Dataset Information

Impact of Pulse Wave Velocity and Parameters Reflecting Android Type Fat Distribution on Left Ventricular Diastolic Dysfunction in Patients with Chronic Coronary Syndromes.

ABSTRACT: Left ventricular diastolic dysfunction (LVDD) is caused by a decreased left ventricle relaxation and is associated with an increased risk of symptomatic heart failure (HF) and excessive mortality. To evaluate the frequency and factors related to LVDD in the population with chronic coronary syndromes (CCS). 200 patients (mean age 63.18 ± 8.12 years, 75.5% male) with CCS were included. LVDD was diagnosed based on the recent echocardiography guidelines. LVDD was diagnosed in 38.5% of CCS population. From the studied factors, after adjustment for age, sex, and N-terminal pro-brain natriuretic peptide (NT-proBNP), LVDD associated positively with android/gynoid (A/G) fat mass ratio, left ventricular mass index (LVMI), and negatively with Z-score and left ventricular ejection fraction (LVEF). In stepwise backward logistic regression analysis, the strongest factors associated with LVDD were pulse wave velocity value, handgrip strength and waist to hip ratio (WHR). LVDD is common among CCS patients and it is associated with parameters reflecting android type fat distribution regardless of NT-proBNP and high-sensitivity troponin T concentrations. Deterioration in diastolic dysfunction is linked with increased aortic stiffness independently of age and sex. Further studies evaluating the effects of increasing physical fitness and lowering abdominal fat accumulations on LVDD in CCS patients should be considered.

SUBMITTER: Paniczko M

PROVIDER: S-EPMC7761650 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Impact of Pulse Wave Velocity and Parameters Reflecting Android Type Fat Distribution on Left Ventricular Diastolic Dysfunction in Patients with Chronic Coronary Syndromes.

Paniczko Marlena M Chlabicz Małgorzata M Jamiołkowski Jacek J Sowa Paweł P Szpakowicz Małgorzata M Łapińska Magda M Kondraciuk Marcin M Ptaszyńska-Kopczyńska Katarzyna K Raczkowski Andrzej A Szpakowicz Anna A Kamiński Karol Adam KA

Journal of clinical medicine 20201203 12

<h4>Background</h4>Left ventricular diastolic dysfunction (LVDD) is caused by a decreased left ventricle relaxation and is associated with an increased risk of symptomatic heart failure (HF) and excessive mortality.<h4>Aim</h4>To evaluate the frequency and factors related to LVDD in the population with chronic coronary syndromes (CCS).<h4>Methods</h4>200 patients (mean age 63.18 ± 8.12 years, 75.5% male) with CCS were included. LVDD was diagnosed based on the recent echocardiography guidelines.< ...[more]

PMID: 33287316

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Project description:BackgroundAortic stiffness shares a similar profile of risk factors with left ventricular hypertrophy (LVH) and can also lead to LVH by itself. Published data have demonstrated the correlation between aortic stiffness and LVH. Recent data have revealed estimated pulse wave velocity (ePWV) to be a simple and cost-effective marker of the severity of aortic stiffness. Our analysis aimed to explore the association between ePWV and LVH prevalence, and to investigate the incremental value of ePWV for the identification of LVH prevalence.MethodsThe present analysis based on a cross-sectional survey which included 11,597 participants from rural areas of southeastern China between Sep 2020 and Feb 2021. ePWV was formulated based on mean blood pressure and age according to a published algorithm.ResultsThe prevalence of LVH was 14.56%. With the adjustment of age, sex, education, income and physical activity level, current drinking and smoking status, BMI, waist circumference, serum creatinine, total cholesterol, high density cholesterol, mean blood pressure, fasting plasma glucose, anti-hypertensive therapy, anti-diabetic therapy, lipid-lowering therapy, and cardiovascular disease history, every standard deviation increment of ePWV associated with a 2.993 times risk of LVH prevalence. When dividing ePWV into quartiles, the top quartile had a 4.520 times risk of LVH prevalence when compared with the bottom quartile. Furthermore, smooth spline analysis displayed that the association was linear in the whole range of ePWV (p for non-linearity = 0.073). Additionally, subgroup analysis revealed the association was robust to sex, obesity and diabetes, and younger people and hypertensive population were more vulnerable to the increase of ePWV than their corresponding counterparts. Finally, ROC analysis showed a significant advancement when introducing ePWV into established risk factors (0.787 vs. 0.810, p for comparison < 0.001), and reclassification analysis also confirmed significant improvement from ePWV to identify LVH prevalence (category-free net reclassification analysis = 0.421, p < 0.001; integrated discrimination index = 0.023, p < 0.001).ConclusionOur analysis demonstrated a linear association between ePWV and LVH prevalence. Furthermore, our results suggest younger people and hypertensive population are more likely to have LVH prevalence with the increase of ePWV. More importantly, our findings implicate the incremental value of ePWV to optimize the identification of LVH prevalence in a general Chinese population.

Project description:Background:Obesity is an important risk factor of cardiovascular disease (CVD). Atherosclerosis can be considered an important signal of CVD. Primary physicians can reduce the risk of CVD by preventing and treating obesity. Therefore, finding a tool to diagnose the association of obesity with arteriosclerosis is important. The association between obesity parameters and arterial stiffness remains controversial. To our knowledge, no previous studies reported the relationships between multiple new anthropometric parameters (a body shape index [ABSI], body round index [BRI], and visceral adiposity index [VAI]) and brachial-ankle wave velocity (ba-PWV) as an indicator of CVD risk, especially in the Korean population. Objective:To investigate the relationships between arterial stiffness (assessed using ba-PWV) and anthropometric parameters estimated on the basis of body mass index (BMI), waist circumference (WC), ABSI, BRI, and VAI, and to identify the indicators of obesity that best represents CVD risk. Methods:A total of 2,647 adults (1,474 men and 1,173 women) were recruited for this cross-sectional study. The correlations between the anthropometric indexes (BMI, WC, ABSI, BRI, and VAI) and mean ba-PWV were analyzed. A multivariate linear regression analysis was performed to evaluate the association between each anthropometric and the presence of arterial stiffness. Results:We investigated the relationships between the obesity parameters and ba-PWV by adjusting the covariates (age, diabetes mellitus [DM], hypertension [HTN], and smoking status) related to the mean ba-PWV. In the multivariate regression analysis, ABSI (men: ? =0.066, p<0.01; women: ? =0.087, p<0.001) and VAI (men: ? =0.067, p<0.01; women: ? =0.136, p<0.001) were found to be significantly correlated with the mean ba-PWV in both men and women in Korea. Conclusion:Among the new obesity indices, ABSI and VAI were found to be significantly associated with arterial stiffness, represented by the mean ba-PWV, in both men and women in Korea. These results suggest that ABSI and VAI may be convenient, highly cost-effective, and simple assessment tools for obesity and CVD risk in clinical practice.

Project description:BackgroundPhase space is a mechanical systems approach and large-scale data representation of an object in 3-dimensional space. Whether such techniques can be applied to predict left ventricular pressures non-invasively and at the point-of-care is unknown.ObjectiveThis study prospectively validated a phase space machine-learned approach based on a novel electro-mechanical pulse wave method of data collection through orthogonal voltage gradient (OVG) and photoplethysmography (PPG) for the prediction of elevated left ventricular end diastolic pressure (LVEDP).MethodsConsecutive outpatients across 15 US-based healthcare centers with symptoms suggestive of coronary artery disease were enrolled at the time of elective cardiac catheterization and underwent OVG and PPG data acquisition immediately prior to angiography with signals paired with LVEDP (IDENTIFY; NCT #03864081). The primary objective was to validate a ML algorithm for prediction of elevated LVEDP using a definition of ≥25 mmHg (study cohort) and normal LVEDP ≤ 12 mmHg (control cohort), using AUC as the measure of diagnostic accuracy. Secondary objectives included performance of the ML predictor in a propensity matched cohort (age and gender) and performance for an elevated LVEDP across a spectrum of comparative LVEDP (<12 through 24 at 1 mmHg increments). Features were extracted from the OVG and PPG datasets and were analyzed using machine-learning approaches.ResultsThe study cohort consisted of 684 subjects stratified into three LVEDP categories, ≤12 mmHg (N = 258), LVEDP 13-24 mmHg (N = 347), and LVEDP ≥25 mmHg (N = 79). Testing of the ML predictor demonstrated an AUC of 0.81 (95% CI 0.76-0.86) for the prediction of an elevated LVEDP with a sensitivity of 82% and specificity of 68%, respectively. Among a propensity matched cohort (N = 79) the ML predictor demonstrated a similar result AUC 0.79 (95% CI: 0.72-0.8). Using a constant definition of elevated LVEDP and varying the lower threshold across LVEDP the ML predictor demonstrated and AUC ranging from 0.79-0.82.ConclusionThe phase space ML analysis provides a robust prediction for an elevated LVEDP at the point-of-care. These data suggest a potential role for an OVG and PPG derived electro-mechanical pulse wave strategy to determine if LVEDP is elevated in patients with symptoms suggestive of cardiac disease.

Dataset Information

Impact of Pulse Wave Velocity and Parameters Reflecting Android Type Fat Distribution on Left Ventricular Diastolic Dysfunction in Patients with Chronic Coronary Syndromes.

Publications

Impact of Pulse Wave Velocity and Parameters Reflecting Android Type Fat Distribution on Left Ventricular Diastolic Dysfunction in Patients with Chronic Coronary Syndromes.

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