Examining the challenges of blood pressure estimation via photoplethysmogram.

The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such technology can have a significant impact on health screening, chronic disease management and remote monitoring. A common approach is to collect sensor data and corresponding labels from a clinical grade device (e.g., blood pressure cuff) and train deep learning models to map one to the other. Although well intentioned, this approach often ignores a principled analysis of whether the input sensor data have enough information to predict the desired metric. We analyze the task of predicting blood pressure from PPG pulse wave analysis. Our review of the prior work reveals that many papers fall prey to data leakage and unrealistic constraints on the task and preprocessing steps. We propose a set of tools to help determine if the input signal in question (e.g., PPG) is indeed a good predictor of the desired label (e.g., blood pressure). Using our proposed tools, we found that blood pressure prediction using PPG has a high multi-valued mapping factor of 33.2% and low mutual information of 9.8%. In comparison, heart rate prediction using PPG, a well-established task, has a very low multi-valued mapping factor of 0.75% and high mutual information of 87.7%. We argue that these results provide a more realistic representation of the current progress toward the goal of wearable blood pressure measurement via PPG pulse wave analysis. For code, see our project page: https://github.com/lirus7/PPG-BP-Analysis.

The Impact of Cardiopulmonary Rehabilitation on Ventriculoarterial Coupling in Post-Coronavirus Disease-2019 Patients.

PURPOSE: Coronavirus disease-2019 (COVID-19) affects the cardiovascular system even after the acute phase of the disease. Cardiopulmonary rehabilitation may improve post-COVID-19 symptoms. This study aims to evaluate the impact of a cardiopulmonary rehabilitation program after acute COVID-19 on arterial stiffness, left ventricular function, and ventriculoarterial coupling (VAC). METHODS: Forty-eight adults were examined 1 (T0) and 3-mo (T1) following recovery from COVID-19 and randomized 1:1 to participate or not in a 3-mo rehabilitation program. Matched subjects were enrolled as a non-COVID-19 group. Arterial stiffness was evaluated by carotid-femoral pulse wave velocity (PWV). Left ventricular (LV) systolic performance was evaluated with global longitudinal strain (GLS). The PWV/LV-GLS ratio was calculated as an index of VAC. High-sensitivity C reactive protein (hs-CRP) was measured. RESULTS: At T0, convalescent patients with COVID-19 had impaired PWV ( P = .001) and reduced VAC ( P = .001) compared to non-COVID-19 subjects. PWV (8.15 ± 1.37 to 6.55 ± 0.98 m/sec, P < .001) and LV-GLS (-19.67 ± 1.98 to -21.3 ± 1.93%, P < .001) improved only in convalescent patients with COVID-19 undergoing rehabilitation. Similarly, VAC was only improved in the rehabilitation group (-0.42 ± 0.11 to -0.31 ± 0.06 m · sec -1  ·% -1 , P < .001). A significant improvement in VO 2max was noted after rehabilitation (15.70 [13.05, 21.45] to 18.30 [13.95, 23.75] ml · kg -1  · min -1 , P = .01). Finally, hs-CRP was improved in both groups with a significantly greater improvement in the rehabilitation group. CONCLUSION: A 3-mo rehabilitation program in convalesced patients with COVID-19 enhances the recovery of arterial stiffness, left ventricular function, and VAC, highlighting the beneficial mechanisms of rehabilitation in this patient population.

Deep Learning-Based Vascular Aging Prediction From Retinal Fundus Images.

Purpose: The purpose of this study was to establish and validate a deep learning model to screen vascular aging using retinal fundus images. Although vascular aging is considered a novel cardiovascular risk factor, the assessment methods are currently limited and often only available in developed regions. Methods: We used 8865 retinal fundus images and clinical parameters of 4376 patients from two independent datasets for training a deep learning algorithm. The gold standard for vascular aging was defined as a pulse wave velocity ≥1400 cm/s. The probability of the presence of vascular aging was defined as deep learning retinal vascular aging score, the Reti-aging score. We compared the performance of the deep learning model and clinical parameters by calculating the area under the receiver operating characteristics curve (AUC). We recruited clinical specialists, including ophthalmologists and geriatricians, to assess vascular aging in patients using retinal fundus images, aiming to compare the diagnostic performance between deep learning models and clinical specialists. Finally, the potential of Reti-aging score for identifying new-onset hypertension (NH) and new-onset carotid artery plaque (NCP) in the subsequent three years was examined. Results: The Reti-aging score model achieved an AUC of 0.826 (95% confidence interval [CI] = 0.793-0.855) and 0.779 (95% CI = 0.765-0.794) in the internal and external dataset. It showed better performance in predicting vascular aging compared with the prediction with clinical parameters. The average accuracy of ophthalmologists (66.3%) was lower than that of the Reti-aging score model, whereas geriatricians were unable to make predictions based on retinal fundus images. The Reti-aging score was associated with the risk of NH and NCP (P < 0.05). Conclusions: The Reti-aging score model might serve as a novel method to predict vascular aging through analysis of retinal fundus images. Reti-aging score provides a novel indicator to predict new-onset cardiovascular diseases. Translational Relevance: Given the robust performance of our model, it provides a new and reliable method for screening vascular aging, especially in undeveloped areas.

Temporal Convolutional Neural Network-Based Prediction of Vascular Health in Elderly Women Using Photoplethysmography-Derived Pulse Wave during Exercise.

(1) Background: The objective of this study was to predict the vascular health status of elderly women during exercise using pulse wave data and Temporal Convolutional Neural Networks (TCN); (2) Methods: A total of 492 healthy elderly women aged 60-75 years were recruited for the study. The study utilized a cross-sectional design. Vascular endothelial function was assessed non-invasively using Flow-Mediated Dilation (FMD). Pulse wave characteristics were quantified using photoplethysmography (PPG) sensors, and motion-induced noise in the PPG signals was mitigated through the application of a recursive least squares (RLS) adaptive filtering algorithm. A fixed-load cycling exercise protocol was employed. A TCN was constructed to classify flow-mediated dilation (FMD) into "optimal", "impaired", and "at risk" levels; (3) Results: TCN achieved an average accuracy of 79.3%, 84.8%, and 83.2% in predicting FMD at the "optimal", "impaired", and "at risk" levels, respectively. The results of the analysis of variance (ANOVA) comparison demonstrated that the accuracy of the TCN in predicting FMD at the impaired and at-risk levels was significantly higher than that of Long Short-Term Memory (LSTM) networks and Random Forest algorithms; (4) Conclusions: The use of pulse wave data during exercise combined with the TCN for predicting the vascular health status of elderly women demonstrated high accuracy, particularly in predicting impaired and at-risk FMD levels. This indicates that the integration of exercise pulse wave data with TCN can serve as an effective tool for the assessment and monitoring of the vascular health of elderly women.

Do Photopletysmographic Parameters of Arterial Stiffness Differ Depending on the Presence of Arterial Hypertension and/or Atherosclerosis?

BACKGROUND: Hypertension and atherosclerotic cardiovascular diseases (ASCVD) increase cardiovascular risk and worsen patients' prognoses. One early predictor of increased risk is a change in arterial stiffness. This study aimed to evaluate arterial stiffness parameters using the non-invasive photoplethysmography (PPG) method in Polish patients with arterial hypertension (AH) and/or atherosclerosis (AS). METHODS: The study group consisted of 333 patients (Caucasians, both sexes, aged 30-85 years old). Patients were analyzed in four groups depending on AH and AS (Group I: patients without AH or AS, Group II: AH patients, Group III: AS patients, and Group IV: AH/AS patients) and, in addition, according to sex and history of SARS-CoV-2 infection. Arterial stiffness parameters, i.e., reflection index (RI), peak-to-peak time (PPT), and stiffness index (SI) were automatically calculated with PPG based on the analysis of the pulse wave contour. RESULTS: Mean values of RI and SI were higher in men than women (p < 0.001 each). Diastolic blood pressure (DBP) also differed between sexes (p = 0.010). Mean SI values differed between the study groups (p = 0.038) with the highest SI found in AS/AH patients and the lowest-in patients without AH or AS. The mean SI values were significantly lower in women compared to men in both Group I and Group II (p = 0.006 and p < 0.001, respectively). The mean values of RI were also greater in men than in women in Group I and Group II (p < 0.001 for each group). Regarding COVID-19 history, only HR values differed between patients with and without COVID-19 in AH patients (p = 0.012). In AH patients, men had higher values of RI and SI compared to women (p < 0.001 and p < 0.001). On the other hand, AS women with COVID-19 had significantly greater mean values of SI (9.66 m/s ± 1.61) than men with COVID-19 (7.98 m/s ± 1.09) (p = 0.045). CONCLUSIONS: The present study confirmed that sex had a significant impact on arterial stiffness parameters. Both AH and AS affected arterial stiffness. Heart rate was greater in hypertensive patients after COVID-19 compared to hypertensive patients without COVID-19.

Aortic Stiffness Is Associated With Higher Nighttime Ambulatory Blood Pressure in Middle-Aged and Older Adults.

PURPOSE: The objective of this study was to determine the relationship between aortic stiffening and brachial and central ambulatory blood pressure (AMBP) in a nonclinical sample of middle-aged and older adults (MA/O). We hypothesized aortic stiffness would be positively associated with 24-hr, daytime, and nighttime brachial and central AMBP. METHODS: Fifty-one participants aged ≥50 yr (21 males and 30 females, mean age 63.4 ± 9.0 yr) with a body mass index <35 kg/m 2 who also had a resting brachial blood pressure (BP) <160/100 mmHg with or without BP medications were recruited for this cross-sectional analysis. All participants underwent measures of aortic stiffness (carotid-femoral pulse wave velocity [cfPWV]) and 24-hr AMBP monitoring. Bivariate correlations assessed the relationship between cfPWV, brachial, and central AMBP. Partial correlations were used to independently adjust for traditional cardiovascular disease (CVD) risk factors including age, sex, waist circumference, glucose, and augmentation index normalized to heart rate 75 bpm, a surrogate measure of arterial stiffness, and in a multivariable combined model. RESULTS: Nighttime brachial systolic BP ( r = 0.31) and central systolic BP ( r = 0.30) were correlated with cfPWV in the multivariable combined model ( P ≤ .05). Nighttime brachial pulse pressure and central pulse pressure were correlated with cfPWV after independently adjusting for all CVD risk factors ( P ≤ .05, all) but not when combined in the multivariable model ( P > .05). CONCLUSIONS: Higher nighttime brachial and central AMBP with older age are related, in part, to greater aortic stiffening. Therefore, interventions to lower or prevent aortic stiffening may also lower nighttime BP in MA/O adults to lower CVD risk.

Serum Endocan Is a Risk Factor for Aortic Stiffness in Patients Undergoing Maintenance Hemodialysis.

Background and Objectives: Endocan, secreted from the activated endothelium, is a key player in inflammation, endothelial dysfunction, proliferation of vascular smooth muscle cells, and angiogenesis. We aimed to investigate the link between endocan and aortic stiffness in maintenance hemodialysis (HD) patients. Materials and Methods: After recruiting HD patients from a medical center, their baseline characteristics, blood sample, and anthropometry were assessed and recorded. The serum endocan level was determined using an enzyme immunoassay kit, and carotid-femoral pulse wave velocity (cfPWV) measurement was used to evaluate aortic stiffness. Results: A total of 122 HD patients were enrolled. Aortic stiffness was diagnosed in 53 patients (43.4%), who were found to be older (p = 0.007) and have a higher prevalence of diabetes (p < 0.001) and hypertension (p = 0.030), higher systolic blood pressure (p = 0.011), and higher endocan levels (p < 0.001), when compared with their counterparts. On the multivariate logistic regression model, the development of aortic stiffness in patients on chronic HD was found to be associated with endocan [odds ratio (OR): 1.566, 95% confidence interval (CI): 1.224-2.002, p < 0.001], age (OR: 1.040, 95% CI: 1.001-1.080, p = 0.045), and diabetes (OR: 4.067, 95% CI: 1.532-10.798, p = 0.005), after proper adjustment for confounders (adopting diabetes, hypertension, age, systolic blood pressure, and endocan). The area under the receiver operating characteristic curve was 0.713 (95% CI: 0.620-0.806, p < 0.001) for predicting aortic stiffness by the serum endocan level, at an optimal cutoff value of 2.68 ng/mL (64.15% sensitivity, 69.57% specificity). Upon multivariate linear regression analysis, logarithmically transformed endocan was proven as an independent predictor of cfPWV (ß = 0.405, adjusted R2 change = 0.152; p < 0.001). Conclusions: The serum endocan level positively correlated with cfPWV and was an independent predictor of aortic stiffness in chronic HD patients.

Arteriovenous Oscillometric Plethysmography for Fistula Functional Testing.

INTRODUCTION: The aim of the presented prospective observational study was to evaluate the effect of fistula flow on peripheral wave morphology and pulse wave velocity by means of the oscillometric Vicorder®-device with the purpose of fistula surveillance. METHODS: Digitized and normalized curves of 53 haemodialysis patients at the fistula and non-fistula arm were analysed. Slope parameters and the areas under the curve of characteristic sections of pulse waves as well as the power spectrum of the pulse waves and their first and second derivatives were computed. Furthermore, the amplitude of volumetric change (AMP) was assessed. Duplex sonography served as a reference method. RESULTS: In the comprehensive set of novel pulse wave parameters significant inter-arm differences were demonstrated and a significant delay of the systolic maximum at the fistula arm in comparison to the non-fistula arm (204 ± 3.4 vs. 162 ± 5.3 ms, p < 0.001) was proven. Unexpectedly, pulse wave velocity apparently did not differ between both arms (7.85 vs. 8.05 m/s at the fistula/non-fistula side, p = 0.942). The inter-arm differences of the slope parameters were more pronounced in forearm than in upper arm fistulas. Finally, we showed that the inter-arm difference of AMP correlated with volume flow (r = 0.326 with p = 0.017). CONCLUSION: Pulse waves as assessed by oscillometric pulse wave analysis have distinct features at fistula and non-fistula arms. This is due to enhanced arteriovenous flow, i.e. in both the brachial artery and the fistula vein. The analysis of those alterations has the potential to assess fistula function.

Arterial stiffness is associated with prehypertension in both non-hypertensives and treated hypertensives-A matched case control study.

BACKGROUND: Prehypertension (PHT) is a cardiovascular health risk defined by blood pressure (BP). Arterial stiffness (AS) provides beyond brachial BP inference on vascular ageing and pulse wave analysis (PWA) can measure it non-invasively.We compared association between AS and PHT using age and gender matched case-controls. METHODS: This is a sub analysis of previous PWA studies of hypertensives and non-hypertensives. Using oscillometric PWA by Mobil-o-Graph (IEM, Stolberg, Germany), parameters of AS (augmentation pressure and index, reflection magnitude, aortic pulse wave velocity, pulse pressure amplification), brachial hemodynamics (BH), and central hemodynamics (CH; aortic BP, cardiac output related parameters, stroke work) were derived. Age and gender matched case controls were compared as: 1) Nonhypertensives with BP at prehypertensive level (PHT) versus normotensives (NT) (n = 217 each), 2) Under treatment hypertensives with BP at prehypertensive level (PHT-T) versus untreated, nonhypertensives with BP at prehypertensive level (PHT-UT) (n = 74 each). RESULTS: PHTs had higher AS, BH and CH than NTs, with statistical significance for all but few parameters. PHT-T had comparable BH but higher AS, CH than PHT-UT with significance for few parameters. CONCLUSION: Pulse wave analysis derived arterial stiffness is associated with prehypertension compared to normal, after age and gender matching. In hypertensives, arterial stiffness is significantly higher despite being treated to prehypertension level as compared to control. It hints arterial stiffness to be better parameter than brachial BP to study prehypertension.

An algorithm to detect dicrotic notch in arterial blood pressure and photoplethysmography waveforms using the iterative envelope mean method.

BACKGROUND AND OBJECTIVE: Detection of the dicrotic notch (DN) within a cardiac cycle is essential for assessment of cardiac output, calculation of pulse wave velocity, estimation of left ventricular ejection time, and supporting feature-based machine learning models for noninvasive blood pressure estimation, and hypotension, or hypertension prediction. In this study, we present a new algorithm based on the iterative envelope mean (IEM) method to detect automatically the DN in arterial blood pressure (ABP) and photoplethysmography (PPG) waveforms. METHODS: The algorithm was evaluated on both ABP and PPG waveforms from a large perioperative dataset (MLORD dataset) comprising 17,327 patients. The analysis involved a total of 1,171,288 cardiac cycles for ABP waveforms and 3,424,975 cardiac cycles for PPG waveforms. To evaluate the algorithm's performance, the systolic phase duration (SPD) was employed, which represents the duration from the onset of the systolic phase to the DN in the cardiac cycle. Correlation plots and regression analysis were used to compare the algorithm against marked DN detection, while box plots and Bland-Altman plots were used to compare its performance with both marked DN detection and an established DN detection technique (second derivative). The marking of the DN temporal location was carried out by an experienced researcher using the help of the 'find_peaks' function from the scipy Python package, serving as a reference for the evaluation. The marking was visually validated by both an engineer and an anesthesiologist. The robustness of the algorithm was evaluated as the DN was made less visually distinct across signal-to-noise ratios (SNRs) ranging from -30 dB to -5 dB in both ABP and PPG waveforms. RESULTS: The correlation between SPD estimated by the algorithm and that marked by the researcher is strong for both ABP (R2(87,343) =0.99, p<.001) and PPG (R2(86,764) =0.98, p<.001) waveforms. The algorithm had a lower mean error of DN detection (s): 0.0047 (0.0029) for ABP waveforms and 0.0046 (0.0029) for PPG waveforms, compared to 0.0693 (0.0770) for ABP and 0.0968 (0.0909) for PPG waveforms for the established 2nd derivative method. The algorithm has high rate of detectability of DN detection for SNR of >= -9 dB for ABP waveforms and >= -12 dB for PPG waveforms indicating robust performance in detecting the DN when it is less visibly distinct. CONCLUSION: Our proposed IEM- based algorithm can detect DN in both ABP and PPG waveforms with low computational cost, even in cases where it is not distinctly defined within a cardiac cycle of the waveform ('DN-less signals'). The algorithm can potentially serve as a valuable, fast, and reliable tool for extracting features from ABP and PPG waveforms. It can be especially beneficial in medical applications where DN-based features, such as SPD, diastolic phase duration, and DN amplitude, play a significant role.

Serum Lipoprotein(a) Levels as a Predictor of Aortic Stiffness in Patients on Long-Term Peritoneal Dialysis.

BACKGROUND Lipoprotein (a) [Lp(a)] is associated with atherosclerosis and cardiovascular mortality in patients with kidney failure. Aortic stiffness (AS), measured primarily by carotid-femoral pulse wave velocity (cfPWV), reflects vascular aging and precedes end-organ failure. This study aimed to evaluate the association between serum Lp(a) levels and cfPWV in patients undergoing peritoneal dialysis (PD). MATERIAL AND METHODS In this cross-sectional study, which included 148 patients with long-term PD for end-stage kidney failure, cfPWV was measured using a cuff-based method. AS was defined as a cfPWV exceeding 10 m/s, and an enzyme-linked immunosorbent assay was used to determine serum Lp(a) levels. Univariate and multivariate regression analyses were performed to identify the clinical correlates of AS. RESULTS There were 32 (21.6%) patients diagnosed with AS. Based on the multivariate logistic regression analysis, the odds ratio for AS was 1.007 (95% confidence interval, 1.003-1.011; P=0.001) for every 1 mg/L increase in Lp(a) levels. Multivariate linear regression analysis showed that Lp(a) (P<0.001), age (P=0.003), waist circumference (P=0.008), systolic blood pressure (P=0.010), and diabetes mellitus (P<0.001) were positively associated with cfPWV. The area under the receiver operating characteristic curve for Lp(a) in differentiating AS from non-AS was 0.770 (95% confidence interval, 0.694-0.835; P<0.0001). CONCLUSIONS Serum Lp(a) level was independently associated with cfPWV and AS in patients with PD.

Measuring global cerebrovascular pulsatility transmission using 4D flow MRI.

Pulse wave encephalopathy (PWE) is hypothesised to initiate many forms of dementia, motivating its identification and risk assessment. As candidate pulsatility based biomarkers for PWE, pulsatility index and pulsatility damping have been studied and, currently, do not adequately stratify risk due to variability in pulsatility and spatial bias. Here, we propose a locus-independent pulsatility transmission coefficient computed by spatially tracking pulsatility along vessels to characterise the brain pulse dynamics at a whole-organ level. Our preliminary analyses in a cohort of 20 subjects indicate that this measurement agrees with clinical observations relating blood pulsatility with age, heart rate, and sex, making it a suitable candidate to study the risk of PWE. We identified transmission differences between vascular regions perfused by the basilar and internal carotid arteries attributed to the identified dependence on cerebral blood flow, and some participants presented differences between the internal carotid perfused regions that were not related to flow or pulsatility burden, suggesting underlying mechanical differences. Large populational studies would benefit from retrospective pulsatility transmission analyses, providing a new comprehensive arterial description of the hemodynamic state in the brain. We provide a publicly available implementation of our tools to derive this coefficient, built into pre-existing open-source software.

Clinical Validation of Carotid-Femoral Pulse Wave Velocity Measurement Using a Multi-Beam Laser Vibrometer: The CARDIS Study.

BACKGROUND: Carotid-femoral pulse wave velocity (cfPWV) is the gold standard for noninvasive arterial stiffness assessment, an independent predictor of cardiovascular disease, and a potential parameter to guide therapy. However, cfPWV is not routinely measured in clinical practice due to the unavailability of a low-cost, operator-friendly, and independent device. The current study validated a novel laser Doppler vibrometry (LDV)-based measurement of cfPWV against the reference technique. METHODS: In 100 (50 men) hypertensive patients, cfPWV was measured using applanation tonometry (Sphygmocor) and the novel LDV device. This device has 2 handpieces with 6 laser beams each that simultaneously measure vibrations from the skin surface at carotid and femoral sites. Pulse wave velocity is calculated using ECG for the identification of cardiac cycles. An ECG-independent method was also devised. Cardiovascular risk score was calculated for patients between 40 and 75 years old using the WHO risk scoring chart. RESULTS: LDV-based cfPWV correlated significantly with tonometry (r=0.86, P<0.0001 ECG-dependent [cfPWVLDV_ECG] and r=0.80, P<0.001 ECG-independent [cfPWVLDV_w/oECG] methods). Bland-Altman analysis showed nonsignificant bias (0.65 m/s) and acceptable SD (1.27 m/s) between methods. Intraobserver coefficient of variance for LDV was 4.7% (95% CI, 3.0%-5.5%), and interobserver coefficient of variance was 5.87%. CfPWV correlated significantly with CVD risk (r=0.64, P<0.001; r=0.41, P=0.003; and r=0.37, P=0.006 for tonometry, LDV-with, and LDV-without ECG, respectively). CONCLUSIONS: The study demonstrates clinical validity of the LDV device. The LDV provides a simple, noninvasive, operator-independent method to measure cfPWV for assessing arterial stiffness, comparable to the standard existing techniques. REGISTRATION: URL: https://clinicaltrials.gov/study/NCT03446430; Unique identifier: NCT03446430.

Optimum Parameters in Ultrasound Coherent Plane Wave Compounding for High LPWV Estimation: Validation on Phantom and Feasibility in 10 Subjects.

OBJECTIVES: The aim of this study is to determine the optimum and fine values of the number and transmission angles of tilted plane waves for coherent plane-wave compounding (CPWC)-based high local pulse wave velocity (LPWV) estimation. METHODS: A Verasonics system incorporating a linear array probe L14-5/38 with 128 elements and a pulsatile pump, CompuFlow1000, were used to acquire radio frequency data of 3, 5, 7, and 9 tilted plane wave sequences with angle intervals from 0° to 12° with a coarse interval increment step of 1°, and the angle intervals from 0° to 2° with a fine interval increment step of 0.25° from a carotid vessel phantom with the LPWV of 13.42 ± 0.90 m/s. The mean value, standard deviation, and coefficients of variation (CV) of the estimated LPWVs were calculated to quantitatively assess the performance of different configurations for CPWC-based LPWV estimation. Ten healthy human subjects of two age groups were recruited to assess the in vivo feasibility of the optimum parameter values. RESULTS: The CPWC technique with three plane waves (PRF of 12 kHz corresponding to a frame rate of 4000 Hz) with an interval of 0.75° had LPWVs of 13.52 ± 0.08 m/s with the lowest CV of 1.84% on the phantom, and 5.49 ± 1.46 m/s with the lowest CV of 12.35% on 10 subjects. CONCLUSIONS: The optimum parameters determined in this study show the best repeatability of the LPWV measurements with a vessel phantom and 10 healthy subjects, which support further studies on larger datasets for potential applications.

Association between arterial health and cognition in adolescents: The PANIC study.

We investigated the associations of the measures of arterial health with cognition in adolescents and whether physical activity (PA) or sedentary time (ST) confounds these associations. One hundred sixteen adolescents (71 boys) aged 15.9 ± 0.4 participated in the study. PA and ST were assessed using a combined accelerometer/heart rate monitor. Overall cognition was computed from the results of psychomotor function, attention, working memory, and paired-associate learning tests. Pulse wave velocity was measured by impedance cardiography, carotid intima-media thickness, and carotid artery distensibility by carotid ultrasonography. Systolic and diastolic blood pressure (SBP and DBP) were measured using an aneroid sphygmomanometer. SBP was inversely associated with overall cognition (standardized regression coefficient [ß] = -0.216, 95% confidence interval (CI) -0.406 to -0.027, p = 0.025). Pulse wave velocity (ß = -0.199, 95% CI -0.382 to -0.017, p = 0.033) was inversely associated with working memory task accuracy. SBP was directly associated with reaction time in the attention (ß = 0.256, 95% CI 0.069 to 0.443, p = 0.008) and errors in the paired-associate learning tasks (ß = 0.308, 95% CI 0.126 to 0.489, p = 0.001). Blood pressure was inversely associated with overall cognition. PA or ST did not confound the associations. Results suggest that preventing high blood pressure is important for promoting cognition in adolescents.

Comparison of cardiac output estimates obtained from the Antares oscillometric pulse wave analysis algorithm and from Doppler transthoracic echocardiography.

BACKGROUND: In cardiology, cardiac output (CO) is an important parameter for assessing cardiac function. While invasive thermodilution procedures are the gold standard for CO assessment, transthoracic Doppler echocardiography (TTE) has become the established method for routine CO assessment in daily clinical practice. However, a demand persists for non-invasive approaches, including oscillometric pulse wave analysis (PWA), to enhance the accuracy of CO estimation, reduce complications associated with invasive procedures, and facilitate its application in non-intensive care settings. Here, we aimed to compare the TTE and oscillometric PWA algorithm Antares for a non-invasive estimation of CO. METHODS: Non-invasive CO data obtained by two-dimensional TTE were compared with those from an oscillometric blood pressure device (custo med GmbH, Ottobrunn, Germany) using the integrated algorithm Antares (Redwave Medical GmbH, Jena, Germany). In total, 59 patients undergoing elective cardiac catheterization for clinical reasons (71±10 years old, 76% males) were included. Agreement between both CO measures were assessed by Bland-Altman analysis, Student's t-test, and Pearson correlations. RESULTS: The mean difference in CO was 0.04 ± 1.03 l/min (95% confidence interval for the mean difference: -0.23 to 0.30 l/min) for the overall group, with lower and upper limits of agreement at -1.98 and 2.05 l/min, respectively. There was no statistically significant difference in means between both CO measures (P = 0.785). Statistically significant correlations between TTE and Antares CO were observed in the entire cohort (r = 0.705, P<0.001) as well as in female (r = 0.802, P<0.001) and male patients (r = 0.669, P<0.001). CONCLUSIONS: The oscillometric PWA algorithm Antares and established TTE for a non-invasive estimation of CO are highly correlated in male and female patients, with no statistically significant difference between both approaches. Future validation studies of the Antares CO are necessary before a clinical application can be considered.

Influence of Blood Pressure Reduction on Pulse Wave Velocity in Primary Hypertension: A Meta-Analysis and Comparison With an Acute Modulation of Transmural Pressure.

BACKGROUND: Increased arterial stiffness and pulse wave velocity (PWV) of the aorta and large arteries impose adverse hemodynamic effects on the heart and other organs. Antihypertensive treatment reduces PWV, but it is unknown whether this results from an unloading of stiffer elements in the arterial wall or is due to an alternate functional or structural change that might differ according to class of antihypertensive drug. METHODS: We performed a systematic review and meta-analysis of the effects of different antihypertensive drug classes and duration of treatment on PWV with and without adjustment for change in mean arterial blood pressure (BP; study 1) and compared this to the change in PWV after an acute change in transmural pressure, simulating an acute change in BP (study 2). RESULTS: A total of 83 studies involving 6200 subjects were identified. For all drug classes combined, the reduction of PWV was 0.65 (95% CI, 0.46-0.83) m/s per 10 mm Hg reduction in mean arterial BP, a change similar to that induced by an acute change in transmural pressure in a group of hypertensive subjects. When adjusted for change in mean arterial BP, the reduction in PWV after treatment with beta-blockers or diuretics was less than that after treatment with angiotensin-converting enzyme inhibitors/angiotensin receptor antagonists or calcium channel antagonists. CONCLUSIONS: Reduction in PWV after antihypertensive treatment is largely explained by the reduction in BP, but there are some BP-independent effects. These might increase over time and contribute to better outcomes over the long term, but this remains to be demonstrated in long-term clinical trials.

Effect of systemic vascular resistance on the agreement between stroke volume by non-invasive pulse wave analysis and Doppler ultrasound in healthy volunteers.

BACKGROUND: Stroke volume can be estimated beat-to-beat and non-invasively by pulse wave analysis (PWA). However, its reliability has been questioned during marked alterations in systemic vascular resistance (SVR). We studied the effect of SVR on the agreement between stroke volume by PWA and Doppler ultrasound during reductions in stroke volume in healthy volunteers. METHODS: In a previous study we simultaneously measured stroke volume by PWA (SVPWA) and suprasternal Doppler ultrasound (SVUS). We exposed 16 healthy volunteers to lower body negative pressure (LBNP) to reduce stroke volume in combination with isometric hand grip to elevate SVR. LBNP was increased by 20 mmHg every 6 minutes from 0 to 80 mmHg, or until hemodynamic decompensation. The agreement between SVPWA and SVUS was examined using Bland-Altman analysis with mixed regression. Within-subject limits of agreement (LOA) was calculated from the residual standard deviation. SVRUS was calculated from SVUS. We allowed for a sloped bias line by introducing the mean of the methods and SVRUS as explanatory variables to examine whether the agreement was dependent on the magnitude of stroke volume and SVRUS. RESULTS: Bias ± limits of agreement (LOA) was 27.0 ± 30.1 mL. The within-subject LOA was ±11.1 mL. The within-subject percentage error was 14.6%. The difference between methods decreased with higher means of the methods (-0.15 mL/mL, confidence interval (CI): -0.19 to -0.11, P<0.001). The difference between methods increased with higher SVRUS (0.60 mL/mmHg × min × L-1, 95% CI: 0.48 to 0.72, P<0.001). CONCLUSION: PWA overestimated stroke volume compared to Doppler ultrasound during reductions in stroke volume and elevated SVR in healthy volunteers. The agreement between SVPWA and SVUS decreased during increases in SVR. This is relevant in settings where a high level of reliability is required.