Heart Rate Dynamics after Exercise in Cardiac Patients with and without Type 2 Diabetes

Purpose: The incidence of cardiovascular events is higher in coronary artery disease patients with type 2 diabetes (CAD + T2D) than in CAD patients without T2D. There is increasing evidence that the recovery phase after exercise is a vulnerable phase for various cardiovascular events. We hypothesized that autonomic regulation differs in CAD patients with and without T2D during post-exercise condition. Methods: A symptom-limited maximal exercise test on a bicycle ergometer was performed for 68 CAD + T2D patients (age 61 ± 5 years, 78% males, ejection fraction (EF) 67 ± 8, 100% on β-blockade), and 64 CAD patients (age 62 ± 5 years, 80% males, EF 64 ± 8, 100% on β-blockade). Heart rate (HR) recovery after exercise was calculated as the slope of HR during the first 60 s after cessation of exercise (HRRslope). R–R intervals were measured before (5 min) and after exercise from 3 to 8 min, both in a supine position. R–R intervals were analyzed using time and frequency methods and a detrended fluctuation method (α1). Results: BMI was 30 ± 4 vs. 27 ± 3 kg m2 (p < 0.001); maximal exercise capacity, 6.5 ± 1.7 vs. 7.7 ± 1.9 METs (p < 0.001); maximal HR, 128 ± 19 vs. 132 ± 18 bpm (p = ns); and HRRslope, −0.53 ± 0.17 vs. −0.62 ± 0.15 beats/s (p = 0.004), for CAD patients with and without T2D, respectively. There was no differences between the groups in HRRslope after adjustment for METs, BMI, and medication (ANCOVA, p = 0.228 for T2D and, e.g., p = 0.030 for METs). CAD + T2D patients had a higher HR at rest than non-diabetic patients (57 ± 10 vs. 54 ± 6 bpm, p = 0.030), but no other differences were observed in HR dynamics at rest or in post-exercise condition. Conclusion: HR recovery is delayed in CAD + T2D patients, suggesting impairment of vagal activity and/or augmented sympathetic activity after exercise. Blunted HR recovery after exercise in diabetic patients compared with non-diabetic patients is more closely related to low exercise capacity and obesity than to T2D itself

Clinical Application of Heart Rate Variability after Acute Myocardial Infarction

AbstractHeart rate (HR) variability has been extensively studied in patients surviving an acute myocardial infarction (AMI). The majority of studies have shown that patients with reduced or abnormal HR variability/turbulence have an increased risk of mortality within few years after an AMI. Various measures of HR dynamics, such as time-domain, spectral, and non-linear measures of HR variability, as well as HR turbulence, have been used in risk stratification of post-AMI patients. The prognostic power of various measures, except of those reflecting rapid R-R interval oscillations, has been almost identical, albeit some non-linear HR variability measures, such as short-term fractal scaling exponent, and HR turbulence, have provided somewhat better prognostic information than the others. Abnormal HR variability predicts both sudden and non-sudden cardiac death after AMI. Because of remodeling of the arrhythmia substrate after AMI, early measurement of HR variability to identify those at high risk should likely be repeated later in order to assess the risk of fatal arrhythmia events. Future randomized trials using HR variability/turbulence as one of the pre-defined inclusion criteria will show whether routine measurement of HR variability/turbulence will become a routine clinical tool for risk stratification of post-AMI patients

Heart Rate Variability: Clinical Applications and Interaction between HRV and Heart Rate

Over the last decades, assessment of heart rate variability (HRV) has increased in various fields of research. HRV describes changes in heartbeat intervals, which are caused by autonomic neural regulation, i.e. by the interplay of the sympathetic and the parasympathetic nervous systems. The most frequent application of HRV is connected to cardiological issues, most importantly to the monitoring of post-myocardial infarction patients and the prediction of sudden cardiac death. Analysis of HRV is also frequently applied in relation to diabetes, renal failure, neurological and psychiatric conditions, sleep disorders, psychological phenomena such as stress, as well as drug and addiction research including alcohol and smoking. The widespread application of HRV measurements is based on the fact that they are noninvasive, easy to perform, and in general reproducible – if carried out under standardized conditions. However, the amount of parameters to be analysed is still rising. Well-established time domain and frequency domain parameters are discussed controversially when it comes to their physiological interpretation and their psychometric properties like reliability and validity, and the sensitivity to cardiovascular properties of the variety of parameters seems to be a topic for further research. Recently introduced parameters like pNNxx and new dynamic methods such as approximate entropy and detrended fluctuation analysis offer new potentials and warrant standardization. However, HRV is significantly associated with average heart rate (HR) and one can conclude that HRV actually provides information on two quantities, i.e. on HR and its variability. It is hard to determine which of these two plays a principal role in the clinical value of HRV. The association between HRV and HR is not only a physiological phenomenon but also a mathematical one which is due to non-linear (mathematical) relationship between RR interval and HR. If one normalizes HRV to its average RR interval, one may get ‘pure’ variability free from the mathematical bias. Recently, a new modification method of the association between HRV and HR has been developed which enables us to completely remove the HRV dependence on HR (even the physiological one), or conversely enhance this dependence. Such an approach allows us to explore the HR contribution to the clinical significance of HRV, i.e. whether HR or its variability plays a main role in the HRV clinical value. This Research Topic covers recent advances in the application of HRV, methodological issues, basic underlying mechanisms as well as all aspects of the interaction between HRV and HR

Peak exercise capacity prediction from a submaximal exercise test in coronary artery disease patients

The purpose of this study was to determine whether a rating of perceived exertion scale (RPE) obtained during submaximal exercise could be used to predict peak exercise capacity (METpeak) in coronary artery disease (CAD) patients. Angiographically documented CAD patients (n = 124, 87% on β blockade) completed a symptom-limited peak exercise test on a bicycle ergometer, reporting RPE values at every second load on a scale of 6 to 20. Regression analysis was used to develop equations for predicting METpeak. We found that submaximal METs at a workload of 60/75 W (for women and men, respectively) and the corresponding RPE (METs/RPE ratio) was the most powerful predictor of METpeak (r = 0.67, p &lt; 0.0001). The final model included the submaximal METs/RPE ratio, body mass index, sex, resting heart rate, smoking history, age, and use of a β blockade (r = 0.86, p &lt; 0.0001, SEE 0.98 METs). These data suggest that RPE at submaximal exercise intensity is related to METpeak in CAD patients. The model based on easily measured variables at rest and during warm-up exercise can reasonably predict absolute METpeak in patients with CAD

Causes of nonischemic sudden cardiac death in the current era

Previous data have shown that various nonischemic cardiac diseases account for about 20% of sudden cardiac deaths (SCDs) and that dilated and hypertrophic cardiomyopathy (CM) are major causes of nonischemic SCD. The purpose of this study was to define the prevalence and causes of SCD due to nonischemic CM in the current era given the substantial change in the diagnosis and treatment of cardiac diseases and in lifestyle patterns. A total of 2661 consecutive victims of SCD from among a population of approximately 470,000 inhabitants in the Province of Oulu, Northern Finland, were included in the study. The causes of deaths were determined from the uniformly required autopsies of SCD victims in Finland, plus available medical records and standardized questionnaires. Nonischemic cause of SCD was found in 579 victims (21.8% of all the SCDs). Mean age (± SD) was 55 (±12) years; 78% were males. After subgrouping the nonischemic SCDs into various categories, SCDs associated most closely with obesity (23.7%), followed by alcoholic CM (19.0%), hypertensive CM (15.5%), and fibrotic CM (13.6%). Fibrotic CM was the most common association with SCD in subjects younger than 40 years (28.3%), whereas alcoholic CM was the most common cause of death in subjects between 40 and 59 years of age (25.8%). CM related to obesity, fibrotic CM, and alcoholic CM are commonly associated with nonischemic SCD in the current era. The association of SCD with fibrotic CM is notably frequent among victims younger than 40 years

Acute post-exercise change in blood pressure and exercise training response in patients with coronary artery disease

We tested the hypothesis that acute post-exercise change in blood pressure (BP) may predict exercise training responses in BP in patients with coronary artery disease (CAD). Patients with CAD (n=116, age 62±5 years, 85 men) underwent BP assessments at rest and during 10-min recovery following a symptom-limited exercise test before and after the 6-month training intervention (one strength and 3-4 aerobic moderate-intensity exercises weekly). Post-exercise change in systolic BP (SBP) was calculated by subtracting resting SBP from lowest post-exercise SBP. The training-induced change in resting SBP was -2±13 mmHg (p=0.064), ranging from -42 to 35 mmHg. Larger post-exercise decrease in SBP and baseline resting SBP predicted a larger training-induced decrement in SBP (β=0.46 and β=-0.44, respectively, p<0.001 for both). Acute post-exercise decrease in SBP provided additive value to baseline resting SBP in the prediction of training-induced change in resting SBP (R squared from 0.20 to 0.26, p=0.002). After further adjustments for other potential confounders (sex, age, baseline body mass index, realized training load), post-exercise decrease in SBP still predicted the training response in resting SBP (β=0.26, p=0.015). Acute post-exercise change in SBP was associated with training-induced change in resting SBP in patients with CAD, providing significant predictive information beyond baseline resting SBP

Unobtrusive, Low-Cost Out-of-Hospital, and In-Hospital Measurement and Monitoring System

Continuous monitoring of vital signs can be a life-saving matter for different patient groups. The development is going toward more intelligent and unobtrusive systems to improve the usability of body-worn monitoring devices. Body-worn devices can be skin-conformable, patch-type monitoring systems that are comfortable to use even for prolonged periods of time. Herein, an intelligent and wearable, out-of-hospital, and in-hospital four-electrode electrocardiography (ECG) and respiration measurement and monitoring system is proposed. The system consists of a conformable screen-printed disposable patch, a measurement unit, gateway unit, and cloud-based analysis tools with reconfigurable signal processing pipelines. The performance of the ECG patch and the measurement unit was tested with cardiac patients and compared with a Holter monitoring device and discrete, single-site electrodes.publishedVersionPeer reviewe