Additive Effects of Heating and Exercise on Baroreflex Control of Heart Rate in Healthy Males

This study assessed the additive effects of passive heating and exercise on cardiac baroreflex sensitivity (cBRS) and heart rate variability (HRV). Twelve healthy young men (25±1 yrs, 23.8±0.5 kg/m229 ) randomly underwent two experimental sessions: heat stress (HS; whole-body heat stress using a tube-lined suit to increase core temperature by ~1°C) and normothermia (NT). Each session was composed of a: pre-intervention rest (REST1); HS or NT interventions; post-intervention rest (REST2); and 14 min of cycling exercise [7 min at 40%HRreserve (EX1) and 7 min at 60%HRreserve (EX2)]. Heart rate and finger blood pressure were continuously recorded. cBRS was assessed using the sequence (cBRSSEQ) and transfer function (cBRSTF) methods. HRV was assessed using the indices SDNN (standard deviation of RR intervals) and RMSSD (root mean square of successive RR intervals). cBRS and HRV were not different between sessions during EX1 and EX2 (i.e. matched heart rate conditions: EX1=116±3 vs. 114±3, EX2=143±4 vs. 142±3 bpm; but different workloads: EX1=50±9 vs. 114±8, EX2=106±10 vs. 165±8 Watts; for HS and NT, respectively; P<0.01). However, when comparing EX1 of NT with EX2 of HS (i.e. matched workload conditions, but with different heart rates), cBRS and HRV were significantly reduced in HS (cBRSSEQ = 1.6±0.3 vs. 0.6±0.1 ms/mmHg, P<0.01; SDNN = 2.3±0.1 vs. 1.3±0.2 ms, P<0.01). In conclusion, in conditions matched by HR, the addition of heat stress to exercise does not affect cBRS and HRV. Alternatively, in workload-matched conditions, the addition of heat to exercise results in reduced cBRS and HRV compared to exercise in normothermia

Predictors of walking capacity in peripheral arterial disease patients

OBJECTIVE: To estimate walking capacity in intermittent claudication patients through a prediction model based on clinical characteristics and the walking impairment questionnaire. METHODS: The sample included 133 intermittent claudication patients of both genders aged between 30 and 80 years. Data regarding clinical characteristics, the walking impairment questionnaire and treadmill walking test performance were obtained. Multiple regression modeling was conducted to predict claudication onset distance and total walking distance using clinical characteristics (age, height, mass, body mass index, ankle brachial index lower, gender, history of smoking and co-morbid conditions) and walking impairment questionnaire responses. Comparisons of claudication onset distance and total walking distance measured during treadmill tests and estimated by a regression equation were performed using paired t-tests. RESULTS: Co-morbid conditions (diabetes and coronary artery disease) and questions related to difficulty in walking short distances (walking indoors - such as around your house and walking 5 blocks) and at low speed (walking 1 block at average speed - usual pace) resulted in the development of new prediction models high significant for claudication onset distance and total walking distance (p0.05) were observed. CONCLUSION: The current study demonstrated that walking capacity can be adequately estimated based on co-morbid conditions and responses to the walking impairment questionnaire

Cardiovascular Responses During Resistance Exercise in Patients with Parkinson Disease

Background: Patients with Parkinson disease (PD) present cardiovascular autonomic dysfunction which impairs blood pressure control. However, cardiovascular responses during resistance exercise are unknown in these patients. Objective: Investigate the cardiovascular responses during resistance exercise performed with different muscle masses, in patients with PD. Design: Two groups, repeated-measures design. Setting: Exercise Hemodynamic Laboratory, School of Physical Education and Sport, University of São Paulo. Participants: Thirteen patients with PD (4 women, 62.7±1.3 years, stages 2-3 of modified Hoehn and Yahr scale; "on" state of medication) and thirteen paired controls without PD (7 women, 66.2±2.0years) Interventions: Both groups performed, in a random order, bilateral and unilateral knee extension exercises (2 sets, 10–12 RM, 2 min of interval). Main Outcome Measurements: Systolic blood pressure (SBP) and heart rate (HR) were assessed before (pre) and during the exercises. Results: Independent of set and exercise type, SBP and HR increases were significantly lower in PD than the control group (combined values: +45±2 vs. +73±4 mmHg and +18±1 vs. +31±2 bpm, P =.003 and .007, respectively). Independently of group and set, the SBP increase was greater in the bilateral than the unilateral exercise (combined values: +63±4 vs +54±3 mmHg, P=.002), while the HR increase was similar. In addition, independently of group and exercise type, the SBP increase was higher in the 2nd than the 1st set (combined values: +56±4 vs +61±4 mmHg, P=.04), while the HR increases were similar. Conclusions: Patients with PD present attenuated 25 increases in SBP and HR during resistance exercise in comparison with healthy subjects. These results support that resistance exercise is safe and well tolerated for patients with PD from a cardiovascular point of view supporting its recommendation for this population

Effects of post-exercise cooling on heart rate recovery in normotensive and hypertensive men

Background: Post-exercise heart rate recovery (HRR) is determined by cardiac autonomic restoration after exercise and is reduced in hypertension. Post-exercise cooling accelerates HRR in healthy subjects, but its effects in a population with cardiac autonomic dysfunction, such as hypertensives (HT), may be blunted. This study assessed and compared the effects of post-exercise cooling on HRR and cardiac autonomic regulation in HT and normotensive (NT) subjects. Methods: Twenty-three never-treated HT (43±8 ys) and 25 NT (45±8 ys) men randomly underwent two exercise sessions (30 min of cycling at 70%VO2peak) followed by 15 min of recovery. In one randomly allocated session, a fan was turned on in front of the subject during the recovery (cooling), while in the other session, no cooling was performed (control). HRR was assessed by heart rate reductions after 60 (HRR60s) and 300s (HRR300s) of recovery, short-term time constant of HRR (T30), and the time constant of the HRR after exponential fitting (HRRτ). HRV was assessed using time- and frequency-domain indices. Results: HRR and HRV responses in the cooling and control sessions were similar between the HT and NT. Thus, in both groups, post-exercise cooling equally accelerated HRR (HRR300s = 39±12 vs. 36±10 bpm, p≤0.05) and increased post44 exercise HRV (lnRMSSD = 1.8±0.7 vs. 1.6±0.7 ms, p≤0.05). Conclusion: Differently from the hypothesis, post-exercise cooling produced similar improvements in HRR in HT and NT men, likely by an acceleration of cardiac parasympathetic reactivation and sympathetic withdrawal. These results suggest that post-exercise cooling equally accelerates HRR in hypertensive and normotensive subjects

Arterial pressure changes monitoring with a new precordial noninvasive sensor

<p>Abstract</p> <p>Background</p> <p>Recently, a cutaneous force-frequency relation recording system based on first heart sound amplitude vibrations has been validated. A further application is the assessment of Second Heart Sound (S2) amplitude variations at increasing heart rates. The aim of this study was to assess the relationship between second heart sound amplitude variations at increasing heart rates and hemodynamic changes.</p> <p>Methods</p> <p>The transcutaneous force sensor was positioned in the precordial region in 146 consecutive patients referred for exercise (n = 99), dipyridamole (n = 41), or pacing stress (n = 6). The curve of S2 peak amplitude variation as a function of heart rate was computed as the increment with respect to the resting value.</p> <p>Results</p> <p>A consistent S2 signal was obtained in all patients. Baseline S2 was 7.2 ± 3.3 m<it>g</it>, increasing to 12.7 ± 7.7 m<it>g </it>at peak stress. S2 percentage increase was + 133 ± 104% in the 99 exercise, + 2 ± 22% in the 41 dipyridamole, and + 31 ± 27% in the 6 pacing patients (p < 0.05). Significant determinants of S2 amplitude were blood pressure, heart rate, and cardiac index with best correlation (R = .57) for mean pressure.</p> <p>Conclusion</p> <p>S2 recording quantitatively documents systemic pressure changes.</p