Beyond blood pressure: pulse wave analysis – a better way of assessing cardiovascular risk?

Estimation of pulse wave analysis indices from invasive arterial blood pressure only for a clinical assessment of wave reflection in a 5-day septic animal experiment

Wave separation analysis (WSA) is the gold standard to analyze the arterial blood pressure (ABP) waveform, decomposing it into a forward and a reflected wave. It requires ABP and arterial blood flow (ABF) measurement, and ABF is often unavailable in clinical settings. Therefore, methods to estimate ABF from ABP have been proposed, but they are not investigated in critical conditions. In this work, an autoregressive with exogenous input model was proposed as an original method to estimate ABF from the measured ABP. Its performance in assessing WSA indices to characterize the arterial tree was evaluated in critical conditions, i.e., during sepsis. The triangular and the personalized flow approximation and the multi-Gaussian ABP decomposition were compared to the proposed model. The results highlighted how the black-box modeling approach is superior to other flow estimation models when computing WSA indices in septic condition. This approach holds promise for overcoming challenges in clinical settings where ABF data are unavailable.

The role of pulse wave analysis indexes for critically ill patients: a narrative review

Objective.Arterial pulse wave analysis (PWA) is now established as a powerful tool to investigate the cardiovascular system, and several clinical studies have shown how PWA can provide valuable prognostic information over and beyond traditional cardiovascular risk factors. Typically these techniques are applied to chronic conditions, such as hypertension or aging, to monitor the slow structural changes of the vascular system which lead to important alterations of the arterial PW. However, their application to acute critical illness is not currently widespread, probably because of the high hemodynamic instability and acute dynamic alterations affecting the cardiovascular system of these patients.Approach.In this work we propose a review of the physiological and methodological basis of PWA, describing how it can be used to provide insights into arterial structure and function, cardiovascular biomechanical properties, and to derive information on wave propagation and reflection.Main results.The applicability of these techniques to acute critical illness, especially septic shock, is extensively discussed, highlighting the feasibility of their use in acute critical patients and their role in optimizing therapy administration and hemodynamic monitoring.Significance.The potential for the clinical use of these techniques lies in the ease of computation and availability of arterial blood pressure signals, as invasive arterial lines are commonly used in these patients. We hope that the concepts illustrated in the present review will soon be translated into clinical practice.

Wave Separation Analysis to Assess Cardiovascular Alterations Induced by Sepsis

OBJECTIVE

Sepsis induces a severe decompensation of arterial and cardiac functional properties, leading to important modifications of arterial blood pressure (ABP) waveform, not resolved by recommended therapy, as shown by previous works. The aim of this study is to quantify the changes in ABP waveform morphology and wave reflections during a long-term swine experiment of polymicrobial sepsis and resuscitation, to deepen the understanding of the cardiovascular response to standard resuscitation therapy.

METHODS

We analyzed 14 pigs: polymicrobial sepsis was induced in 9 pigs followed by standard resuscitation and 5 pigs were treated as sham controls. Septic animals were studied at baseline (T1), after sepsis development (T2), and after 24 h (T3) and 48 h (T4) of therapy administration, and sham controls at the same time points. ABP and arterial blood flow were measured in the left and right carotid artery, respectively. Pulse wave analysis and wave separation techniques were used to estimate arterial input impedance, carotid characteristic impedance, forward and backward waves, indices of wave reflections such as reflection magnitude and reflection index, and augmentation index.

RESULTS

Sepsis led to an acute alteration of ABP waveform passing from type A to type B or C; consistently, the reflection phenomena were significantly reduced. The resuscitation was successful in reaching targeted hemodynamic stability, but it failed in restoring a physiological blood propagation and reflection.

CONCLUSION

Septic pigs persistently showed altered reflected waves even after 48 hours of successful therapy according to guidelines, suggesting a persistent hidden cardiovascular disorder.

SIGNIFICANCE

The proposed indices may be useful to unravel the complex cardiovascular response to therapy administration in septic patients and could potentially be used for risk stratification of patient deterioration. Whether alterations of blood propagation and reflection contribute to persisting organ dysfunction after hemodynamic stabilization should be further investigated.

Sex-specific cardiovascular risk factors in the UK Biobank

The lack of sex-specific cardiovascular disease criteria contributes to the underdiagnosis of women compared to that of men. For more than half a century, the Framingham Risk Score has been the gold standard to estimate an individual's risk of developing cardiovascular disease based on the age, sex, cholesterol levels, blood pressure, diabetes status, and the smoking status. Now, machine learning can offer a much more nuanced insight into predicting the risk of cardiovascular diseases. The UK Biobank is a large database that includes traditional risk factors and tests related to the cardiovascular system: magnetic resonance imaging, pulse wave analysis, electrocardiograms, and carotid ultrasounds. Here, we leverage 20,542 datasets from the UK Biobank to build more accurate cardiovascular risk models than the Framingham Risk Score and quantify the underdiagnosis of women compared to that of men. Strikingly, for a first-degree atrioventricular block and dilated cardiomyopathy, two conditions with non-sex-specific diagnostic criteria, our study shows that women are under-diagnosed 2× and 1.4× more than men. Similarly, our results demonstrate the need for sex-specific criteria in essential primary hypertension and hypertrophic cardiomyopathy. Our feature importance analysis reveals that out of the top 10 features across three sexes and four disease categories, traditional Framingham factors made up between 40% and 50%; electrocardiogram, 30%-33%; pulse wave analysis, 13%-23%; and magnetic resonance imaging and carotid ultrasound, 0%-10%. Improving the Framingham Risk Score by leveraging big data and machine learning allows us to incorporate a wider range of biomedical data and prediction features, enhance personalization and accuracy, and continuously integrate new data and knowledge, with the ultimate goal to improve accurate prediction, early detection, and early intervention in cardiovascular disease management. Our analysis pipeline and trained classifiers are freely available at https://github.com/LivingMatterLab/CardiovascularDiseaseClassification.

Acute inflammation elicits decreased blood pressure but similar arterial stiffness in young African American adults

African Americans (AA) have a higher risk for cardiovascular disease (CVD) as compared to their White (W) counterparts. CVD is characterized by increased blood pressure (BP), arterial stiffness and systemic inflammation. An acute inflammatory stimulus may explain physiological manifestations responsible for amplified CVD in AA that are not apparent at rest. The purpose of this study was to evaluate central and peripheral BP, central and local arterial stiffness, and indices of pulse wave morphology in young healthy AA and W participants in response to acute inflammation. Concentrations of the inflammatory cytokine interleukin-6 (IL-6) and measures of central and peripheral BP, central arterial stiffness (carotid-femoral pulse wave velocity (cfPWV)), local carotid arterial stiffness (β-stiffness, elastic modulus (Ep)), and indices of pulse wave morphology were assessed in 28 participants (21 ± 2 years, AA: n = 11) at baseline (BL), 24 h and 48 h post-inflammation. Changes in IL-6 concentrations (ΔIL-6) were significantly greater at 24 h as compared to 48 h post-inflammation (0.652 ± 0.644 vs. -0.146 ± 0.532 pg/μl, P ≤ 0.0001). Among AA participants, central and peripheral diastolic BP were significantly decreased at 24 h post-inflammation as compared to BL (aortic diastolic BP: -4 ± 4 mmHg, P = 0.016; brachial diastolic BP: -4 ± 4 mmHg, P = 0.014). AA participants also experienced a significant decrease in central and peripheral mean arterial BP at 48 h post-inflammation as compared to BL (aortic mean arterial pressure: -4 ± 4 mmHg, P = 0.009; brachial mean arterial pressure: -4 ± 4 mmHg, P = 0.012). Despite haemodynamic changes, there were no differences in central or local carotid arterial stiffness or indices of pulse wave morphology.

Comparing Remote Speckle Plethysmography and Finger-Clip Photoplethysmography with Non-Invasive Finger Arterial Pressure Pulse Waves, Regarding Morphology and Arrival Time

OBJECTIVE

The goal was to compare Speckle plethysmography (SPG) and Photoplethysmography (PPG) with non-invasive finger Arterial Pressure (fiAP) regarding Pulse Wave Morphology (PWM) and Pulse Arrival Time (PAT).

METHODS

Healthy volunteers (n = 8) were connected to a Non-Invasive Blood Pressure (NIBP) monitor providing fiAP pulse wave and PPG from a clinical transmission-mode SpO₂ finger clip. Biopac recorded 3-lead ECG. A camera placed at a 25 cm distance recorded a video stream (100 fps) of a finger illuminated by a laser diode at 639 nm. A chest belt (Polar) monitored respiration. All signals were recorded simultaneously during episodes of spontaneous breathing and paced breathing.

ANALYSIS

Post-processing was performed in Matlab to obtain SPG and analyze the SPG, PPG and fiAP mean absolute deviations (MADs) on PWM, plus PAT modulation.

RESULTS

Across 2599 beats, the average fiAP MAD with PPG was 0.17 (0-1) and with SPG 0.09 (0-1). PAT derived from ECG-fiAP correlated as follows: 0.65 for ECG-SPG and 0.67 for ECG-PPG.

CONCLUSION

Compared to the clinical NIBP monitor fiAP reference, PWM from an experimental camera-derived non-contact reflective-mode SPG setup resembled fiAP significantly better than PPG from a simultaneously recorded clinical transmission-mode finger clip. For PAT values, no significant difference was found between ECG-SPG and ECG-PPG compared to ECG-fiAP.

Discrimination between possible sarcopenia and metabolic syndrome using the arterial pulse spectrum and machine-learning analysis

Sarcopenia is defined as decreased skeletal muscle mass and function, and is an important cause of frailty in the elderly, also being associated with vascular lesions and poor microcirculation. The present study aimed to combine noninvasive pulse measurements, frequency-domain analysis, and machine learning (ML) analysis (1) to determine the effects on the pulse waveform induced by sarcopenia and (2) to develop discriminating models for patients with possible sarcopenia. Radial blood pressure waveform (BPW) signals were measured noninvasively for 1 min in 133 subjects who visited Tri-Service General Hospital for geriatric health checkups. They were assigned to a robust group and a possible-sarcopenia group that combined dynapenia, presarcopenia, and sarcopenia. Two classification methods were used: ML analysis and a self-developed scoring system that used 40 harmonic pulse indices as features: amplitude proportions and their coefficients of variation, and phase angles and their standard deviations. Significant differences were found in several spectral indices of the BPW between possible-sarcopenia and robust subjects. Threefold cross-validation results indicated excellent discrimination performance, with AUC equaling 0.77 when using LDA and 0.83 when using our scoring system. The present noninvasive and easy-to-use measurement and analysis method for detecting sarcopenia-induced changes in the arterial pulse transmission condition could aid the discrimination of possible sarcopenia.

Machine-Learning Classification of Pulse Waveform Quality

Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin-sensor contact pressure is insufficient. An alternative approach is to extract only high-quality pulses for use in index calculations. The present study aimed to determine the effectiveness of using machine-learning analysis in discriminating between high-quality and low-quality pulse waveforms induced by applying different contact pressures. Radial blood pressure waveform (BPW) signals were measured noninvasively in healthy young subjects using a strain-gauge transducer. One-minute-long trains of pulse data were measured when applying the appropriate contact pressure (67.80 ± 1.55 mmHg) and a higher contact pressure (151.80 ± 3.19 mmHg). Eight machine-learning algorithms were employed to evaluate the following 40 harmonic pulse indices: amplitude proportions and their coefficients of variation and phase angles and their standard deviations. Significant differences were noted in BPW indices between applying appropriate and higher skin-surface contact pressures. The present appropriate contact pressure could not only provide a suitable holding force for the wearable device but also helped to maintain the physiological stability of the underlying tissues. Machine-learning analysis provides an effective method for distinguishing between the high-quality and low-quality pulses with excellent discrimination performance (leave-one-subject-out test: random-forest AUC = 0.96). This approach will aid the development of an automatic screening method for waveform quality and thereby improve the noninvasive acquisition reliability. Other possible interfering factors in practical applications can also be systematically studied using a similar procedure.

Mechanical Sensors for Cardiovascular Monitoring: From Battery-Powered to Self-Powered

Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect abnormalities and conduct early intervention in time. To this end, the development of flexible wearable/implantable sensors for real-time monitoring of various vital signs has aroused extensive interest among researchers. Among the different kinds of sensors, mechanical sensors can reflect the direct information of pressure fluctuations in the cardiovascular system with the advantages of high sensitivity and suitable flexibility. Herein, we first introduce the recent advances of four kinds of mechanical sensors for cardiovascular system monitoring, based on capacitive, piezoresistive, piezoelectric, and triboelectric principles. Then, the physio-mechanical mechanisms in the cardiovascular system and their monitoring are described, including pulse wave, blood pressure, heart rhythm, endocardial pressure, etc. Finally, we emphasize the importance of real-time physiological monitoring in the treatment of cardiovascular disease and discuss its challenges in clinical translation.

Spatiotemporal Measurement of Arterial Pulse Waves Enabled by Wearable Active-Matrix Pressure Sensor Arrays

Wearable pressure sensors have demonstrated great potential in detecting pulse pressure waves on the skin for the noninvasive and continuous diagnosis of cardiac conditions. However, difficulties lie in positioning conventional single-point sensors on an invisible arterial line, thereby preventing the detection of adequate signal amplitude for accurate pulse wave analysis. Herein, we introduce the spatiotemporal measurements of arterial pulse waves using wearable active-matrix pressure sensors to obtain optimal pulse waveforms. We fabricate thin-film transistor (TFT) arrays with high yield and uniformity using inkjet printing where array sizes can be customizable and integrate them with highly sensitive piezoresistive sheets. We maximize the pressure sensitivity (16.8 kPa^-1) and achieve low power consumption (10¹ nW) simultaneously by strategically modulating the TFT operation voltage. The sensor array creates a spatiotemporal pulse wave map on the wrist. The map presents the positional dependence of pulse amplitudes, which allows the positioning of the arterial line to accurately extract the augmentation index, a parameter for assessing arterial stiffness. The device overcomes the positional inaccuracy of conventional single-point sensors, and therefore, it can be used for medical applications such as arterial catheter injection or the diagnosis of cardiovascular disease in daily life.

Classification of patients with Alzheimer's disease using the arterial pulse spectrum and a multilayer-perceptron analysis

Cerebrovascular atherosclerosis has been identified as a prominent pathological feature of Alzheimer's disease (AD); the link between vessel pathology and AD risk may also extend to extracranial arteries. This study aimed to determine the effectiveness of using arterial pulse-wave measurements and multilayer perceptron (MLP) analysis in distinguishing between AD and control subjects. Radial blood pressure waveform (BPW) and finger photoplethysmography signals were measured noninvasively for 3 min in 87 AD patients and 74 control subjects. The 5-layer MLP algorithm employed evaluated the following 40 harmonic pulse indices: amplitude proportion and its coefficient of variation, and phase angle and its standard deviation. The BPW indices differed significantly between the AD patients (6247 pulses) and control subjects (6626 pulses). Significant intergroup differences were found between mild, moderate, and severe AD (defined by Mini-Mental-State-Examination scores). The hold-out test results indicated an accuracy of 82.86%, a specificity of 92.31%, and a 0.83 AUC of ROC curve when using the MLP-based classification between AD and Control. The identified differences can be partly attributed to AD-induced changes in vascular elastic properties. The present findings may be meaningful in facilitating the development of a noninvasive, rapid, inexpensive, and objective method for detecting and monitoring the AD status.

Kouzani A, Mosadegh B, Gharaie S. Blood Pressure Sensors: Materials, Fabrication Methods, Performance Evaluations and Future Perspectives

Advancements in materials science and fabrication techniques have contributed to the significant growing attention to a wide variety of sensors for digital healthcare. While the progress in this area is tremendously impressive, few wearable sensors with the capability of real-time blood pressure monitoring are approved for clinical use. One of the key obstacles in the further development of wearable sensors for medical applications is the lack of comprehensive technical evaluation of sensor materials against the expected clinical performance. Here, we present an extensive review and critical analysis of various materials applied in the design and fabrication of wearable sensors. In our unique transdisciplinary approach, we studied the fundamentals of blood pressure and examined its measuring modalities while focusing on their clinical use and sensing principles to identify material functionalities. Then, we carefully reviewed various categories of functional materials utilized in sensor building blocks allowing for comparative analysis of the performance of a wide range of materials throughout the sensor operational-life cycle. Not only this provides essential data to enhance the materials' properties and optimize their performance, but also, it highlights new perspectives and provides suggestions to develop the next generation pressure sensors for clinical use.

Associations of Reservoir-Excess Pressure Parameters Derived From Central and Peripheral Arteries With Kidney Function

BACKGROUND

Central artery reservoir-excess pressure parameters are clinically important but impractical to record directly. However, diastolic waveform morphology is consistent across central and peripheral arteries. Therefore, peripheral artery reservoir-excess pressure parameters related to diastolic waveform morphology may be representative of central parameters and share clinically important associations with end-organ damage. This has never been determined and was the aim of this study.

METHODS

Intra-arterial blood pressure (BP) waveforms were measured sequentially at the aorta, brachial, and radial arteries among 220 individuals (aged 61 ± 10 years, 68% male). Customized software was used to derive reservoir-excess pressure parameters at each arterial site (reservoir and excess pressure, systolic and diastolic rate constants) and clinical relevance was determined by association with estimated glomerular filtration rate (eGFR).

RESULTS

Between the aorta and brachial artery, the mean difference in the diastolic rate constant and reservoir pressure integral was -0.162 S-1 (P = 0.08) and -0.772 mm Hg s (P = 0.23), respectively. The diastolic rate constant had the strongest and most consistent associations with eGFR across aortic and brachial sites (β = -0.20, P = 0.02; β = -0.20, P = 0.03, respectively; adjusted for traditional cardiovascular risk factors). Aortic, but not brachial peak reservoir pressure was associated with eGFR in adjusted models (aortic β = -0.48, P = 0.02).

CONCLUSIONS

The diastolic rate constant is the most consistent reservoir-excess pressure parameter, in both its absolute values and associations with kidney dysfunction, when derived from the aorta and brachial artery. Thus, the diastolic rate constant could be utilized in the clinical setting to improve BP risk stratification.

Hemodynamic changes caused by acupuncture in healthy volunteers: a prospective, single-arm exploratory clinical study

BACKGROUND

Radial pressure pulse wave (RPPW) examination has been a key diagnostic component of traditional Chinese medicine. The objective of this study was to investigate the changes in RPPW along with various hemodynamic variables after acupuncture stimulation and to examine the validity of pulse diagnosis as a modern diagnostic tool.

METHODS

We conducted acupuncture stimulation at both ST36 acupuncture points in 25 healthy volunteers. We simultaneously assessed the RPPW by pulse tonometry; heart rate variability (HRV) by electrocardiogram; photoplethysmogram (PPG) signals, respiration rate, peripheral blood flow velocity and arterial depth by ultrasonography; and cardiac output by impedance cardiography, before, during and after a session of acupuncture stimulation.

RESULTS

We observed consistent patterns of increased spectral energy at low frequency (<10 Hz) and pulse power using RPPW examination and in the amplitude and systolic area of the PPG signal during the entire acupuncture session. The low- and high-frequency domains of HRV increased and decreased, respectively, during the acupuncture session. The peripheral blood velocity rose shortly after needle insertion, reached a maximum in the middle of the session and decreased afterwards. The augmentation index (AIX) and pulse transit time (PTT) obtained from RPPW did not change significantly.

CONCLUSION

Acupuncture stimulation at ST36 in healthy subjects increased the peripheral pulse amplitudes (pressure pulse wave (PPW) and PPG), blood flow velocity (ultrasonography) and sympathetic nerve activity (HRV). The lack of changes in the AIX and PTT suggests that the increased pulse amplitudes and blood flow velocity may result from increased cardiac output.

TRIAL REGISTRATION

Clinical Research Information Service ( KCT0001663 ).

[Evaluation of vascular function by modern non-invasive methods]

Vascular functional alterations frequently precede morphological changes and, therefore, their recognition may theoretically improve early detection of vascular injury. The aim of this review is to demonstrate recently available non-invasive clinical methods including vascular stiffness examinations, flow-mediated vasodilatation, coronary flow reserve and myocardial flow reserve measurements.

Evaluation of pulse rate variability obtained by the pulse onsets of the photoplethysmographic signal

This work presents the evaluation of pulse rate variability (PRV) obtained from pulse onsets of photoplethysmographic (PPG) signals. Three published algorithms were used to determine the pulse onsets: diastolic point, maximum second derivative and tangent intersection. Temporal series of pulse onsets were obtained for each method, and several variability indices were derived from these series. Simultaneous ECG and PPG records were acquired from 37 healthy volunteers to evaluate the interchangeability between PRV indices and heart rate variability (HRV) indices by the Bland-Altman method. Furthermore, the concordance correlation coefficient was used to correlate the indices. In all the cases, PRV indices obtained through the tangent intersection method showed better accuracy and precision (Bland-Altman analysis, bias ± 1.96 standard deviation: low frequency, LF(ms)(2) = -28.06 ± 72.68; high frequency, HF(ms)(2) = -68.23 ± 192.85; high frequency in normalized units, HF(nu) =-2.02 ± 7.08; LF/HF = 0.17 ± 0.71) and higher correlation (concordance correlation coefficients: low frequency, LF(ms)(2) = 0.99; high frequency, HF(ms)(2) = 0.98; high frequency in normalized units, HF(nu) = 0.97; LF/HF = 0.90) with HRV indices than other methods, and could be used as a good surrogate of HRV.