Validation of non-invasive central blood pressure devices: Artery society task force (abridged) consensus statement on protocol standardization

Central Aortic Blood Pressure Waveform Estimation with a Temporal Convolutional Network

A novel temporal convolutional network (TCN) model is utilized to reconstruct the central aortic blood pressure (aBP) waveform from the radial blood pressure waveform. The method does not need manual feature extraction as traditional transfer function approaches. The data acquired by the SphygmoCor CVMS device in 1,032 participants as a measured database and a public database of 4,374 virtual healthy subjects were used to compare the accuracy and computational cost of the TCN model with the published convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) model. The TCN model was compared with CNN-BiLSTM in the root mean square error (RMSE). The TCN model generally outperformed the existing CNN-BiLSTM model in terms of accuracy and computational cost. For the measured and public databases, the RMSE of the waveform using the TCN model was 0.55 ± 0.40 mmHg and 0.84 ± 0.29 mmHg, respectively. The training time of the TCN model was 9.63 min and 25.51 min for the entire training set; the average test time was around 1.79 ms and 8.58 ms per test pulse signal from the measured and public databases, respectively. The TCN model is accurate and fast for processing long input signals, and provides a novel method for measuring the aBP waveform. This method may contribute to the early monitoring and prevention of cardiovascular disease.

Evaluation of the agreement of two oscillometric blood pressure devices with invasive blood pressure in anaesthetized chimpanzees (Pan troglodytes)

OBJECTIVE

To evaluate the agreement of two noninvasive blood pressure devices: a human device with the cuff placed on the wrist (Omron R1) and a veterinary device with the cuff placed on the upper brachium (Surgivet Advisor Vital Signs Monitor) with invasive blood pressure (IBP) measurement in anaesthetized chimpanzees.

STUDY DESIGN

Prospective clinical study.

ANIMALS

A convenience sample of 11 adult chimpanzees undergoing anaesthesia for translocation and routine health checks.

METHODS

Systolic (SAP) and diastolic arterial pressures (DAP) were continuously recorded via a transducer connected to a femoral artery cannula, and at 5 minute intervals from the two oscillometric devices. Agreement was explored using Bland-Altman analysis and bias defined as the mean difference between the two measurement methods. Spearman correlation coefficients were calculated. Significance was set at p < 0.05.

RESULTS

Bias and standard deviation for the Surgivet compared with IBP were 8.6 ± 18 for SAP and 8.4 ± 9.9 for DAP, showing a significant underestimation of both variables. Limits of agreement (LOA) were from -27 to 44 for SAP and from -11 to 28 for DAP. Correlation coefficients between the Surgivet and IBP values were 0.86 for SAP and 0.85 for DAP (p < 0.0001). Bias and standard deviation for the Omron compared with the IBP were -21 ± 25 for SAP and -18 ± 15 for DAP, showing a significant overestimation of both variables. LOA were from -70 to -28 for SAP and from -47 to 11 for DAP. Spearman correlation coefficients between the Omron and IBP values were 0.64 for SAP and 0.72 for DAP (p < 0.0001).

CONCLUSIONS AND CLINICAL RELEVANCE

Although neither device met all the criteria for device validation, the Surgivet presented better agreement with IBP values than the Omron in adult anaesthetized chimpanzees.

Estimating central blood pressure from aortic flow: development and assessment of algorithms

Central blood pressure (cBP) is a highly prognostic cardiovascular (CV) risk factor whose accurate, invasive assessment is costly and carries risks to patients. We developed and assessed novel algorithms for estimating cBP from noninvasive aortic hemodynamic data and a peripheral blood pressure measurement. These algorithms were created using three blood flow models: the two- and three-element Windkessel (0-D) models and a one-dimensional (1-D) model of the thoracic aorta. We tested new and existing methods for estimating CV parameters (left ventricular ejection time, outflow BP, arterial resistance and compliance, pulse wave velocity, and characteristic impedance) required for the cBP algorithms, using virtual (simulated) subjects (n = 19,646) for which reference CV parameters were known exactly. We then tested the cBP algorithms using virtual subjects (n = 4,064), for which reference cBP were available free of measurement error, and clinical datasets containing invasive (n = 10) and noninvasive (n = 171) reference cBP waves across a wide range of CV conditions. The 1-D algorithm outperformed the 0-D algorithms when the aortic vascular geometry was available, achieving central systolic blood pressure (cSBP) errors≤2.1 ± 9.7mmHg and root-mean-square errors (RMSEs)≤6.4 ± 2.8mmHg against invasive reference cBP waves (n = 10). When the aortic geometry was unavailable, the three-element 0-D algorithm achieved cSBP errors ≤ 6.0 ± 4.7mmHg and RMSEs ≤ 5.9 ± 2.4mmHg against noninvasive reference cBP waves (n = 171), outperforming the two-element 0-D algorithm. All CV parameters were estimated with mean percentage errors ≤ 8.2%, except for the aortic characteristic impedance (≤13.4%), which affected the three-element 0-D algorithm’s performance. The freely available algorithms developed in this work enable fast and accurate calculation of the cBP wave and CV parameters in datasets containing noninvasive ultrasound or magnetic resonance imaging data.

Vascular Aging and Central Aortic Blood Pressure: From Pathophysiology to Treatment

Large conductive arteries undergo to structural modifications by aging, eventually leading to increased vascular stiffness. As consequence, cardiovascular hemodynamic changes by increasing central blood pressure which may be also associated to the remodelling of peripheral resistance arteries that contribute to increase further the central vascular stiffness and blood pressure. These modifications resemble the ones that has been shown in essential hypertension, thus a condition of "early vascular aging" has been described in hypertensive patients. Since hypertension related target organs, particularly the heart, face aortic blood pressure rather than brachial blood pressure, it has been recently suggested that central blood pressure and other parameters of large arteries' stiffness, including pulse wave velocity (PWV), may better correlate with subclinical organ damage and might be useful to assess the cardiovascular risk of patients beyond the traditional risk factors. Different devices have been validated to measure central blood pressure and PWV, and are currently available for clinical use. The increasing application of these tools in clinical practice could improve the management of hypertensive patients by better defining the cardiovascular risk and address the antihypertensive therapy.

Screening System for Cardiac Problems through Non-Invasive Identification of Blood Pressure Waveform

This paper presents the initial development of a non-invasive system for identification of the pulse pressure waveform to be used for screening cardiac problems. The system employs a tonometric method using an off-the-shelf force sensor and custom-designed electronic circuits. Initial results on the use of the system are presented.

Impact of hemodialysis on cardiovascular system assessed by pulse wave analysis

Valuable information about cardiovascular system can be derived from the shape of aortic pulse wave being the result of reciprocal interaction between heart and vasculature. Pressure profiles in ascending aorta were obtained from peripheral waveforms recorded non-invasively (SphygmoCor, AtCor Medical, Australia) before, during and after hemodialysis sessions performed after 3-day and 2-day interdialytic intervals in 35 anuric, prevalent hemodialysis patients. Fluid status was assessed by Body Composition Monitor (Fresenius Medical Care, Bad Homburg, Germany) and online hematocrit monitoring device (CritLine, HemaMetrics, Utah). Systolic pressure and ejection duration decreased during dialysis. Augmentation index remained stable at 30 ± 13% throughout hemodialysis session despite the decrease of augmented pressure and pulse height. Subendocardial viability ratio (SEVR) determined after 3-day and 2-day interdialytic intervals increased during the sessions by 43.8 ± 26.6% and 26.1 ± 25.4%, respectively. Hemodialysis performed after 3-day and 2-day interdialytic periods reduced significantly overhydration by 2.4 ± 1.0 L and 1.8 ± 1.2 L and blood volume by 16.3 ± 9.7% and 13.7 ± 8.9%, respectively. Intradialytic increase of SEVR correlated with ultrafiltration rate (R = 0.39, p-value < 0.01), reduction in overhydration (R = -0.57, p-value < 0.001) and blood volume drop (R = -0.38, p-value < 0.01). The strong correlation between the decrease of overhydration during hemodialysis and increase in SEVR confirmed that careful fluid management is crucial for proper cardiac function. Hemodialysis affected cardiovascular system with the parameters derived from pulse-wave-analysis (systolic and augmented pressures, pulse height, ejection duration, SEVR) being significantly different at the end of dialysis from those before the session. Combination of pulse-wave-analysis with the monitoring of overhydration provides a new insight into the impact of hemodialysis on cardiovascular system.

Patient-specific pulse wave propagation model identifies cardiovascular risk characteristics in hemodialysis patients

Risk of cardiovascular associated death in dialysis patients is the highest among all other co-morbidities. Improving the identification of patients with the highest cardiovascular risk to design an adequate treatment is, therefore, of utmost importance. There are several non-invasive cardiovascular state biomarkers based on the pulse (pressure) wave propagation properties, but their major determinants are not fully understood. In the current study we aimed to provide a framework to precisely dissect the information available in non-invasively recorded pulse wave in hemodialysis patients. Radial pressure wave profiles were recorded before, during and after two independent hemodialysis sessions in 35 anuric prevalent hemodialysis patients and once in a group of 32 healthy volunteers. Each recording was used to estimate six subject-specific parameters of pulse wave propagation model. Pressure profiles were also analyzed using SphygmoCor software (AtCor Medical, Australia) to derive values of already established biomarkers, i.e. augmentation index and sub-endocardial viability ratio (SEVR). Data preprocessing using propensity score matching allowed to compare hemodialysis and healthy groups. Augmentation index remained on average stable at 142 ± 28% during dialysis and had similar values in both considered groups. SEVR, whose pre-dialytic value was on average lower by 12% compared to healthy participants, was improved by hemodialysis, with post-dialytic values indistinguishable from those in healthy population (p-value > 0.2). The model, however, identified that the patients on hemodialysis had significantly increased stiffness of both large and small arteries compared to healthy counterparts (> 60% before dialysis with p-value < 0.05 or borderline) and that it was only transiently decreased during hemodialysis session. Additionally, correlation-based clustering revealed that augmentation index reflects the shape of heart ejection profile and SEVR is associated with stiffness of larger arteries. Patient-specific pulse wave propagation modeling coupled with radial pressure profile recording correctly identified increased arterial stiffness in hemodialysis patients, while regular pulse wave analysis based biomarkers failed to show significant differences. Further model testing in larger populations and investigating other biomarkers are needed to confirm these findings.

There are more than 2 million people receiving hemodialysis (HD) treatment worldwide. Cardiovascular disease is the most common cause of death in those patients. There are several non-invasive methods to assess if a person from general population has a high risk for developing cardiovascular disease, but it is unclear whether they are useful in hemodialysis patients. Here we assessed the ability of patient-specific pulse wave propagation modeling to correctly identify high cardiovascular risk factors in hemodialysis patients. We performed pulse wave analysis (PWA) in patients on hemodialysis and in healthy subjects. Recorded peripheral pressure profiles were simultaneously used to inform subject-specific mathematical model of pulse wave propagation. We found that standard PWA-derived biomarkers failed to clearly show the differences between hemodialysis patients and healthy subjects. However, proposed mathematical model of pulse wave propagation identified significantly increased arterial stiffness in HD patients and provided also the major determinants of PWA-derived biomarkers. Our study suggests that current pulse wave analysis based biomarkers can be insufficient to accurately diagnose hemodialysis patients. Proposed patient-specific pulse wave propagation modeling framework may be a new tool to assess the cardiovascular risk in both general and hemodialysis populations.