Validation of an early vascular aging construct model for comprehensive cardiovascular risk assessment using external risk indicators for improved clinical utility: data from the EVasCu study.

BACKGROUND: Cardiovascular diseases (CVDs) remain a major global health concern, necessitating advanced risk assessment beyond traditional factors. Early vascular aging (EVA), characterized by accelerated vascular changes, has gained importance in cardiovascular risk assessment. METHODS: The EVasCu study in Spain examined 390 healthy participants using noninvasive measurements. A construct of four variables (Pulse Pressure, Pulse Wave Velocity, Glycated Hemoglobin, Advanced Glycation End Products) was used for clustering. K-means clustering with principal component analysis revealed two clusters, healthy vascular aging (HVA) and early vascular aging (EVA). External validation variables included sociodemographic, adiposity, glycemic, inflammatory, lipid profile, vascular, and blood pressure factors. RESULTS: EVA cluster participants were older and exhibited higher adiposity, poorer glycemic control, dyslipidemia, altered vascular properties, and higher blood pressure. Significant differences were observed for age, smoking status, body mass index, waist circumference, fat percentage, glucose, insulin, C-reactive protein, diabetes prevalence, lipid profiles, arterial stiffness, and blood pressure levels. These findings demonstrate the association between traditional cardiovascular risk factors and EVA. CONCLUSIONS: This study validates a clustering model for EVA and highlights its association with established risk factors. EVA assessment can be integrated into clinical practice, allowing early intervention and personalized cardiovascular risk management.

Arterial stiffness assessment using PPG feature extraction and significance testing in an in vitro cardiovascular system.

Cardiovascular diseases (CVDs) remain the leading cause of global mortality, therefore understanding arterial stiffness is essential to developing innovative technologies to detect, monitor and treat them. The ubiquitous spread of photoplethysmography (PPG), a completely non-invasive blood-volume sensing technology suitable for all ages, highlights immense potential for arterial stiffness assessment in the wider healthcare setting outside specialist clinics, for example during routine visits to a General Practitioner or even at home with the use of mobile and wearable health devices. This study employs a custom-manufactured in vitro cardiovascular system with vessels of varying stiffness to test the hypothesis that PPG signals may be used to detect and assess the level of arterial stiffness under controlled conditions. Analysis of various morphological features demonstrated significant (p < 0.05) correlations with vessel stiffness. Particularly, area related features were closely linked to stiffness in red PPG signals, while for infrared PPG signals the most correlated features were related to pulse-width. This study demonstrates the utility of custom vessels and in vitro investigations to work towards non-invasive cardiovascular assessment using PPG, a valuable tool with applications in clinical healthcare, wearable health devices and beyond.

Assessment of aortic and peripheral arterial stiffness in patients with knee osteoarthritis by ultrasound Doppler derived pulse wave velocity.

Information regarding regional arterial stiffness assessment in osteoarthritis (OA) was scarce and sometimes contradictory. We aimed to investigate the aortic, lower limb peripheral arterial stiffness and their associations with knee OA. Patients with primary knee OA and matched non-OA controls were prospectively enrolled from two medical centers in China. The carotid-femoral pulse wave velocity (cfPWV) and femoral-ankle pulse wave velocity (faPWV) were measured using a novel ultrasound technique. A total of 238 participants (including 128 patients with knee OA and 110 controls) were included. In OA patients, cfPWV was significantly higher than that of non-OA controls (9.40 ± 1.92 vs 8.25 ± 1.26 m/s, P < 0.0001). However, faPWV measurements in OA patients (12.10 ± 2.09 m/s) showed no significant difference compared with that of the controls (11.67 ± 2.52 m/s, P = 0.130). Multiple regression analysis revealed that cfPWV was independently associated with knee OA (P < 0.0001) after adjusting for the confounding factors including age, gender, smoking, mean blood pressure, body mass index, heart rate, high-sensitivity C-reactive protein and lipids profiles. In contrast, faPWV did not show independent association with knee OA (P = 0.372) when after adjusting for confounding factors. In addition, Spearman's correlation analysis showed cfPWV had a significant correlation with Kellgren-Lawrence score (rs = 0.2333, P = 0.008), but no correlation was founded between faPWV with Kellgren-Lawrence score (rs = 0.1624, P = 0.067) in OA patients. This study demonstrated that stiffening of aorta, but not lower limb arteries, was independently associated with knee OA. Our findings may call for further implementation of routine aortic stiffness assessments so as to evaluate cardiovascular risk in patients with OA.

Model-Based Assessment of the Reference Values of CAVI in Healthy Russian Population and Benchmarking With CAVI0.

BACKGROUND: Cardio-ankle vascular index (CAVI) and its modified version (CAVI0) are promising non-invasive markers of arterial stiffness, extensively evaluated primarily in the Japanese population. In this work, we performed a model-based analysis of the association between different population characteristics and CAVI or CAVI0 values in healthy Russian subjects and propose a tool for calculating the range of reference values for both types of indices. METHODS: The analysis was based on the data from 742 healthy volunteers (mean age 30.4 years; 73.45% men) collected from a multicenter observational study. Basic statistical analysis [analysis of variance, Pearson's correlation (r), significance tests] and multivariable linear regression were performed in R software (version 4.0.2). Tested covariates included age, sex, BMI, blood pressure, and heart rate (HR). RESULTS: No statistically significant difference between healthy men and women were observed for CAVI and CAVI0. In contrast, both indices were positively associated with age (r = 0.49 and r = 0.43, P < 0.001), however, with no clear distinction between subjects of 20-30 and 30-40 years old. Heart rate and blood pressure were also identified as statistically significant predictors following multiple linear regression modeling, but with marginal clinical significance. Finally, the algorithm for the calculation of the expected ranges of CAVI in healthy population was proposed, for a given age category, HR and pulse pressure (PP) values. CONCLUSIONS: We have evaluated the quantitative association between various population characteristics, CAVI, and CAVI0 values and established a method for estimating the subject-level reference CAVI and CAVI0 measurements.

Photoplethysmography for the Assessment of Arterial Stiffness.

This review outlines the latest methods and innovations for assessing arterial stiffness, along with their respective advantages and disadvantages. Furthermore, we present compelling evidence indicating a recent growth in research focused on assessing arterial stiffness using photoplethysmography (PPG) and propose PPG as a potential tool for assessing vascular ageing in the future. Blood vessels deteriorate with age, losing elasticity and forming deposits. This raises the likelihood of developing cardiovascular disease (CVD), widely reported as the global leading cause of death. The ageing process induces structural modifications in the vascular system, such as increased arterial stiffness, which can cause various volumetric, mechanical, and haemodynamic alterations. Numerous techniques have been investigated to assess arterial stiffness, some of which are currently used in commercial medical devices and some, such as PPG, of which still remain in the research space.

Assessment of aortic to peripheral vascular stiffness and gradient by segmented upper limb PWV in healthy and hypertensive individuals.

Theoretically pulse wave velocity (PWV) is obtained by calculating the distance between two waveform probes divided by the time difference, and PWV ratio is used to assess the arterial stiffness gradient (SG) from proximal to distal. The aim was to investigate segmental upper-limb PWV (ulPWV) differences and the effects of hypertension and or aging on each ulPWV and SG. The study collected multi-waveform signals and conduction distances from 167 healthy individuals and 92 hypertensive patients. The results showed significant differences between ulPWVs (P < 0.001), with increased and then decreased vascular stiffness along the proximal transmission to the distal peripheral artery and then to the finger. Adjusted for age and sex, ulPWVs in hypertension exceeded that of healthy individuals, with significant differences between groups aged ≥ 50 years (P < 0.05). The hrPWV/rfPWV (heart-radial/radial-finger) was reduced in hypertension and differed significantly between the aged ≥ 50 years (P = 0.015); the ratio of baPWV (brachial-ankle) to ulPWV differed significantly between groups (P < 0.05). Hypertension affected the consistency of rfPWV with hfPWV (heart-finger). The findings suggest that segmented ulPWV is instrumental in providing stiffness corresponding to the physiological structure of the vessel. The superimposition of hypertension and or aging exacerbates peripheral arterial stiffness, as well as alteration in stiffness gradient.

[Clinical value of arterial stiffness assessment on risk prediction of vascular stiffness in the octogenarian elderly].

Objective: This study aimed to analyze clinical factors related to arterial stiffening and establish a risk prediction nomogram of arterial stiffening in the octogenarian(≥80 years). Methods: This study was a retrospective cross-sectional study, which enrolled the octogenarian elderly who underwent physical examination and secondary prevention intervention in the outpatient department of Chinese People's Liberation Army General Hospital from April 2022 to August 2022. Clinical data including demographics, biochemical indicators and medical history were collected. Brachial-ankle pulse wave velocity (baPWV) was detected during the clinical visit. Participants were divided into the control group (baPWV≤1 800 cm/s) and vascular sclerosis group (baPWV>1 800 cm/s). The risk factors of arterial stiffness were analyzed by univariate and logistic regression analysis, and the nomogram model was constructed by R programming language. The predictive effect of the nomogram model was evaluated by the receiver operating characteristic curve (ROC). Results: The median age of the 525 participants was 87.0 (82.0, 92.0) years, 504 (96.0%) were male, 82 in the control group, 443 in the vascular sclerosis group. The baPWV, age, systolic blood pressure, mean arterial pressure and diastolic blood pressure were significantly lower in the control group than those in the vascular sclerosis group (all P<0.05). Logistic regression analysis showed that high-density lipoprotein cholesterol, alanine aminotransferase and amylase were protective factors, and alkaline phosphatase and creatinine were risk factors of arterial stiffening (all P<0.05). The combined nomogram model scores including age, mean arterial pressure and the above five laboratory indicators indicated that mean arterial pressure and serum creatinine levels were strongly correlated with vascular sclerosis. The ROC curve suggested that the nomogram model had good prediction ability. Conclusions: Age, mean arterial pressure, high-density lipoprotein cholesterol, alanine aminotransferase, alkaline phosphatase, amylase and creatinine are independently determinants for increased vascular stiffness. The combined prediction model in this study can provide reference for individualized clinical risk prediction of vascular sclerosis in the octogenarian elderly.

Noninvasive hemodynamic indices of vascular aging: an in silico assessment.

Vascular aging (VA) involves structural and functional changes in blood vessels that contribute to cardiovascular disease. Several noninvasive pulse wave (PW) indices have been proposed to assess the arterial stiffness component of VA in the clinic and daily life. This study investigated 19 of these indices, identified in recent review articles on VA, by using a database comprising 3,837 virtual healthy subjects aged 25-75 yr, each with unique PW signals simulated under various levels of artificial noise to mimic real measurement errors. For each subject, VA indices were calculated from filtered PW signals and compared with the precise theoretical value of aortic Young's modulus (EAo). In silico PW indices showed age-related changes that align with in vivo population studies. The cardio-ankle vascular index (CAVI) and all pulse wave velocity (PWV) indices showed strong linear correlations with EAo (Pearson's rp > 0.95). Carotid distensibility showed a strong negative nonlinear correlation (Spearman's rs < -0.99). CAVI and distensibility exhibited greater resilience to noise compared with PWV indices. Blood pressure-related indices and photoplethysmography (PPG)-based indices showed weaker correlations with EAo (rp and rs < 0.89, |rp| and |rs| < 0.84, respectively). Overall, blood pressure-related indices were confounded by more cardiovascular properties (heart rate, stroke volume, duration of systole, large artery diameter, and/or peripheral vascular resistance) compared with other studied indices, and PPG-based indices were most affected by noise. In conclusion, carotid-femoral PWV, CAVI and carotid distensibility emerged as the superior clinical VA indicators, with a strong EAo correlation and noise resilience. PPG-based indices showed potential for daily VA monitoring under minimized noise disturbances.NEW & NOTEWORTHY For the first time, 19 noninvasive pulse wave indices for assessing vascular aging were examined together in a single database of nearly 4,000 subjects aged 25-75 yr. The dataset contained precise values of the aortic Young's modulus and other hemodynamic measures for each subject, which enabled us to test each index's ability to measure changes in aortic stiffness while accounting for confounding factors and measurement errors. The study provides freely available tools for analyzing these and additional indices.

Arterial stiffness and biological parameters: A decision tree machine learning application in hypertensive participants.

Arterial stiffness, measured by arterial stiffness index (ASI), could be considered a main denominator in target organ damage among hypertensive subjects. Currently, no reported ASI normal references have been reported. The index of arterial stiffness is evaluated by calculation of a stiffness index. Predicted ASI can be estimated regardless to age, sex, mean blood pressure, and heart rate, to compose an individual stiffness index [(measured ASI-predicted ASI)/predicted ASI]. A stiffness index greater than zero defines arterial stiffness. Thus, the purpose of this study was 1) to determine determinants of stiffness index 2) to perform threshold values to discriminate stiffness index and then 3) to determine hierarchical associations of the determinants by performing a decision tree model among hypertensive participants without CV diseases. A study was conducted from 53,363 healthy participants in the UK Biobank survey to determine predicted ASI. Stiffness index was applied on 49,452 hypertensives without CV diseases to discriminate determinants of positive stiffness index (N = 22,453) from negative index (N = 26,999). The input variables for the models were clinical and biological parameters. The independent classifiers were ranked from the most sensitives: HDL cholesterol≤1.425 mmol/L, smoking pack years≥9.2pack-years, Phosphate≥1.172 mmol/L, to the most specifics: Cystatin c≤0.901 mg/L, Triglycerides≥1.487 mmol/L, Urate≥291.9 µmol/L, ALT≥22.13 U/L, AST≤32.5 U/L, Albumin≤45.92 g/L, Testosterone≥5.181 nmol/L. A decision tree model was performed to determine rules to highlight the different hierarchization and interactions between these classifiers with a higher performance than multiple logistic regression (p<0.001). The stiffness index could be an integrator of CV risk factors and participate in future CV risk management evaluations for preventive strategies. Decision trees can provide accurate and useful classification for clinicians.

Assessment of Hydration, Nutritional Status and Arterial Stiffness in Hypertensive Chronic Kidney Disease Patients.

The aim of this cross-sectional study was to determine the body fluid volume in patients diagnosed with both chronic kidney disease (CKD) and arterial hypertension (AH), and to investigate the relationship between fluid overload (FO), nutritional status and arterial stiffness in this specific patient population. A total of 169 participants with CKD and AH were enrolled in the study, and data on general parameters, comorbidities, medication use, and laboratory parameters were collected. Body composition was assessed with a Tanita MC 780 device, and data on the central and peripheral systolic and diastolic blood pressure, as well as pulse wave velocity (PWV) and the augmentation index (AIx) were collected with an IEM Mobil-O-Graph 24 h ambulatory blood pressure monitor, which was based on oscillometry. The Mediterranean Diet Serving Score (MDSS) questionnaire was used to determine the adherence to the Mediterranean diet (MeDi). Our results showed that the significant positive predictors of hydration status were the use of diuretics and oral hypoglycemic agents, whereas the negative predictors were female sex, higher body mass index level and use of two or more antihypertensives in the form of a single-pill combination. We also found differences in blood pressure and arterial stiffness parameters in relation to volume status, along with differences based on the presence of diabetes mellitus (DM). In conclusion, these results call for a higher awareness of volume status in the care of CKD patients with AH, especially in those with diabetes mellitus.

Relationship between the Central and Regional Pulse Wave Velocity in the Assessment of Arterial Stiffness Depending on Gender in the Geriatric Population.

Artery stiffness is a risk factor for cardiovascular disease (CVD). The measurement of pulse wave velocity (PWV) between the carotid artery and the femoral artery (cfPWV) is considered the gold standard in the assessment of arterial stiffness. A relationship between cfPWV and regional PWV has not been established. The aim of this study was to evaluate the influence of gender on arterial stiffness measured centrally and regionally in the geriatric population. The central PWV was assessed by a SphygmoCor XCEL, and the regional PWV was assessed by a new device through the photoplethysmographic measurement of multi-site arterial pulse wave velocity (MPPT). The study group included 118 patients (35 males and 83 females; mean age 77.2 ± 8.1 years). Men were characterized by statistically significantly higher values of cfPWV than women (cfPWV 10.52 m/s vs. 9.36 m/s; p = 0.001). In the measurement of regional PWV values using MPPT, no such relationship was found. Gender groups did not statistically differ in the distribution of atherosclerosis risk factors. cfPWV appears to be more accurate than regional PWV in assessing arterial stiffness in the geriatric population.

Predictive value of estimated pulse wave velocity with all-cause and cause-specific mortality in the hypertensive population: the National Health and Nutrition Examination Surveys 1999-2014.

BACKGROUND: Estimated pulse wave velocity (ePWV) has been proposed as a potential approach to assess carotid-femoral pulse wave velocity (cfPWV). However, the potential ability of ePWV to predict all-cause and cause-specific mortality in the population group with hypertension remains unresolved. METHODS: We conducted a prospective cohort study using the data of 14 044 adults (age ≥18 years) from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014, and followed this cohort until the end of December 2019. ePWV was calculated by using a regression equation for age and mean blood pressure (MBP), derived by the Arterial Stiffness Collaborative Group. RESULTS: The weighted mean age of the 14 044 adults included was 54.79 years; 49.42% of all participants were men. During the median follow-up period of 11 years, 3795 deaths were recorded. In the fully adjusted cox regression model, each 1 m/s increase in ePWV was associated with an increased risk of 56% [hazard ratio 1.61; 95% confidence interval (CI) 1.49-1.64] risk for all-cause mortality. Every 1 m/s increase in ePWV resulted in an increased risk of mortality from cardiovascular disease, cerebrovascular disease, respiratory disease, Alzheimer's disease, accidents, cancer, influenza and pneumonia by 60, 70, 47, 118, 73, 41 and 103%, respectively. ePWV has a robust predictive value for 5- and 10-year all-cause mortality in the hypertensive population with AUCs of 0.749 and 0.741, respectively. CONCLUSION: Elevated ePWV is positively correlated with all-cause mortality and most cause-specific mortalities, independent of traditional risk factors. Moreover, ePWV demonstrates high accuracy in predicting 5-year and 10-year all-cause mortality, outperforming Framingham Risk Score.

[Impact of individual and combined assessment of age- and sex-specific brachial-ankle pulse wave velocity and pulse pressure on all-cause mortality].

Objective: To evaluate the impact of individual and combined assessment of age- and sex-specific brachial-ankle pulse wave velocity (baPWV) and pulse pressure (PP) on all-cause mortality. Methods: This study is a prospective cohort study. Individuals participated in the Kailuan Study and completed baPWV measurements between 2010 and 2016 were included in this study. After stratifying by sex, 75th percentile baPWV and PP values for different age group were calculated at five years interval. BaPWV and PP values below the 75th percentile were defined as normal, and those above or equal to the 75th percentile were defined as increased. The participants were allocated to four groups according to their PP and baPWV status: normal baPWV/PP group, high baPWV/normal PP group, normal baPWV/high PP group and high baPWV/PP group. The primary outcome was all-cause mortality during the follow-up period. Cox proportional hazards models were used to explore the impact of individual and combined assessment of baPWV and PP on all-cause mortality events. Results: A total of 39 339 participants were enrolled in this study, aged (49.3±12.8) years, of which 28 731 (73.03%) were males. There were 23 268, 6 025, 6 210 and 3 836 cases in the normal baPWV/PP group, high baPWV/normal PP group, normal baPWV/high PP group and high baPWV/PP group, respectively. The average follow-up duration was (4.98±2.53) years. During the follow-up period, all-cause mortality occurred in 998 individuals. Multivariate Cox regression analysis showed increased risk of all-cause mortality in the high baPWV/normal PP group (HR=1.27, 95%CI 1.07-1.50), and in the high baPWV/PP group (HR=1.33, 95%CI 1.08-1.65) compared to the normal baPWV/PP group. Increased pulse pressure alone had no impcat on all-cause death (HR=1.06, 95%CI 0.87-1.29). Conclusions: The risk of all-cause mortality significantly increases with increased age-and sex-specific baPWV and PP values. BaPWV may be a better predictor of all-cause mortality than PP in this cohort.

Fully automatic carotid arterial stiffness assessment from ultrasound videos based on machine learning.

Arterial stiffness (AS) refers to the loss of arterial compliance and alterations in vessel wall properties. The study of local carotid stiffness (CS) is particularly important since carotid artery stiffening raises the risk of stroke, cognitive impairment, and dementia. So, stiffness measurement as a screening tool approach is crucial because it can reduce mortality and facilitate therapy planning. This study aims to evaluate the stiffness of the CCA using machine learning (ML) through the features of diameter change (ΔD) and stiffness parameters. This study was conducted in seven stages: data collection, preprocessing, CCA segmentation, CCA lumen diameter (DCCA) computing during cardiac cycles, denoising signals of DCCA, computational of AS parameters, and stiffness assessment using ML. The 51 videos (with 25 s) of CCA B-mode ultrasound (US) were used and analyzed. Each US video yielded approximately 750 sequential frames spanning about 24 cardiac cycles. Firstly, US preset settings with time gain compensation with a U-pattern were employed to enhance CCA segmentations. The study showed that auto region-growing, employed three times, is appropriate for segmenting walls with a short running time (4.56 s/frame). The diameter computed for frames constructs a signal (diameter signal) with noisy parts in the shape of peak variance and an un-smooth side. Among the 12 employed smoothing methods, spline fitting with a mean peak difference per cycle (MPDCY) of 0.58 pixels was the most effective for the diameter signal. The authors propose the MPDCY as a new selection criterion for smoothing methods with highly preserved peaks. The ΔD (Dsys-Ddia) determined in this study was validated by statistical analysis as a viable replacement for manual ΔD measurement. Statistical analysis was carried out by Mann-Whitney t-test with a p-value of 0.81, regression line R2 = 0.907, and there was no difference in means between the two groups for box plots. The stiffness parameters of the carotid arteries were calculated based on auto-ΔD and pulse pressure. Five ML models, including K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), logistic regression (LR), and random forest (RF), fed by distension (ΔD) and five stiffness parameters, were used to distinguish between the stiffened and un-stiffened CCA. Except for SVM, all models performed excellently in terms of specificity, sensitivity, precision, and area under the curve (AUC). In addition, the scatterplot and statistical analysis of the fed features confirm these remarkable outcomes. The scatter plot demonstrates that a linear hyperline can easily distinguish between the two classes. The statistical analysis shows that the stiffness parameters computed from the database of this work were statistically (p < 0.05) distributed into the non-stiffness and stiffness groups. The presented models are validated by applying them to additional datasets. Applying models to other datasets reveals a model performance of 100%. The proposed ML models could be applied in clinical practice to detect CS early, which is essential for preventing stroke.

Neighborhood characteristics and arterial stiffness among Black adults - Results from the Jackson Heart Study and Morehouse-Emory Cardiovascular Center for Health Equity.

INTRODUCTION: Poor quality neighborhood environments are independent risk factors for cardiovascular disease (CVD) but are understudied in Black adults, who face large CVD health disparities. Arterial stiffness, a marker of early vascular aging, precedes development of hypertension and adverse CVD events but the effect of neighborhood on arterial stiffness among Black adults remains unknown. OBJECTIVE: We compared the association between neighborhood environment and arterial stiffness among Black adults in Jackson, MS and Atlanta, GA. METHODS: We studied 1582 Black adults (mean age 53 ± 10, 35% male) living in Jackson, MS from the Jackson Heart Study (JHS) and 451 Black adults (mean age 53 ± 10, 39% male) living in Atlanta, GA from the Morehouse-Emory Cardiovascular Center for Health Equity (MECA) study, without known CVD. Neighborhood problems (includes measures of aesthetic quality, walking environment, food access), social cohesion (includes activity with neighbors), and violence/safety were assessed using validated questionnaires. Arterial stiffness was measured as pulse wave velocity (PWV) using magnetic resonance imaging in JHS and as PWV and augmentation index (AIx) using applanation tonometry (SphygmoCor, Inc.) in MECA. Multivariable linear regression models were used to examine the association between neighborhood characteristics and arterial stiffness, adjusting for potential confounders. RESULTS: Improved social characteristics, measured as social cohesion in JHS (ß = -0.32 [-0.63, -0.02], p = 0.04) and activity with neighbors (ß = -0.23 [-0.40, -0.05], p = 0.01) in MECA, were associated with lower PWV in both cohorts and lower AIx (ß = -1.74 [-2.92, - 0.56], p = 0.004) in MECA, after adjustment for CVD risk factors and income. Additionally, in MECA, better food access (ß = -1.18 [-2.35, - 0.01], p = 0.05) was associated with lower AIx and, in JHS, lower neighborhood problems (ß = -0.33 [-0.64, - 0.02], p = 0.04) and lower violence (ß = -0.30 [-0.61, 0.002], p = 0.05) were associated with lower PWV. CONCLUSION: Neighborhood social characteristics show an independent association with the vascular health of Black adults, findings that were reproducible in two distinct American cities.

An XGBoost-based model for assessment of aortic stiffness from wrist photoplethysmogram.

BACKGROUND AND OBJECTIVE: Carotid-femoral pulse wave velocity (cf-PWV) is the gold standard for non-invasive assessment of aortic stiffness. Photoplethysmography used in wearable devices provides an indirect measurement method for cf-PWV. This study aimed to construct a cf-PWV prediction method based on the XGBoost algorithm and wrist photoplethysmogram (wPPG) for the early screening of arteriosclerosis in primary healthcare. METHODS: Data from 210 subjects were used for modeling, and 100 subjects were used as an external validation set. The wPPG pulse waves were filtered by discrete wavelet transform, and various features were extracted from each waveform, including two original indexes. The extraction rate (ER) and Pearson P were calculated to evaluate the applicability of each feature for model training. The magnitude of cf-PWV was predicted by an XGBoost-based model using the selected features and basic physiological parameters (age, sex, height, weight and BMI). The level of aortic stiffness was classified by a 3-classification strategy according to the standard cf-PWV (measured by the Complior device). Bland-Altman plot, Pearson correlation analysis, and accuracy tested performance from two aspects: predicting the magnitude of cf-PWV and classifying the level of aortic stiffness. RESULTS: In the external validation set (n = 100, age range 22-79), 97 subjects obtained features (ER = 97%). The predicted cf-PWV was significantly correlated with the standard cf-PWV (r = 0.927, P < 0.001). The accuracy (AC) of the 3-classification was 85.6%. The interrater agreement for assessing aortic stiffness was at least substantial (quadratically weighted Kappa = 0.833). CONCLUSIONS: The multi-parameter fusion cf-PWV prediction method based on the XGBoost algorithm and wPPG pulse wave analysis proves the feasibility of atherosclerosis screening in wearable devices.

Risk assessment indicators and brachial-ankle pulse wave velocity to predict atherosclerotic cardiovascular disease.

Brachial-ankle pulse wave velocity (baPWV) is used for predicting the severity of vascular damage and prognosis of atherosclerotic cardiovascular disease (ASCVD) in people with hypertension and diabetes mellitus. This correlation study aimed to compare the baPWV with other risk indicators for identification of subclinical vascular disease for primary prevention and to determine the clinical utility of baPWV-guided therapy in improving prognosis in high-risk subjects. We included 4881 subjects who underwent voluntary health examination at Mackay Memorial Hospital, Taiwan between 2014 and 2019. Participants were categorized into the low-risk (<5%), borderline-risk (5%-7.4%), intermediate-risk (7.5%-19.9%), and high-risk (≥20%) groups based on the 10-year risk for ASCVD. The predictive risk criteria, that is, the metabolic syndrome score, Framingham Risk Score, estimated glomerular filtration rate, and baPWV were compared among these groups. The chief cause of induced responses and the relationships between parameters were identified using principal component analysis. The participants' ages, body mass index, systolic, diastolic blood pressure, triglycerides, fasting glucose, hemoglobin A1c, creatinine, neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, metabolic syndrome, Framingham Risk Score, and age-related arterial stiffness (vascular age) increased significantly from the low-risk to high-risk groups (P < .001). The mean estimated glomerular filtration rate decreased significantly from the low- to high-risk groups (P < .001). The predicted vascular age and actual age differed significantly between the intermediate- and high-risk groups (P < .001). High-density lipoprotein levels plummeted significantly among the 4 groups (P < .001). The right and left baPWV and ankle brachial index differed significantly among the 4 groups (all P < .001) and increased from the low-risk to high-risk groups (P < .001). Carotid Doppler ultrasonography revealed a significant increase in plaque formation (23.5%, 35.4%, 46.3%, and 61.5% for the low-, borderline-, intermediate, and high-risk groups, respectively). The total explanatory variation was 61.9% for 2 principal variation factors (baPWV, 36.8% and creatinine, 25.1%). The vascular age predicted using baPWV greatly exceeded the chronological age. Plaque formation was significant even in the low-risk group, and its frequency increased with the predicted ASCVD risk. Risk indicators and baPWV are useful predictors of ASCVD, which in conjunction with conventional pharmacotherapy could be useful for primary prevention of plaque formation in subjects with cardiovascular comorbidities.

Measurement of Serum N-Glycans in the Assessment of Early Vascular Aging (Arterial Stiffness) in Adults With Type 1 Diabetes.

OBJECTIVE: Vascular aging (arterial stiffness [AS]) is an inflammation-linked process that predicts macro- and microvascular complications in adults with type 1 diabetes (T1D). We evaluated the utility of measuring the inflammation-linked N-glycans GlycA and GlycB to assess vascular aging in adults with T1D. RESEARCH DESIGN AND METHODS: Eighty-four adults with T1D (>10-year duration without cardiovascular events) and 68 healthy control subjects were evaluated for clinical characteristics (including microvascular complications in patients with T1D), aortic pulse wave velocity (aPWV) (surrogate measure of AS), and serum GlycA and GlycB (peak area [concentration] and height/width [H/W] ratio) using 1H-nuclear magnetic resonance spectroscopy. RESULTS: Patients with T1D had higher median (interquartile range) values than healthy control subjects for (P < 0.001 for all comparisons) aPWV 7.9 (6.9-9.1) vs. 6.1 (5.5-6.7) m/s, GlycA 850.4 (781.3-916.1) vs. 652.4 (581.5-727.1) µmoL; GlycB 386.1 (353.2-426.3) vs. 310.0 (280.5-331.9) µmol/L), H/W ratio of GlycA 16.5 (14.9-18.1) vs. 15.0 (13.7-16.7), and H/W ratio of GlycB 5.0 (4.6-5.5) vs. 4.0 (3.4-4.3). Moreover, aPWV correlated (P < 0.001 for all correlations) with GlycA (r = 0.550) and GlycB (r = 0.423) concentrations and with H/W ratios of GlycA (r = 0.453) and GlycB (r = 0.510). Adjusting for potential confounders, GlycA concentration (ß = 0.212, P < 0.001) and the H/W ratios of GlycA (ß = 0.150, P = 0.009) and GlycB (ß = 0.155, P = 0.011) remained independently associated with aPWV. C-statistics for detecting individuals with aPWV >10 m/s were 0.866 (95% CI 0.794-0.937) for GlycA levels and 0.862 (0.780-0.943) for H/W ratio of GlycB. CONCLUSIONS: Measurement of serum GlycA and GlycB may have utility in assessing vascular aging in adults with T1D of >10-year duration and no previous cardiovascular events.

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.