The relationship between arterial stiffness index and coronary heart disease and its severity

Association of baseline and dynamic arterial stiffness status with dyslipidemia: a cohort study

Background and aims

Dyslipidemia is known to contribute to arterial stiffness, while the inverse association remains unknown. This study aimed to explore the association of baseline arterial stiffness and its changes, as determined by brachial-ankle pulse wave velocity (baPWV), with dyslipidemia onset in the general population.

Methods

This study enrolled participants from Beijing Health Management Cohort using measurements of the first visit from 2012 to 2013 as baseline, and followed until the dyslipidemia onset or the end of 2019. Unadjusted and adjusted Cox proportional regression models were used to evaluate the associations of baseline baPWV and baPWV transition (persistent low, onset, remitted and persistent high) with incident dyslipidemia.

Results

Of 4362 individuals (mean age: 55.5 years), 1490 (34.2%) developed dyslipidemia during a median follow-up of 5.9 years. After adjusting for potential confounders, participants with elevated arterial stiffness at baseline had an increased risk of dyslipidemia (HR, 1.194; 95% CI, 1.050-1.358). Compared with persistent low baPWV, new-onset and persistent high baPWV were associated with a 51.2% and 37.1% excess risk of dyslipidemia.

Conclusion

The findings indicated that arterial stiffness is an early risk factor of dyslipidemia, suggesting a bidirectional association between arterial stiffness and lipid metabolism.

Added value of arterial stiffness index for the 10-year atherosclerotic cardiovascular disease risk determination in a middle-aged population-based study

OBJECTIVE

Atherosclerotic cardiovascular disease (ASCVD) is considered the leading cause of mortality worldwide. Arterial stiffness, measured by arterial stiffness index (ASI), could be a main predictor in target damage of organs. Uncertainty remains regarding the contribution of ASI to estimated ASCVD risk. This study investigates the added value of ASI in ASCVD risk determination using the general UK Biobank middle-aged population.

METHODS

Among 100,598 participants from the UK Biobank population, ASI was assessed and associations between ASCVD risk were stratified by sex and estimated using multiple linear and logistic regressions adjusted for heart rate, physical activity, alcohol status, smocking pack years, BMI categories and CKD.

RESULTS

Males presented higher ASCVD risk than females (8.58% vs. 2.82%, p < 0.001) and higher ASI levels (9.50 m/s vs. 7.00 m/s, p < 0.001). The Youden index was determined at 9.70 m/s in males (p < 0.001) and 10.46 m/s in females (p < 0.001). Among females, participants with ASI > 10.46 m/s showed higher ASCVD risk than others (3.64% vs. 2.56%, p < 0.001), similar results were observed for males (9.92% vs. 7.21%, p < 0.001). In males, ASI showed significant added value information when including overall covariates (AUC = 0.695 vs. AUC = 0.663, p < 0.001). Similar results were observed in females (AUC = 0.693 vs. AUC = 0.687, p = 0.001). In both genders, for the association between ASI and ASCVD risk, nonlinear relationships were observed with higher accuracies than linear models.

CONCLUSION

Further studies should investigate ASCVD risk stratification management depending on ASI measurement.

The association between erector spinae muscle content and chronic heart failure and its severity

AIMS

Previous studies have shown a significant reduction in skeletal muscle content in patients with chronic heart failure (CHF). The present study focused on the erector spinae muscle (ESM) to determine whether ESM content is associated with the development and severity of CHF.

METHODS AND RESULTS

A total of 652 patients were included in this trial for the study. According to the diagnostic criteria of CHF, 652 patients were divided into two groups, namely, the control group (268 patients) and the CHF group (384 patients). Meanwhile, to assess whether the ESM is associated with the severity of CHF, patients in the CHF group were divided into two groups according to left ventricular ejection fraction (LVEF) values: heart failure with preserved ejection fraction (HFpEF, LVEF ≥50%, 256 patients) and heart failure with reduced ejection fraction (HFrEF, LVEF ≤40%, 68 patients). Receiver operating curve analysis was performed to assess whether ESM content could predict CHF and determine its severity. Compared with the control group, the patients in the CHF group were older, the prevalence of coronary heart disease (CHD) and atrial fibrillation was higher, the colour ultrasound results showed that LVEF decreased significantly, and the left ventricular end-diastolic internal diameter and left ventricular end-systolic internal diameter increased significantly. Besides, patients in the CHF group had significantly lower ESM content, and ESM is an independent predictor of heart failure, with an odds ratio of 0.713 (CHF group vs. control group, 95% confidence interval 0.626-0.811, P < 0.001). Compared with the HFpEF group, the HFrEF group has a lower prevalence of CHD, LVEF decreased significantly, the left ventricular end-diastolic internal diameter and left ventricular end-systolic internal diameter increased significantly, also patients in the HFrEF group had significantly lower ESM content compared with patients in the HFpEF group, and ESM is an independent predictor of the severity of heart failure, with an odds ratio of 0.514 (HFrEF group vs. HFpEF group, 95% confidence interval (0.418-0.633, P < 0.05). The results of receiver operating curve analysis showed that the sensitivity and specificity of ESM content for the diagnosis of CHF were 65.6% and 71.6%, respectively, while the sensitivity and specificity of ESM content for predicting the severity of CHF were 47.1% and 89.1%, respectively.

CONCLUSIONS

The ESM is of great value in predicting the onset and severity of CHF.

Association between tobacco smoking and alcohol consumption with arterial stiffness

Few investigations have been performed between tobacco smoking, alcohol, and arterial stiffness. The purpose of our study was to investigate the association between smoking use and alcohol with arterial stiffness index (ASI) in a middle-age population. Smoking pack-years and cigarettes per day were defined as alcohol consumption in units/day. Sex associations between smoking and alcohol with ASI were estimated using multiple linear regressions. Interactions and synergistic effects were investigating. 98 039 individuals of the UK Biobank cohort were included (45 457 men and 52 582 women). ASI levels were higher in men than in women (9.91 vs. 8.71 m/s, p < .001), and showed higher relationship to smoking tobacco in multiple linear regression models in women than in men (FDR logworth 78.4 vs. 52.7). The findings revealed that ASI was higher among current smokers than never smokers in both sex and after adjustment for all covariates (in men 10.4 vs. 9.6 and in women 9.5 vs. 8.5 m/s, p < .001). Alcohol consumption per day was positively associated with higher levels of ASI in both sex, but with a less relationship (FDR logworth for men = 2.8, for women = 2.5). An interaction was observed between smoking information and alcohol in men but not in women. Synergistic effects were observed by adding smoking information on alcohol consumption models in men and women (p = .029, p < .001, respectively). Smoking and alcohol were associated with higher ASI in both sex but with a higher relationship among women. The findings suggest the importance of considering smoking and alcohol consumption cessation in cardiovascular diseases prevention.

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.

Arterial stiffness nomogram identification by cluster analysis: A new approach of vascular phenotype modeling

Arterial stiffness, measured by arterial stiffness index (ASI), can be considered as a major denominator in cardiovascular diseases. Thus, it remains essential to highlight patient phenotyping profiles with high ASI values. A nomogram of arterial stiffness was evaluated by calculation of ASI nomogram. Theoretical ASI can be performed according to age, sex, mean blood pressure, and heart rate, allowing to form an individual ASI nomogram [(measured ASI - theoretical ASI)/theoretical ASI]. An ASI nomogram > 0 defined AS. This study investigates among UK Biobank participants without cardiovascular diseases, the hypothesis that K-means cluster analysis can be used to identify homogeneous phenotyping subgroups of participants according to ASI levels and then, the phenotype differences observed between these clusters. ASI nomogram was applied on 132 851 participants. K-means clustering was implemented with 10 clusters (optimal CCC value of 105.246). One cluster showed 100% rate of AS, corresponding to 25 393 participants (41.6% of the AS participants) with ASI nomogram = .26 (.22), ASI = 11.6 (2.3)m/s. A second cluster showed a 100% of non-AS, corresponding to 27 844 participants (38.8% of the participants with no arterial stiffness) with ASI nomogram = -.22 (.13), ASI = 7.1 (1.44)m/s. Threshold values of independent factors for differencing these two clusters were total cholesterol > 5.409 mmol/L (P < .001), triglycerides > 1.286 mmol/L (P < .001), smoking pack years > 11.8 pack/years, CRP > .99 (P < .001), daily alcohol consumption > 1.794 units/days and BMI > 26.641 kg/m² (P < .001). Cluster analysis allowed to highlight homogeneous participants profile with or without AS. Determine the markers differencing these clusters participates in the management of cardiovascular preventive strategies.