Effect of Aquatic Exercise Training on Aortic Hemodynamics in Middle-Aged and Elderly Adults

Aquatic exercise is an attractive form of exercise that utilizes the various properties of water to improve physical health, including arterial stiffness. However, it is unclear whether regular head-out aquatic exercise affects aortic hemodynamics, the emerging risk factors for future cardiovascular disease. The purpose of this study was to investigate whether head-out aquatic exercise training improves aortic hemodynamics in middle-aged and elderly people. In addition, to shed light on the underlying mechanisms, we determined the contribution of change in arterial stiffness to the hypothesized changes in aortic hemodynamics. Twenty-three middle-aged and elderly subjects (62 ± 9 years) underwent a weekly aquatic exercise course for 15 weeks. Aortic hemodynamics were evaluated by pulse wave analysis via the general transfer function method. Using a polar coordinate description, companion metrics of aortic pulse pressure (PPC = √{(systolic blood pressure)2 + (diastolic blood pressure)2}) and augmentation index (AIxC = √{(augmentation pressure)2 + (pulse pressure)2}) were calculated as measures of arterial load. Brachial-ankle (baPWV, reflecting stiffness of the abdominal aorta and leg artery) and heart-ankle (haPWV, reflecting stiffness of the whole aortic and leg artery) pulse wave velocities were also measured. The rate of participation in the aquatic training program was 83.5 ± 13.0%. Aortic systolic blood pressure, pulse pressure, PPC, AIxC, baPWV, and haPWV decreased after the training (P < 0.05 for all), whereas augmentation index remained unchanged. Changes in aortic SBP were correlated with changes in haPWV (r = 0.613, P = 0.002) but not baPWV (r = 0.296, P = 0.170). These findings suggest that head-out aquatic exercise training may improve aortic hemodynamics in middle-aged and elderly people, with the particular benefits for reducing aortic SBP which is associated with proximal aortic stiffness.

Arterial stiffness and valvular calcifications in aortic stenosis: caught between a rock and a hard place

Background/Introduction Arterial stiffness and aortic hemodynamics are independent predictors of adverse cardiovascular events. Indications for transcatheter aortic valve implantation (TAVI) are expanding and aortic valve calcifications (AVC) are an important prognostic factor of the success of TAVI. Purpose We sought to investigate the associations between AVC and aortic vascular function/hemodynamics. Methods Fifty-two high-risk patients (mean age 80.4±8.5 years, 27 male) with severe symptomatic aortic stenosis undergoing TAVI were included. Arterial stiffness was estimated through carotid-femoral pulse wave velocity (cfPWV) and brachial-ankle pulse wave velocity (baPWV). Aortic hemodynamics (aortic pressures, aortic augmentation index corrected for heart rate [AIx@75]) were also measured. Measurements were conducted prior to the implantation and at discharge. In all patients, a native and contrast-enhanced multislice cardiac computed tomography were performed pre-interventionally. AVC were then graded semi-quantitatively as follows: grade 1 – no calcification; grade 2 – mildly calcified (small isolated spots); grade 3 – moderately calcified (multiple larger spots); grade 4 – severely calcified (extensive calcification of all cusps). Results Group 1 (subjects with none/mild AVC, n=29) did not significantly differ in age, gender and body-mass index compared to group 2 (subjects with moderate/severe AVC, n=23). As far as the traditional cardiovascular risk factors were concerned, only hypertension (p=0.008), coronary artery disease (p=0.016), atrial fibrillation (p=0.075) and insulin-dependent diabetes mellitus (p=0.068) were found to be more prevalent in group 2. Group 2 had significantly higher both cfPWV and baPWV (8.3±1.7 vs 7.2±1.2 m/s and 1750±484 cm/s vs. 2101±590 cm/s with p=0.008 and p=0.022 respectively) compared to Group 1 (Figure 1). Even after adjustment for age, gender and systolic blood pressure, aortic stiffness indices were higher in Group 2 compared to Group 1 (p=0.038 and p=0.048, respectively). There was no statistically significant difference in peripheral or aortic pressures as well as in wave reflections indices between the two groups. Conclusion Our study shows that in patients with aortic valve stenosis there is a correlation between increased aortic stiffness and a greater extent of damage of aortic valvular leaflets as well as calcifications. FUNDunding Acknowledgement Type of funding sources: None. Figure 1. PWV and aortic valve calcifications

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning

Cardiac and aortic characteristics are crucial for cardiovascular disease detection. However, noninvasive estimation of aortic hemodynamics and cardiac contractility is still challenging. This paper investigated the potential of estimating aortic systolic pressure (aSBP), cardiac output (CO), and end-systolic elastance (Ees) from cuff-pressure and pulse wave velocity (PWV) using regression analysis. The importance of incorporating ejection fraction (EF) as additional input for estimating Ees was also assessed. The models, including Random Forest, Support Vector Regressor, Ridge, Gradient Boosting, were trained/validated using synthetic data (n = 4,018) from an in-silico model. When cuff-pressure and PWV were used as inputs, the normalized-RMSEs/correlations for aSBP, CO, and Ees (best-performing models) were 3.36 ± 0.74%/0.99, 7.60 ± 0.68%/0.96, and 16.96 ± 0.64%/0.37, respectively. Using EF as additional input for estimating Ees significantly improved the predictions (7.00 ± 0.78%/0.92). Results showed that the use of noninvasive pressure measurements allows estimating aSBP and CO with acceptable accuracy. In contrast, Ees cannot be predicted from pressure signals alone. Addition of the EF information greatly improves the estimated Ees. Accuracy of the model-derived aSBP compared to in-vivo aSBP (n = 783) was very satisfactory (5.26 ± 2.30%/0.97). Future in-vivo evaluation of CO and Ees estimations remains to be conducted. This novel methodology has potential to improve the noninvasive monitoring of aortic hemodynamics and cardiac contractility.