Repeatability and reproducibility of pulse wave velocity in relation to hemodynamics and sodium excretion in stable patients with hypertension

Hemodynamic phenotypes in chronic kidney disease patients based on linear regression of blood pressure parameters

Classic and non-classic cardiovascular (CV) risk factors accumulate in chronic kidney disease (CKD), contributing to vascular remodeling and hemodynamic abnormalities. This study aimed to determine hemodynamic phenotypes based on linear regression of blood pressure (BP) parameters in stage G3-G4 CKD patients at very high CV risk. 24-h ambulatory BP monitoring (ABPM), carotid-femoral pulse wave velocity (PWV) and central BP were obtained from 52 patients (aged 60 ± 11 years, BMI 30 ± 6 kg/m2) with stage G3-G4 CKD (eGFR 44 ± 12 mL/min./1.73 m2). Linear BP regression coefficients were generated to determine hemodynamic phenotypes using ABPM data. Coexisting hypertension was present in 45 (86%) patients, out of whom 33 (73%) had BP controlled. 24-h mean systolic/diastolic BP was 128 ± 18/75 ± 12 mm Hg. Twenty-six patients demonstrated the harmonious (H) and 26 patients diastolic dysfunctional (D) hemodynamic phenotypes. eGFR was not significantly different between both phenotypes. Compared to phenotype H, patients with phenotype D were older (57 ± 11 vs. 63 ± 10 years, p = .04), had higher PWV (8.2 [7.3-10.3] vs. 9.7 [8.3-10.9] m/s, p = .02), ambulatory arterial stiffness index (AASI) (0.31 ± 0.1 vs. 0.40 ± 0.1, p = .02), systolic BP (128 [122-130] vs. 137 [130-150] mm Hg, p = .001) and systolic BP variability (BPV) (11.7 ± 2.3 vs. 15.7 ± 3.4 mm Hg, p < .0001). Our findings suggest that one in two patients with stage G3-G4 CKD demonstrates an unfavorable D hemodynamic phenotype based on a linear regression model, associated with higher PWV, AASI, systolic BP, and systolic BPV. Further studies are required to assess the clinical utility of hemodynamic phenotypes and whether the D phenotype may predict latent circulatory disorders and outcomes.

The effects of experimental, meteorological, and physiological factors on short-term repeated pulse wave velocity measurements, and measurement difficulties: A randomized crossover study with two devices

Background

Large longitudinal studies with repeated pulse wave velocity (PWV) measurements, a direct measure of arterial stiffness, are required to realize the full potential of arterial stiffness in clinical practice. To facilitate such studies it is important to increase the power of a study by reducing within-subject variability of PWV, and to ease the use of a PWV device in clinical settings by minimizing PWV measurement difficulties.

Methods

We systematically investigated experimental setting and meteorological conditions, as well as physiological factors and participant characteristics, to determine whether and to what extent they affected: between- and within-subjects variability of PWV recordings, and measurement difficulties of a particular device. We conducted a 2-week longitudinal block-randomized cross-over study with two blinded observers and two commonly used devices: applanation tonometry SphygmoCor CvMS and oscillometric Arteriograph to assess carotid-femoral (cfPWV) or aortic (PWVao) PWV, respectively. Our sample had uniform and wide-spread distribution of age, blood pressures, hypertensive status and BMI. Each participant (N = 35) was recorded 12 times over 3 visiting days, 7 days apart. On each day, recordings were made twice in the morning (7-10 a.m.) and afternoon (16-18 p.m.). Data were analyzed using multilevel mixed-effects models, separately for each device.

Results

In addition to age and mean arterial pressure (MAP) that strongly affected both cfPWV and PWVao, other significant factors appeared to indicate a measurement approach. cfPWV as a more direct measure of arterial stiffness was additionally affected by hypertension status, outdoor temperature, interaction of MAP with outdoor temperature and the order of visit, with MAP within-subject variability contributing on average 0.27 m/s to difference in repeated measurements at 5^°C and 0.004 m/s at 25^°C. PWVao measurements derived at a single brachial site were more dependent on age than cfPWV and also depended on personal characteristics such as height and sex, and heart rate; with within-subject MAP variability adding on average 0.23 m/s to the difference in repeated measures. We also found that female sex significantly increased, and recording in afternoon vs. morning significantly decreased measurement difficulties of both devices.

Conclusion

We identified factors affecting PWV recordings and measurement-difficulties and propose how to improve PWV measuring protocols.

Arterial Stiffness Assessment by Pulse Wave Velocity in Patients with Metabolic Syndrome and Its Components: Is It a Useful Tool in Clinical Practice?

Metabolic syndrome (MS) is not a single disease but a cluster of metabolic disorders associated with increased risk for development of diabetes mellitus and its complications. Currently, the definition of MS published in 2009 is widely used, but there are more versions of the diagnostic criteria, making it difficult to conduct scientific discourse in this area. Increased arterial stiffness (AS) can predict the development of cardiovascular disease both in the general population and in patients with MS. Pulse wave velocity (PWV), as a standard method to assess AS, may point out subclinical organ damage in patients with hypertension. The decrease in PWV level during antihypertensive therapy can identify a group of patients with better outcomes independently of their reduction in blood pressure. The adverse effect of metabolic disturbances on arterial function can be offset by an adequate program of exercises, which includes mainly aerobic physical training. Non-insulin-based insulin resistance index can predict AS due to a strong positive correlation with PWV. The purpose of this paper is to present the results of the review of the literature concerning the relationship between MS and its components, and AS assessed by PWV, including clinical usefulness of PWV measurement in patients with MS and its components.

Non-invasive Systemic Hemodynamic Index in Vascular Risk Stratification Tailored for Hypertensives

Vascular dysfunction is a key hallmark of hypertension and related cardiovascular outcomes. As a well-known hemodynamic disease, hypertension is characterized by abnormal ventricular-vascular interactions. Complementing non-invasive systemic hemodynamics in hypertensive vascular risk assessment is of promising significance. We aimed to investigate the effects of abnormal hemodynamic states other than elevated blood pressure on vascular damage and establish a united index of systemic hemodynamics for generalized vascular risk evaluation. Non-invasive systemic hemodynamics, assessed by impedance cardiography, was compared among blood pressure stages. Vascular function was evaluated by flow-mediated dilation (FMD) and brachial-ankle pulse wave velocity (baPWV). Systemic hemodynamics was obtained from a total of 88 enrollees with a mean (±SD) systolic blood pressure 140 (±17) mm Hg, and aged 17 to 91 years. Both stroke systemic vascular resistance index and left stroke work index exhibited a significant alteration among blood pressure stages (p < 0.001; p = 0.01, respectively), whereas heterogeneous hemodynamic and vascular function subsets existed within similar blood pressure. In addition, blood pressure categories failed to recognize between-group differences in endothelial dysfunction (p = 0.88) and arterial stiffness (p = 0.26). An increase in myocardial contractility and a parallel decrease in afterload was associated with the decline of vascular dysfunction. Systemic Hemodynamic Index (SHI), as a surrogate marker, demonstrated a significantly negative correlation with vascular damage index (VDI, r = −0.49, p < 0.001). These findings illustrate that systemic hemodynamics underlying hypertensives provides more vascular information. The SHI/VDI score may be a feasible tool for cardiovascular function assessment.

Leveraging the potential of machine learning for assessing vascular ageing: state-of-the-art and future research

Vascular ageing biomarkers have been found to be predictive of cardiovascular risk independently of classical risk factors, yet are not widely used in clinical practice. In this review, we present two basic approaches for using machine learning (ML) to assess vascular age: parameter estimation and risk classification. We then summarize their role in developing new techniques to assess vascular ageing quickly and accurately. We discuss the methods used to validate ML-based markers, the evidence for their clinical utility, and key directions for future research. The review is complemented by case studies of the use of ML in vascular age assessment which can be replicated using freely available data and code.