Brachial Pressure Waveforms Research Articles

Comparison of effects of peripheral vasculature on tonometric radial pulse and cuff-based brachial pulse waveform as used in estimation of central aortic pressures.

Aortic pressure estimation requires reliable peripheral pulse waveform acquisition. The peripheral waveform can change with local vascular effects that can be independent of aortic pressure. This study quantifies the effects of peripheral vasculature changes on radial and brachial waveforms. In 20 subjects (37± 15 years, 7 female), brachial volumetric displacement (cuff-based) and radial tonometry waveforms were simultaneously measured whilst a cuff around the hand on the same arm was inflated to induce transmural pressures of -60, -30, -15, 0, 15 and 30 mmHg, altering local peripheral resistance and compliance by graded arterial wall unloading. Aortic blood pressure (BP), augmentation index (AIx) and ejection duration were calculated from the measurements using a generalized transfer function. The parameters under unloaded conditions were compared to baseline measurements. Brachial systolic and diastolic BP did not change throughout the experiment. Altering peripheral resistance and compliance did not significantly change calculated aortic BP values, although changes were nominally greater for radial (maximum +8±1 mmHg) compared to brachial (maximum +2±1 mmHg) waveforms. AIx at 0 mmHg transmural pressure (maximum arterial wall unloading) was higher when derived from radial waveforms (+24±3%, p<0.001) but not when derived from brachial waveforms. Localized changes in peripheral resistance and compliance affect tonometer acquired radial waveforms but not volumetric displacement acquired brachial pressure waveforms, as judged by computed central aortic augmentation pressure parameters. This suggests aortic pressure estimation from the brachial cuff waveform is less sensitive to peripheral vasculature disturbances that alter the peripheral arterial pulse morphology.

Racial Differences in Blood Pressure and Autonomic Recovery Following Acute Supramaximal Exercise in Women.

Despite the growing popularity of high-intensity anaerobic exercise, little is known about the acute effects of this form of exercise on cardiovascular hemodynamics or autonomic modulation, which might provide insight into the individual assessment of responses to training load. The purpose of this study was to compare blood pressure and autonomic recovery following repeated bouts of acute supramaximal exercise in Black and White women. A convenience sample of twelve White and eight Black young, healthy women were recruited for this study and completed two consecutive bouts of supramaximal exercise on the cycle ergometer with 30 min of recovery in between. Brachial and central aortic blood pressures were assessed by tonometry (SphygmoCor Xcel) at rest and 15-min and 30-min following each exercise bout. Central aortic blood pressure was estimated using brachial pressure waveforms and customized software. Autonomic modulation was measured in a subset of ten participants by heart-rate variability and baroreflex sensitivity. Brachial mean arterial pressure and diastolic blood pressure were significantly higher in Blacks compared to Whites across time (race effect, p = 0.043 and p = 0.049, respectively). Very-low-frequency and low-frequency bands of heart rate variability, which are associated with sympathovagal balance and vasomotor tone, were 22.5% and 24.9% lower, respectively, in Blacks compared to Whites (race effect, p = 0.045 and p = 0.006, respectively). In conclusion, the preliminary findings of racial differences in blood pressure and autonomic recovery following supramaximal exercise warrant further investigations of tailored exercise prescriptions for Blacks and Whites.

Personalized aortic pressure waveform estimation from brachial pressure waveform using an adaptive transfer function

Background and objectiveThe aortic pressure waveform (APW) provides reliable information for the diagnosis of cardiovascular disease. APW is often measured using a generalized transfer function (GTF) applied to the peripheral pressure waveform acquired noninvasively, to avoid the significant risks of invasive APW acquisition. However, the GTF ignores various physiological conditions, which affects the accuracy of the estimated APW. To solve this problem, this study utilized an adaptive transfer function (ATF) combined with a tube-load model to achieve personalized and accurate estimation of APW from the brachial pressure waveform (BPW). MethodsThe proposed method was validated using APWs and BPWs from 34 patients. The ATF was defined using a tube-load model in which pulse transit time and reflection coefficients were determined from, respectively, the diastolic-exponential-pressure-decay of the APW and a piece-wise constant approximation. The root-mean-square-error of overall morphology, mean absolute errors of common hemodynamic indices (systolic blood pressure, diastolic blood pressure and pulse pressure) were used to evaluate the ATF. ResultsThe proposed ATF performed better in estimating diastolic blood pressure and pulse pressure (1.63 versus 1.94 mmHg, and 2.37 versus 3.10 mmHg, respectively, both P < 0.10), and produced similar errors in overall morphology and systolic blood pressure (3.91 versus 4.24 mmHg, and 2.83 versus 2.91 mmHg, respectively, both P > 0.10) compared to GTF. ConclusionUnlike the GTF which uses fixed parameters trained on existing clinical datasets, the proposed method can achieve personalized estimation of APW. Hence, it provides accurate pulsatile hemodynamic measures for the evaluation of cardiovascular function.

Estimation of viscoelasticity of a carotid artery from ultrasound cine images and brachial pressure waveforms: Viscous parameters as a new index of detecting low plaque burden.

Viscoelasticity may be an important physical index for diagnosing vascular diseases, but wall viscosity has received less attention than elasticity due to difficulties in measurement in clinical scenarios. In this study, viscoelastic parameters were estimated from the pressure diameter relationship using carotid artery ultrasound images and brachial artery pressure waveforms of the patients. Carotid artery diameter waveforms were obtained by analyzing wall motion in ultrasound cine images, and carotid pressure waveforms were estimated from brachial waveforms using a transfer function. The estimated viscoelastic parameters quantitatively agreed with the published data, and three viscous parameters (viscous index, energy dissipation ratio, and phase lag between pressure and diameter waveforms) showed good positive correlations with each other. No significant difference in wall elasticity was found between the no plaque (NP) and low plaque (LP) groups, whereas viscous parameters were lower in the NP group than the LP group. This result suggests that the viscous parameters may be a new mechanical index for detecting early atherosclerosis.

HEART-TO-ANKLE PULSE WAVE VELOCITY AS USED IN CARDIO-ANKLE VASCULAR INDEX (CAVI) AND CAVI_0 IS A NEARLY DIASTOLIC WAVE SPEED METRIC

Objective: Cardio-ankle vascular index (CAVI) and CAVI_0 are arterial stiffness indices based on the heart-to-ankle pulse wave velocity (haPWV). haPWV is derived from the heart-to-ankle transit time (haTT = tb+tba) as haPWV = L/haTT, with L an estimated transit distance. tb is the time difference between aortic valve closure (causing the aortic dicrotic notch) and the dicrotic notch in the brachial pressure waveform; tba is the time difference between the diastolic feet in the brachial and ankle pressure waveforms. CAVI and CAVI_0 aim to normalise haPWV for blood pressure at the time of measurement. As tb and tba are determined at different pressures — tb at dicrotic notch pressure (P_notch); tba at diastolic blood pressure (DBP; Fig. C) — determining the pressure that governs haPWV (P_haPWV) and hence should ideally be used for normalisation of haPWV is not trivial. CAVI uses P_m = (SBP+DBP)/2 to normalise haPWV, whereas CAVI_0 uses DBP (SBP: brachial systolic blood pressure). We aim to analytically estimate P_haPWV and compare this to the normalisation pressures used in CAVI and CAVI_0. Design and method: Consistent with CAVI/CAVI_0 assumptions, the arterial tree was assumed to consist of tubes with exponential pressure-diameter relationship and uniform stiffness index beta_0, allowing us to calculate PWV at P_notch (PWV_notch) and at DBP (PWV_DBP; Fig. A). P_notch was calculated as 0.55DBP+0.45SBP [Adji et al.,J Hypertens 2012;30:1540–1551]. The resulting PWVs, together with heart-to-ankle (L_ha=170 cm) and heart-to-brachial (L_hb=38 cm) path lengths [Alastruey et al.,11th Int Conf Press Surges 2012;401–442] (Fig. B), allowed analytically estimating tb and tba: tb=L_hb/PWV_notch and tba=(L_ha-L_hb)/PWV_DBP. P_haPWV was finally estimated as the weighted average of P_notch and DBP using tb and tba as weights. Results: Choosing SBP/DBP=120/80 mmHg (and hence P_m=100 mmHg) and beta_0 = 10 yielded tb = 0.048 s and tba = 0.187 s, giving P_haPWV = 84 mmHg. This implies that P_haPWV was much closer to DBP (as used in CAVI_0) than to P_m (as used in CAVI). This result was only marginally influenced by blood pressure: e.g., SBP/DBP = 160/90 mmHg (P_m = 125 mmHg) yielded P_haPWV = 96 mmHg. Conclusions: DBP offers a more accurate estimate of P_haPWV than Pm, supporting the utility of CAVI_0 as an enhancement of CAVI.

Prognostic Value of Pressure-Volume Measures in Hemocompatibility-Related Clinical Adverse Events

<h3>Purpose</h3> Continuous-flow left ventricular assist device (cf-LVADs) can lead to hemocompatibility-related clinical adverse events (HRAEs) which are largely determined by mechanisms that underpin the pump-patient interaction. We assessed the association of pressure-volume (PV) measures [stroke work (SW) & pump arterial elastance (E_A)] with incidence of HRAEs. <h3>Methods</h3> Using a validated algorithm, brachial-pressure waveforms from oscillometric blood pressure cuff (SphygmoCor Xcel), echocardiography measures and Medtronic HVAD controller data were collected for estimation PV measures within the first 3 months. Patients (all Bridge-To-Transplantation) were divided into low, intermediate and high tertiles for each of SW (n=13, 14, 9) and E_A (n=12, 12, 12). HRAEs, including nonsurgical bleeding (NB), neurological (NE) and thromboembolic events (TE), was followed through a 12-month period post-implant. Hemocompatibility score (HCS) was calculated based on HRAEs in the 1^st year. Comparison between groups were conducted with one-way ANOVAs and Kruskal-Wallis analyses. Kaplan Meier survival analyses determined time-to-event. <h3>Results</h3> 36 HVAD patients (mean age 57±10, 83% males, 69% non-ischemic cardiomyopathy) were included. Baseline demographics and clinical parameters were comparable between SW and E_A tertile groups. Low E_A group had significantly higher rates of HRAEs in the 1^st year compared to intermediate and high groups (p=0.004). HRAE rates were marginally higher in the low SW group (p=0.080). There were no differences in HCS. Survival analysis showed significant differences in distribution of 1-year cumulative HRAE-free probabilities according to E_A tertiles (33.3%, 83.3% and 91.7% for low, intermediate and high E_A respectively, log-rank=0.003). <h3>Conclusion</h3> PV measures offer value in prognostication of LVAD patients. This study highlights the potential importance of assessing afterload and native ventricular contractility in circumventing HRAEs in cf-LVAD patients.

Unique Findings of Myocardial Improvement with Lower Left Ventricular Assist Device Pump Speed

<h3>Purpose</h3> Currently, optimizing hemodynamics and unloading in patients with left ventricular assist device (LVAD) relies on echocardiography and right heart catherization guidance for pump speed adjustments. However, the ideal unloading strategy to maximize reverse remodelling is uncertain - whether to provide maximal pump support to unload the heart (‘rest'), or maximize ventricular work with partial pump support (‘work'). Using non-invasively derived PV loops, we sought to characterize the longitudinal changes in chamber contractile parameters stroke work (SW), peak systolic pressure (LVP_max) and peak LV elastance (E_es) at different pump speeds [2400 vs 2500 vs 2600 revolutions/min (rpm)]. <h3>Methods</h3> 32 Medtronic HVAD patients (mean 55.9±12.3 yrs, 81.3% male) were included in the study. Single-cycle pressure and volume estimations were performed using a validated algorithm with the following bedside measurements: echo parameters, HVAD controller-derived data and oscillometric brachial pressure waveform (SphygmoCor Xcel). In total, 77 PV loops were prospectively collected at 3 intervals: 1, 3 and 6 months post-implant (n=26, 29, 22). Corresponding ventricular contractile parameters SW, LVP_max and E_es were calculated. Pump speed was included as a fixed effect to determine its impact on the longitudinal changes in PV parameters. <h3>Results</h3> There were no significant differences in demographics and clinical data between pump speed groups. Linear mixed-effects model was performed to estimate trends in PV parameters. Patients with pump speed of 2400rpm demonstrated significant monthly increase in SW, LVP_max and E_es at 0.05mmHg/L (95%CI 0.02-0.08, p<0.001), 5.64mmHg (95%CI 1.08-10.2, p=0.016) and 0.071mmHg/mL (95%CI 0.002-0.141, p=0.041) per month respectively. The trajectories were significantly different to the patients with higher speeds of 2500rpm and 2600rpm, in whom the PV parameters were largely unchanged across the first 6 months. These findings were consistent after adjusting for baseline cardiovascular risk factors in a covariate-adjusted model. <h3>Conclusion</h3> Our results provide compelling evidence of the impact pump speed has on the longitudinal changes in cardiac chamber function post-LVAD. Randomized studies are required to evaluate the impacts of lowering pump speed as a strategy, to enhance reverse remodelling in suitable patients.

Simultaneous adaption of the gain and phase of a generalized transfer function for aortic pressure waveform estimation

GoalThis paper proposes and validates a completely adaptive transfer function (CATF) based on an autoregressive exogenous (ARX) model which adjusts the gain and phase of a generalized transfer function (GTF) simultaneously to estimate the aortic pressure waveform from a brachial pressure waveform. MethodsInvasive aortic and brachial pressure waveforms were recorded from 34 subjects for the validation of the proposed method. Individual transfer functions (ITFs) were trained based on the pressure waveforms using an ARX model. The GTF was derived by averaging the ITFs. CATF was then obtained by adjusting both the gain and phase of the GTF using regression formulas calculated from the ITFs and brachial hemodynamic parameters. Meanwhile the quantitative contributions of the adaption of gain and phase of the GTF were investigated respectively. The root-mean-square-error of the total waveform and absolute errors of common hemodynamic indices including systolic and diastolic blood pressures (SBP and DBP, respectively), pulse pressure (PP) and augmentation index were used to evaluate the performance of the proposed method in the data divided into low, middle and high PP amplification groups. ResultsThe CATF achieved lower errors for DBP and PP in the low PP amplification group (1.79 versus 2.10 mmHg and 5.08 versus 6.23 mmHg, respectively, both P < 0.05) and PP in the middle amplification group (1.43 versus 1.92 mmHg, P < 0.05) compared with the GTF. SignificanceThe proposed method provides a step towards the development of an improved and clinically useful non-invasive approach for estimating the aortic pressure waveform from a peripheral pressure waveform.

Five years of cardio-ankle vascular index (CAVI) and CAVI0: how close are we to a pressure-independent index of arterial stiffness?

Pulse wave velocity, a common metric of arterial stiffness, is an established predictor for cardiovascular events and mortality. However, its intrinsic pressure-dependency complicates the discrimination of acute and chronic impacts of increased blood pressure on arterial stiffness. Cardio-ankle vascular index (CAVI) represented a significant step towards the development of a pressure-independent arterial stiffness metric. However, some potential limitations of CAVI might render this arterial stiffness metric less pressure-independent than originally thought. For this reason, we later introduced CAVI0. Nevertheless, advantages of one approach over the other are left debated. This review aims to shed light on the pressure (in)dependency of both CAVI and CAVI0. By critically reviewing results from studies reporting both CAVI and CAVI0 and using simple analytical methods, we show that CAVI0 may enhance the pressure-independent assessment of arterial stiffness, especially in the presence of large inter-individual differences in blood pressure.

ESTIMATION OF MEAN ARTERIAL PRESSURE BY THE ANALYSIS OF BRACHIAL PULSE WAVEFORM RECORDED BY APPLANATION TONOMETRY AND COMPARISON WITH CURRENTLY USED ALGORITHMS

Objective: Mean arterial pressure (MAP) is usually calculated by adding one third of pulse pressure (PP) to diastolic blood pressure (DBP). This formula assumes that the average waveform of pulse pressure (PP) is constant in all individuals and 33.3% of PP is needed to obtain MAP (MAP = DBP + PPx0.333). Other empirical formulas were proposed to calculate MAP, by adding to DBP a different established percentage of PP: MAP = DBP + PPx0.40; MAP = DBP + PPx0.412; MAP = DBP + PPx0.333 + 5mmHg. The estimation of MAP by considering a fixed relationship between SBP and DBP may not be appropriate in the single patient, if significant inter-individual and intra-individual variations occur in the pressure waveform. Design and method: We evaluated the inter-individual variations in MAP calculated from the integral of brachial pressure waveform recorded by applanation tonometry in 1526 patients belonging to 3 distinct cohorts: elderly, hypertensive, and normotensive adults, and the intra-individual variations in 19 healthy controls after a mental stress test. Results: The percentage of PP required to be added to DBP to obtain MAP was extremely variable among individuals, ranging from 23% to 58% (mean: 42.2 ± 5.5%), was higher in females (42.9 ± 5.6%) compared to males (41.2 ± 5.1%, p &lt; 0.001), lower in the elderly cohort (40.9 ± 5.3%) than in the general population cohort (42.8 ± 6.0%, p &lt; 0.001) and in the hypertensives (42.4 ± 4.8%, p &lt; 0.001). This percentage was significantly associated with DBP (b = 0.357, p &lt; 0.001) and gender (b = 0.203, p &lt; 0.001). A significant increase in this percentage (from 39.9 ± 3.2 to 43.0 ± 4.0, p &lt; 0.0001) was found in 19 volunteers, after mental stress test, and was significantly correlated to the increase in blood pressure and heart rate (p = 0.001). MAP value assessed on the brachial tonometric curve was compared with the MAP estimated by formulas proposed in the literature: the average bias from tonometric MAP (mean ± 1.96xSD) was: -5.0 ± 6.7 mmHg when MAP = DBP + PPx0,333; -1.2 ± 6.1 mmHg when MAP = DBP + PPx0.40; -0.6 ± 6.1 mmHg when MAP = DBP + PPx0.412; -0.4 ± 6.7 mmHg when MAP = DBP + PPx0.333 + 5. Conclusions: Due to high interpersonal variability, the estimation of MAP based on fixed formulas is unreliable and inadequate. An improvement in the evaluation of MAP is advisable in daily clinical practice and may be based on the analysis of brachial pulse waveform.

Area of the pressure-strain loop during ejection as non-invasive index of left ventricular performance: a population study

BackgroundPrevious studies highlighted the usefulness of integrating left ventricular (LV) deformation (strain) and hemodynamic parameters to quantify LV performance. In a population sample, we investigated the anthropometric and clinical determinants of a novel non-invasive index of LV systolic performance derived from simultaneous registration of LV strain and brachial pressure waveforms.MethodsThree hundred fifty-six randomly recruited subjects (44.7% women; mean age, 53.9 years; 47.5% hypertensive) underwent echocardiographic and arterial data acquisition. We constructed pressure-strain loops from simultaneously recorded two-dimensional LV strain curves and brachial pressure waveforms obtained by finger applanation tonometry. We defined the area of this pressure-strain loop during ejection as LV ejection work density (EWD). We reported effect sizes as EWD changes associated with a 1-SD increase in covariables.ResultsIn multivariable-adjusted analyses, higher EWD was associated with age, female sex and presence of hypertension (P ≤ 0.0084). In both men and women, EWD increased independently with augmentation pressure (effect size: + 59.1 Pa), central pulse pressure (+ 65.7 Pa) and pulse wave velocity (+ 44.8 Pa; P ≤ 0.0006). In men, EWD decreased with relative wall thickness (− 29.9 Pa) and increased with LV ejection fraction (+ 23.9 Pa; P ≤ 0.040). In women, EWD increased with left atrial (+ 76.2 Pa) and LV end-diastolic (+ 43.8 Pa) volume indexes and with E/e’ ratio (+ 51.1 Pa; P ≤ 0.026).ConclusionOlder age, female sex and hypertension were associated with higher EWD. Integration of the LV pressure-strain loop during ejection might be a useful tool to non-invasively evaluate sex-specific and interdependent effects of preload and afterload on LV myocardial performance.

Precision calibration of peripheral pressure waveforms using intra-arterial blood pressure reveals the need for improved ways to accurately estimate aortic blood pressure

BackgroundEstimating aortic blood pressure (BP) non-invasively requires peripheral waveform calibration using cuff systolic (SBP) and diastolic (DBP). Accuracy of estimated aortic BP has never been determined when peripheral waveforms are precision calibrated using peripheral intra-arterial SBP/DBP. This is relevant to understanding the best methods to estimate aortic BP accurately and was the aim of this study. We also determined how other calibrations influence estimated aortic BP accuracy.MethodsAscending aortic, brachial and radial artery intra-arterial BP was measured among 104 patients (61.8 ± 10 years, 66% male) undergoing coronary angiography. Intra- arterial aortic SBP was compared with estimated aortic SBP by generalised transfer function (SphygmoCor) using: (1) intraarterial brachial pressure waveforms calibrated with intra-arterial brachial SBP/DBP; (2) intra-arterial radial pressure waveforms calibrated with intra-arterial brachial SBP/DBP and (3) radial SBP/DBP and; (4) intra-arterial aortic mean arterial pressure (MAP)/DBP.ResultsAll intra-arterial SBP/DBP peripheral waveform calibrations significantly underestimated intra-arterial aortic SBP ((1) −4.5 ± 7.0 mmHg; (2) −8.8 ± 8.0 mmHg and (3) −5.4 ± 7.6 mmHg; p < 0.0001 all). Conversely, intra-arterial aortic MAP/DBP calibration (4) accurately estimated aortic SBP (0.03 ± 4.6 mmHg, p = 0.95). Underestimation of intra-arterial aortic SBP was related to lower aortic-to-brachial SBP amplification (r > 0.25, p < 0.009 all calibrations).ConclusionEven when using accurate (intra-arterial) SBP/DBP for precision peripheral waveform calibration, aortic SBP was significantly underestimated. Intra-arterial aortic MAP/DBP was the most accurate calibration, but is not feasible for non-invasive use. These findings highlight the need for improved ways to accurately estimate aortic SBP.

Increase in the Arterial Velocity Pulse Index of Patients with Peripheral Artery Disease

Background: Recently, a simple parameter calculated from the brachial pressure waveform recorded using an oscillometric device (arterial velocity pulse index [AVI]: ratio of the forward/reflected pressure wave amplitudes) has become available to assess the pathophysiological abnormalities associated with vascular damage. Peripheral artery disease (PAD) represents one of the disease entities associated with the advanced stages of atherosclerotic vascular damage. The present study was conducted to examine whether an increase in the AVI might be influenced by the presence of PAD. Methods and Results: The AVI was measured from oscillometric recordings of the brachial pressure waveform, and the ankle-brachial pressure index (ABPI) was determined by an oscillometric method. Study 1: In 341 consecutive patients admitted for the management of cardiovascular disease and/or cardiovascular risk factors, the ABPI and the AVI were measured simultaneously. An ABPI ≤0.90 was observed in 19 subjects, and logistic regression analysis revealed a significant association between AVI and ABPI ≤0.90 (odds ratio = 1.81; 95% confidence interval = 1.15–2.84; p = 0.01). Study 2: In another 19 patients with PAD, percutaneous transluminal angioplasty resulted in a decrease in the AVI from 31 ± 8 to 27 ± 8 (p < 0.01). Conclusion: Possible presence of PAD must be taken into account while applying the AVI for the assessment of vascular damage.

7D.09

Objective: Estimation of central aortic pressure requires reliable acquisition of a peripheral pulse waveform either using radial tonometry or volumetric displacement within a brachial cuff. This study tests whether the radial and brachial waveforms are influenced by changes in properties of the peripheral vasculature of the hand, such an influence potentially compromising central aortic pressure estimation. Design and method: In 15 subjects (37 ± 15 years, 7 female), brachial waveform acquired by volumetric displacement (cuff-based) and radial waveform acquired by tonometry were simultaneously measured whilst a cuff around the hand on the same arm was inflated to pressures of 30, 15, 0, −15, −30, −60 mmHg with respect to mean arterial pressure to alter peripheral resistance and compliance. Aortic parameters were compared to measurements at baseline (no hand cuff pressure) using repeated measures ANOVA with post-hoc, Bonferroni-corrected, paired t-tests. Results: Altering peripheral resistance and compliance significantly changed computed mean arterial pressure (MAP), aortic systolic pressure (aSP), pulse pressure (aPP), augmentation pressure (aAP), augmentation index (aAIx) and pulse pressure amplification (PPA) relative to baseline conditions when using tonometric radial waveforms (Table, describing maximum change). Parameters derived from the cuff-based waveform assessment did not change with alterations in the peripheral vasculature. There was no significant change in brachial systolic and diastolic values throughout the experiment.Conclusions: Localised changes in peripheral resistance and compliance affect the radial waveform (tonometer-based acquisition) but not the brachial pressure waveform (cuff-based acquisition) as judged by significant effects on the computed central aortic parameters from radial but not brachial waveforms, the largest discrepancies occurring in aAIx and in PPA. This suggests that estimation of central aortic pressure from brachial cuff waveforms is less sensitive to disturbances in the peripheral vasculature of the upper limb that alter the peripheral arterial pulse morphology

Application of the N-Point Moving Average Method for Brachial Pressure Waveform–Derived Estimation of Central Aortic Systolic Pressure

The N-point moving average (NPMA) is a mathematical low-pass filter that can smooth peaked noninvasively acquired radial pressure waveforms to estimate central aortic systolic pressure using a common denominator of N/4 (where N=the acquisition sampling frequency). The present study investigated whether the NPMA method can be applied to brachial pressure waveforms. In the derivation group, simultaneously recorded invasive high-fidelity brachial and central aortic pressure waveforms from 40 subjects were analyzed to identify the best common denominator. In the validation group, the NPMA method with the obtained common denominator was applied on noninvasive brachial pressure waveforms of 100 subjects. Validity was tested by comparing the noninvasive with the simultaneously recorded invasive central aortic systolic pressure. Noninvasive brachial pressure waveforms were calibrated to the cuff systolic and diastolic blood pressures. In the derivation study, an optimal denominator of N/6 was identified for NPMA to derive central aortic systolic pressure. The mean difference between the invasively/noninvasively estimated (N/6) and invasively measured central aortic systolic pressure was 0.1±3.5 and -0.6±7.6 mm Hg in the derivation and validation study, respectively. It satisfied the Association for the Advancement of Medical Instrumentation standard of 5±8 mm Hg. In conclusion, this method for estimating central aortic systolic pressure using either invasive or noninvasive brachial pressure waves requires a common denominator of N/6. By integrating the NPMA method into the ordinary oscillometric blood pressure determining process, convenient noninvasive central aortic systolic pressure values could be obtained with acceptable accuracy.

Comparison of two generalized transfer functions for measuring central systolic blood pressure by an oscillometric blood pressure monitor

Central aortic systolic blood pressure (SBP-C) can be estimated from a cuff oscillometric waveform derived during the pulse volume plethysmography (PVP) by applying a device-specific aortic pressure-to-PVP waveform-generalized transfer function (A2P(GTF)). The present study compared the performance of an aortic-to-brachial pressure waveforms generalized transfer function (A2B(GTF)), which is independent of any PVP devices, with an A2P(GTF). Generalized transfer function of aortic-to-brachial (A2B(GTF)) and aortic-to-PVP (A2P(GTF)) were generated from the simultaneously obtained central aortic and brachial pressure waveforms recorded by a high-fidelity dual pressure sensor catheter, and the PVP waveform recorded by a customized noninvasive blood pressure monitor during cardiac catheterization in 40 patients, and were then applied in another 100 patients with simultaneously recorded invasive aortic pressure and noninvasively calibrated (using cuff SBP and diastolic blood pressures) PVP waveforms. The mean difference±s.d. between the noninvasively estimated and invasively recorded SBP-C was -2.1±7.7 mm Hg for A2B(GTF), which was not greater than that of -3.0±7.7 mm Hg for A2P(GTF) (P<0.01). In conclusion, SBP-C can be measured reliably using a noninvasive blood pressure monitor by applying either an A2P(GTF) or A2B(GTF) to a noninvasively calibrated PVP waveform. The performance of an A2B(GTF) is not inferior to that of an A2P(GTF).

Estimation of central aortic systolic pressure from the second systolic peak of the peripheral upper limb pulse depends on central aortic pressure waveform morphology

Direct identification of second systolic peaks of peripheral upper limb pulses (pSBP2) has been used to represent central systolic blood pressure (cSBP), but its accuracy at low SBP was questioned. We investigated the relationship of pSBP2 with characteristics of central pressure waveforms. High-fidelity central aortic and right brachial pressure waveforms were simultaneously recorded using a custom-made dual pressure sensor catheter in 78 patients (65.9 ± 12.9 years) during catheterization for 285 measurements. Overall agreement between cSBP and pSBP2 was good (mean difference -0.9 ± 4.8, r = 0.98), with a systematic bias at low SBP. We examined agreements of different waveform types according to the relationship of the second systolic peak of aortic pressure waveforms (cSBP2) to cSBP. Of type A (positive late systolic augmentation) and type B (zero augmentation) aortic pressure waveforms, in which cSBP = cSBP2, agreement between pSBP2 and cSBP was excellent (mean difference -0.4 ± 4.1, r = 0.99). There were 40 type C aortic pressure waveforms (negative augmentation; cSBP > cSBP2) with cSBP 107.2 ± 13.9 mmHg. Their cSBP2, compared with cSBP, showed closer agreement (mean difference -0.6 ± 3.2 vs. -4.0 ± 7.2 mmHg) and better correlation (r = 0.97 vs. 0.85, P = 0.03) with pSBP2. pSBP2 can be used with type A and B aortic pressure waveforms for estimation of cSBP. However, it should not be used with type C aortic pressure waveforms, typically at low SBP, because pSBP2 is closer to cSBP2 than cSBP. This explains why pSBP2 underestimates cSBP at low SBP.

E-005 ESTIMATION OF CENTRAL PULSE PRESSURE FROM PERIPHERAL PRESSURE WAVEFORMS

Objectives The aim of this study was to identify the major source of errors and to improve the accuracy for the noninvasive estimation of central aortic pulse pressure (PP). Background The clinical value of central PP may have been underestimated due to the inaccuracy of its measurement. Methods Invasive high-fidelity right brachial and central aortic pressure tracings and left-brachial pulse volume plethysmography (PVP) waveforms from an oscillometric blood pressure monitor were all digitized simultaneously in 40 patients during cardiac catheterization. Invasive brachial pressure waveforms were used to estimate the central PP by both the generalized transfer function (GTF) and the pressure waveform analysis (PWA) approaches. A noninvasive PWA prediction model was also constructed using the PVP waveforms calibrated by the oscillometric brachial pressures. Results Errors between the central PP and invasive estimates by GTF and PWA were −0.8 ± 3.8 mmHg and 0.0 ± 3.5 mmHg, respectively. However, the oscillometric brachial PP underestimated the invasive brachial PP by −7.4 ± 11.7 mmHg. When the brachial pressure waveforms were purposefully calibrated using oscillometric brachial pressures, the errors of the estimation of central PP were markedly inflated (−7.3 ± 8.4 mmHg by GTF, and −11.7 ± 8.6 mmHg by PWA, respectively). In contrast, the error of the noninvasive PVP model was 0.0 ± 6.7 mmHg. Conclusions Large errors are introduced into the central PP estimates from the oscillometric brachial pressures. The accuracy may be improved when the oscillometric pressures calibrated peripheral pressure waveforms are used in the construction of the prediction models.

Quantification of the Calibration Error in the Transfer Function-Derived Central Aortic Blood Pressures

The accuracy of the central aortic systolic (SBP-C) and pulse (PP-C) blood pressures estimated noninvasively by a generalized transfer function technique has been questioned. The purpose of the present study was to quantify precisely the impact of the input errors (differences between the oscillometric (SBP-O, DBP-O, PP-O) and invasive (SBP-B, DBP-B, PP-B) brachial systolic, diastolic, and pulse blood pressures) on the output errors (differences between the estimated and invasively measured SBP-C and PP-C). Invasive high-fidelity right brachial and central aortic pressure waveforms, and SBP-O, DBP-O, and PP-O (=SBP-O - DBP-O) were obtained simultaneously in 40 patients during cardiac catheterization. A generalized transfer function was applied on the individual brachial pressure waveform to derive predicted SBP-C and PP-C. Observed input errors were -2.3 ± 5.8 mm Hg from SBP-O, 8.1 ± 5.3 mm Hg from DBP-O, and -10.4 ± 7.1 mm Hg from PP-O, respectively. The output errors were -2.2 ± 6.4 mm Hg and -10.3 ± 8.0 mm Hg for SBP-C and PP-C, respectively, when the brachial pressure waveforms were recalibrated using SBP-O and DBP-O. The outputs were determined by the inputs according to the Equation (1): SBP-C error = 0.97 × SBP-O error + 0.03 (r = 0.88, P < 0.01); and the Equation (2): PP-C error = 0.96 × PP-O error - 0.30 (r = 0.86, P < 0.01). Noninvasive application of the generalized transfer function techniques produces estimates of SBP-C and PP-C with errors equivalent to those of the oscillometric blood pressure monitor in the estimation of SBP-B and PP-B. The output errors can be predicted from input errors of SBP-O and DBP-O.

Non-invasive model-based estimation of aortic pulse pressure using suprasystolic brachial pressure waveforms

Elevated central arterial (aortic) blood pressure is related to increased risk of cardiovascular disease. Methods of non-invasively estimating this pressure would therefore be helpful in clinical practice. To achieve this goal, a physics-based model is derived to correlate the arterial pressure under a suprasystolic upper-arm cuff to the aortic pressure. The model assumptions are particularly applicable to the measurement method and result in a time–domain relation with two parameters, namely, the wave propagation transit time and the reflection coefficient at the cuff. Central pressures estimated by the model were derived from completely automatic, non-invasive measurement of brachial blood pressure and suprasystolic waveform and were compared to simultaneous invasive catheter measurements in 16 subjects. Systolic blood pressure agreement, mean (standard deviation) of difference was −1 (7) mm Hg. Diastolic blood pressure agreement was 4 (4) mm Hg. Correlation between estimated and actual central waveforms was greater than 90%. Individualization of model parameters did not significantly improve systolic and diastolic pressure agreement, but increased waveform correlation. Further research is necessary to confirm that more accurate brachial pressure measurement improves central pressure estimation.