Mikko P. Tulppo

Vagal modulation of heart rate during exercise: effects of age and physical fitness

This study was designed to assess the effects of age and physical fitness on vagal modulation of heart rate (HR) during exercise by analyzing the instantaneous R-R interval variability from Poincaré plots (SD1) at rest and at different phases of a bicycle exercise test in a population of healthy males. SD1 normalized for the average R-R interval (SD1n), a measure of vagal activity, was compared at rest and during exercise among subjects of ages 24-34 (young, n = 25), 35-46 (middle-aged, n = 30), and 47-64 yr (old, n = 25) matched for peak O2 consumption (V˙o 2 peak) and among subjects withV˙o 2 peak of 28-37 (poor, n = 25), 38-45 (average, n = 36), and 46-60 ml ⋅ kg-1 ⋅ min-1(good, n = 25) matched for age. SD1n was higher at rest in the young subjects than in the middle-aged or old subjects (39 ± 14, 27 ± 16, and 21 ± 8, respectively; P < 0.001), but the age-related differences in SD1n were smaller during exercise [e.g., 11 ± 5, 9 ± 5, and 8 ± 4 at the level of 100 W; P = not significant (NS)]. The age-matched subjects with good, average, and poor V˙o 2 peakshowed no difference in SD1n at rest (32 ± 17, 28 ± 13, and 26 ± 11, respectively; P = NS), but SD1n differed significantly among the groups from a low to a moderate exercise intensity level (e.g., 13 ± 6, 10 ± 5, and 6 ± 3 for good, average, and poor fitness groups, respectively; P < 0.001, 100 W). These data show that poor physical fitness is associated with an impairment of cardiac vagal function during exercise, whereas aging itself results in more evident impairment of vagal function at rest.

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.

Heart rate dynamics before spontaneous onset of ventricular fibrillation in patients with healed myocardial infarcts

The traditional methods of analyzing heart rate (HR) variability have failed to predict imminent ventricular fibrillation (VF). We sought to determine whether new methods of analyzing RR interval variability based on nonlinear dynamics and fractal analysis may help to detect subtle abnormalities in RR interval behavior before the onset of life-threatening arrhythmias. RR interval dynamics were analyzed from 24-hour Holter recordings of 15 patients who experienced VF during electrocardiographic recording. Thirty patients without spontaneous or inducible arrhythmia events served as a control group in this retrospective case control study. Conventional time- and frequency-domain measurements, the short-term fractal scaling exponent (alpha) obtained by detrended fluctuation analysis, and the slope (beta) of the power-law regression line (log power - log frequency, 10(-4)-10(-2) Hz) of RR interval dynamics were determined. The short-term correlation exponent alpha of RR intervals (0.64 +/- 0.19 vs 1.05 +/- 0.12; p <0.001) and the power-law slope beta (-1.63 +/- 0.28 vs -1.31 +/- 0.20, p <0.001) were lower in the patients before the onset of VF than in the control patients, but the SD and the low-frequency spectral components of RR intervals did not differ between the groups. The short-term scaling exponent performed better than any other measurement of HR variability in differentiating between the patients with VF and controls. Altered fractal correlation properties of HR behavior precede the spontaneous onset of VF. Dynamic analysis methods of analyzing RR intervals may help to identify abnormalities in HR behavior before VF.

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.

Abnormalities in beat to beat complexity of heart rate dynamics in patients with a previous myocardial infarction.

OBJECTIVES The purpose of this research was to study possible abnormalities in the beat to beat complexity of heart rate dynamics in patients with a previous myocardial infarction. BACKGROUND Analysis of approximate entropy of time series data provides information on the complexity of both deterministic and random processes. It has been proposed that regularity or loss of complexity of RR interval dynamics may be related to pathologic states, but this hypothesis has not been well tested in cardiovascular disorders. METHODS Approximate entropy and conventional time and frequency domain measures of RR interval variability were compared between 40 healthy subjects with no evidence of heart disease and 40 patients with coronary artery disease and a previous Q wave myocardial infarction. The groups were matched with respect to age, and cardiac medication was discontinued in the patients with coronary artery disease before the 24-h electrocardiographic recordings. RESULTS Approximate entropy was significantly higher in the postinfarction patients (1.21 +/- 0.18 [mean +/- SD]) than in the healthy subjects (1.05 +/- 0.11, p < 0.001), whereas the standard deviation of RR intervals (63 +/- 19 vs. 86 +/- 23 ms, p < 0.001) and the very low, low and high frequency spectral components were lower (p < 0.01, p < 0.001, p < 0.05, respectively). Approximate entropy was not related to the time domain or the spectral components of heart rate variability and was more commonly abnormal in postinfarction patients (62.5%) than any linear measure (from 20% to 42.5%) when the 90% percentile of the values obtained for healthy subjects was defined as the normal range for each measure. CONCLUSIONS Despite reduced linear measures of heart rate variability, the unpredictability or randomness of beat to beat heart rate dynamics is increased in patients with a previous myocardial infarction. Complexity analysis of RR interval dynamics may provide useful information on abnormalities in heart rate behavior that are not easily detected by the commonly used moment statistics.

Heart rate dynamics during accentuated sympathovagal interaction

Concomitant sympathetic and vagal activation can occur in various physiological conditions, but there is limited information on heart rate (HR) behavior during the accentuated sympathovagal antagonism. Beat-to-beat HR and blood pressure were recorded during intravenous infusion of incremental doses of norepinephrine in 18 healthy male volunteers (mean age 23 ± 5 yr). HR and blood pressure spectra and two-dimensional Poincaré plots were generated from the baseline recordings and from the recordings at different doses of norepinephrine. The mean blood pressure increased (from 90 ± 7 to 120 ± 9 mmHg, P < 0.001), HR decreased (from 60 ± 9 to 48 ± 7 beats/min, P < 0.001), and the high-frequency spectral component of HR variability increased ( P < 0.001) during the norepinephrine infusion as evidence of accentuated sympathovagal interaction. Abrupt aperiodic changes in sinus intervals that were not related to respiratory cycles or changes in blood pressure occurred in 14 of 18 subjects during the norepinephrine infusions. These fluctuations in sinus intervals resulted in a complex or parabola-shaped structure of the Poincaré plots of successive R-R intervals and a widening of the high-frequency spectral peak. In four subjects, the abrupt fluctuations in sinus intervals were followed by a sudden onset of fixed R-R interval dynamics with a loss of respiratory modulation of HR, resulting in a torpedo-shaped structure of the Poincaré plots. These data show that HR behavior becomes remarkably unstable during accentuated sympathovagal interaction, resembling stochastic dynamics or deterministic chaotic behavior. These features of HR dynamics can be better identified by dynamic analysis of beat-to-beat behavior of R-R intervals than by traditional analysis techniques of HR variability.

Coronary angioplasty in drug eluting stent era for the treatment of unprotected left main stenosis compared to coronary artery bypass grafting

Background. Improved outcomes of percutaneous coronary interventions (PCI) with drug-eluting stents (DES) have resulted in their expanded use for left main coronary artery (LMCA) stenosis. Aim. We compared outcomes of patients undergoing PCI for unprotected LMCA stenosis and patients treated by coronary artery bypass grafting (CABG). Method. Between January 2005 and January 2007, 6705 patients were studied with coronary angiography in northern Finland. All subjects treated with revascularization of LMCA stenosis (n=287) were included and followed up for a mean of 12±6 months. Results. From 287 patients, 238 underwent CABG, and 49 had PCI with DES. The incidence of 1-year mortality was 4% among the PCI-treated and 11% among CABG-treated patients (P=0.136). After the first month, mortality among PCI- or CABG-treated patients did not differ statistically significantly (2% versus 7%, P=0.133). The most significant independent predictor of mortality was reduced left ventricular systolic function (hazard ratio 14.9, 95% CI 5.5–40.0, P<0.001). Conclusions. PCI with DES for selected LMCA disease patients results in short- and midterm outcomes comparable to results of CABG in general. PCI is a viable therapeutic option in selected patients with LMCA stenosis.

Clinical Applicability of Heart Rate Variability Analysis by Methods Based on Nonlinear Dynamics

Analysis of heart rate (HR) variability has become an important widely used method for assessing cardiac autonomic regulation. Conventionally, HR variability has been analyzed with time and frequency domain methods. Analysis of HR dynamics by methods based on nonlinear systems theory has opened a novel approach for studying the abnormalities in HR behavior. Recent studies have shown that these measures, particularly scaling analysis methods of HR dynamics, are altered among various patients populations with cardiovascular diseases, and they provide prognostic information. Altered long-term scaling properties of HR dynamics and more random short-term HR fluctuation has been observed, e.g., among patients with previous myocardial infarction, and these alterations have been shown to be associated with increased mortality rate. A relatively large body of data indicate that altered scaling properties of R-R intervals are physiologically deleterious. These findings support the notion that some nonlinear methods, such as scaling and complexity measures, give clinically valuable information for risk stratification among various patient populations. This article provides a review of our current knowledge of the usefulness of dynamical measures of HR fluctuation.

Short-term correlation properties of R-R interval dynamics at different exercise intensity levels.

Methods based on non‐linear heart rate (HR) dynamics have been suggested to probe features in HR behaviour that are not easily detected by the traditional HR variability indices. This study tested the hypothesis that analysis of correlation properties of R–R intervals provides useful information on HR fluctuation during exercise. High‐ (HF) and low‐frequency (LF) spectral components and a short‐term scaling exponent (α1) of HR variability, were analysed for nine healthy subjects at rest, during incremental and steady‐state exercise, during atropine infusion and during incremental exercise after atropine administration. During the incremental exercise test α1 increased from rest to an intensity level of ∼40% of (from 1·07 ± 0·24 to 1·50 ± 0·25, P<0·001) and thereafter decreased linearly until the end of exercise (from 1·50 ± 0·25 to 0·38 ± 0·10, P<0·001). Atropine infusion increased the scaling exponent α1 value from 0·91 ± 0·23 to 1·37 ± 0·31 (P<0·001). During exercise after atropine infusion, a linear reduction was observed in the scaling exponent α1 from 1·37 ± 0·23 to 0·25 ± 0·08 (P<0·001). Analogous changes in α1 were seen during long‐term steady‐state exercise compared to incremental exercise. Conventional HR variability indices did not show any significant changes during exercise at high exercise intensity levels. α1 correlated with the LF/HF ratio at rest (r = 0·90, P<0·001), but the correlation was weaker after atropine (r = 0·71, P<0·05) and during exercise (e.g. r = 0·33, P = NS at the level of 40% of ). In conclusion, incremental exercise test until exhaustion results in bidirectional changes in correlation properties of R–R interval dynamics. These changes can be explained by the intensity of vagal and sympathetic input to the sinus node during the different intensity levels of exercise. Changes in α1 values can be detected also in high intensity levels, when the conventional measures of HR variability can not be applied.

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%.