- 0.14. HR and sample entropy, but not the other measures of HRV, had a significant relationship with PA, as shown by both correlation analyses (r = 0.64, P = 0.021, and r = -0.55, P = 0.022, respectively) and sign tests (P < 0.0001 for both). Beat-to-beat R-R interval fluctuation expressed as SD1 also demonstrated a significant relation to PA according to the sign test (P = 0.037) and a trend of association according to the correlation analysis (r = -0.40, P = 0.129). The complexity measure of HRV, in addition to average HR and the short-term index of HRV (SD1), is significantly influenced by the level of PA during ambulatory conditions. Long-term HRV indexes remained relatively stable at various activity levels, making them the most robust indexes for the assessment of cardiac autonomic function during free-running ambulatory conditions.

Heart rate variability and the metabolic syndrome: a systematic review of the literature

A number of cross‐sectional studies have examined associations between heart rate variability and metabolic syndrome, but differences in study populations, data collection and analysis methodologies make synthesis difficult. The purpose of this study was to systematically review published primary research examining associations between heart rate variability and metabolic syndrome or its individual risk factors.

Sympatho‐vagal interaction in the recovery phase of exercise

Reciprocal autonomic regulation occurs during incremental exercise. We hypothesized that sympatho‐vagal interplay may become altered after exercise because of the differences in recovery patterns of autonomic arms. The cardiac vagal activity was assessed by measurement of beat‐to‐beat R–R interval oscillations using a Poincaré plot method (SD1), and muscle sympathetic nervous activity (MSNA) was measured from peroneus nerve by a microneurography technique during and after exercise in 16 healthy subjects. Autonomic regulation was compared between the rest and after exercise (3·5 ± 1·0 min after exercise) at equal heart rates (HR). SD1 was at the equal level at the recovery phase (40 ± 21 ms) compared to the resting condition (38 ± 16 ms, P = ns) at comparable HR (57 ± 10 for both). MSNA was higher at the recovery phase (40 ± 19 burst per 100 heartbeats) than at rest (25 ± 13 burst per 100 heartbeats, P<0·0001). The difference of MSNA activity between rest and late recovery phase had a strong positive correlation with the difference in SD1 (r = 0·78, P<0·001) at equal HRs. Subjects who have a higher sympathetic activity in the recovery phase of exercise have a more augmented cardiac vagal activity resulting in an accentuated sympatho‐vagal outflow. The altered autonomic interaction observed here may partly explain the clustering of various cardiovascular events to the recovery phase of exercise.

Cardiac autonomic function and high-intensity interval training in middle-age men.

PURPOSE The effects of short-term high-intensity interval training (HIT) on cardiac autonomic function are unclear. The present study assessed cardiac autonomic adaptations to short-term HIT in comparison with aerobic endurance training (AET). METHODS Twenty-six healthy middle-age sedentary men were randomized into HIT (n = 13, 4-6 × 30 s of all-out cycling efforts with 4-min recovery) and AET (n = 13, 40-60 min at 60% of peak workload) groups, performing six sessions within 2 wk. The participants underwent a 24-h ECG recording before and after the intervention and, additionally, recorded R-R interval data in supine position (5 min) at home every morning during the intervention. Mean HR and low-frequency (LF) and high-frequency (HF) power of R-R interval oscillation were analyzed from these recordings. RESULTS Peak oxygen consumption (V˙O2peak) increased in both groups (P < 0.001). Compared with AET (n = 11), HIT (n = 13) increased 24-h LF power (P = 0.024), tended to increase 24-h HF power (P = 0.068), and increased daytime HF power (P = 0.038). In home-based measurements, supine HF power decreased on the days after HIT (P = 0.006, n = 12) but not AET (P = 0.80, n = 9) session. The acute response of HF power to HIT session did not change during the intervention. CONCLUSIONS In conclusion, HIT was more effective short-term strategy to increase R-R interval variability than aerobic training, most probably by inducing larger increases in cardiac vagal activity. The acute autonomic responses to the single HIT session were not modified by short-term training.