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Central Systolic Blood Pressure (cSBP) and Central Augmentation Index (cAIx) have been independently associated with cardiovascular risk in adults, and can be estimated using a generalized peripheral-to-central transfer function. We hypothesize that transfer function accuracy and precision will be influenced by degree of growth and change in body habitus during periods of growth, such as in childhood. We studied the pulse pressure waveforms of 91 healthy children at 8-years of age, and subsequently at 14-years of age. Waveforms were obtained by high-fidelity applanation tonometry of the radial and carotid arteries. Individualized radial-to-carotid transfer functions were formulated at 8-years of age and applied at 14-years of age to estimate cSBP and cAIx. Accuracy was defined as the difference between directly measured and predicted values, and precision as the residuals. Changes in weight (vs. error: β = −0.22, p = 0.04; vs. residuals: β = 0.30; p < 0.01) and body mass index (vs. residuals: β = 0.28, p < 0.01), between 8 and 14 years of age were associated with accuracy and precision of individualized transfer functions in predicting cSBP at 14 years of age. Change in weight (vs. residuals: β = 0.30; p < 0.01) and heart rate (vs. residuals β = 0.32, p < 0.01) were associated with the precision in predicting cAIx. Changes in body habitus and heart rate over a 6-year period of growth are associated with the predictive accuracy and precision of individualized transfer functions in children suggestive of changes in the frequency response characteristics of an individual’s vascular system during growth periods.

Background: Arterial stiffness is a significant cardiovascular risk factor. Carotid-femoral pulse wave velocity (cfPWV) is the standard for measuring arterial stiffness, but indices such as central augmentation index (cAIx) and carotid artery elasticity (cE[p]) also correlate to arterial stiffness. Early-life determinants of arterial stiffening are not well understood. We assessed the relationship between population-indexed anthropometric and hemodynamic parameters, and arterial stiffness in healthy children. Methods: 97 healthy children between 2 to 20 years old were recruited. Z-scores for height, BMI, and brachial systolic (bSBP) and diastolic (bDBP) blood pressure were calculated [1,2]. cfPWV and central arterial waveforms were measured using the Sphygmocor XCEL and CvMS devices (AtCor, Sydney) respectively. Carotid artery maximum and minimum diameters were measured by high-resolution ultrasonography. cfPWV, cE[p], and cAIx were calculated. Results: In bivariate analysis, cfPWV was associated with age (b = 0.52, p < 0.01) and bSBP z-score (b = 0.24, p = 0.03). These associations were independent of sex, height z-score, BMI z-score, and bDBP z-score in a multivariable model (R2 = 0.23). cE[p] was significantly associated with age (b = 0.42, p < 0.01), bSBP z-score (b = 0.45, p < 0.01), and height z-score (b = −0.33, p = 0.01), but only bSBP z-score remained statistically significant in the multivariable model (b = 0.45, p < 0.01; R2 = 0.20). cAIx was not associated with anthropometric or hemodynamic z-scores. Conclusion: cfPWV is associated with age and bSBP z-score, while cE[p] is associated with bSBP z-score only, suggesting a potentially key association between systolic blood pressure and indices of arterial stiffness independent of age and other parameters of growth during healthy early life.

Background: Carotid femoral pulse wave velocity (cfPWV) is directly associated with arterial stiffness in major elastic arteries and predicts future cardiovascular events (1). Little is known of cfPWV as a marker of vascular health in children. Semi-automated cuff-based devices for assessing cfPWV are increasingly popular, although these utilize an algorithm developed and validated in adults (2). Physiological differences between adults and children may thus reduce the accuracy of cuff-based. Methods: We sought to determine the accuracy of a cuff-based cfPWV device in healthy children and determine whether an age-appropriate algorithm increases accuracy. Methods we prospectively recruited 29 healthy children (mean age = 11.5 ± 5.2 years old). cfPWV was measured using a tonometer on the carotid artery and an inflated cuff on the thigh (Sphygmocor XCEL; AtCor Medical, Australia), and using a tonometer on both the carotid artery and femoral artery (SphygmoCor CvMS; AtCor Medical, Australia) as a reference method. We assessed the accuracy of the cuff-based device with its standard algorithm that was developed in adults, and an adjusted algorithm corrected for physiological differences in leg (femoral to thigh cuff) PWV between adult and children (3). Results: Cuff-based device estimates of cfPWV in children had excellent agreement to the reference standard (r = 0.85; Δ = −0.26 ms−1 [SD 0.44]). The adjusted algorithm improved the accuracy of the cuff-based method (r = 0.84; Δ=0.02 ms−1 [SD 0.44]) (Figure 1). Conclusions: Although the cuff-based semi-automatic approach estimates cfPWV with excellent agreement to the reference standard, adjusting the algorithm for known differences in leg PWV improves the accuracy of cuff-based measurement in children.

Objectives: Carotid-femoral pulse wave velocity (cfPWV) is a validated non-invasive measure of aortic stiffness. Risk factors for cfPWV are well described in adulthood, and furthermore cfPWV is associated with incident cardiovascular disease in adults (1). However, risk factors for arterial stiffness in childhood are poorly described (2). Accordingly, we sought to determine the risk factors for cfPWV in childhood and adolescence and hypothesized that cfPWV would be higher amongst those with greater adiposity. Methods: We prospectively recruited 88 healthy children (mean age = 11.0 ± 5.3 years old). Age, weight, height, and blood pressure were measured. cfPWV was assessed using a semi-automated cuff-based device (Sphygmocor XCEL; AtCor Medical, Australia), and body composition using air displacement plethysmography (BOD POD; Cosmed, Italy) (3). Associations with cfPWV were determined by multivariable linear regression, with subsequent mediation analyses to inform likely causal pathways. Results: After adjusting for age and sex, cfPWV was significantly associated with weight, body mass index (BMI), systolic blood pressure, mean blood pressure, heart rate, and lean body mass (LBM), while LBM was significantly associated with height, weight, BMI and fat mass (Table 1). After further adjusting for weight, mean blood pressure and heart rate, LBM remained significantly associated with cfPWV (ß = 0.68; p = 0.007). Mediation analyses indicate that weight mediates the association between age and cfPWV (PM = 76%), and that LBM mediates the relationship between weight and cfPWV (Figure 1). Conclusion: Higher cfPWV in healthy children and adolescents is a function of growth, and this association may be in turn mediated by higher LBM rather than adiposity.