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The dynamics of the pulse wave (PW) associated with the PW transit time variability (PWTTV) determines the peripheral pulse rate variability, which is used as a surrogate for heart rate variability (HRV). The aim of the work is to analyze the frequency-dependent dynamics of PWTTV and to identify the possible frequency-phase modulation of PW velocity oscillations on the transit from the heart to the soft tissues of the distal parts of the upper extremities. RR-interval recordings and synchronous records of photoplethysmograms of 12 conditionally healthy subjects from the PhysioNet open database were used in this work. Using the Hilbert–Huang transform 3 spectral components of PWTTV and HRV were identified. It was shown that the amplitudes of PWTTV oscillations were many times (up to 8.4 times) smaller than the amplitudes of HRV, and the peaks of PWTTV spectral components were shifted towards higher frequencies than those of HRV. Functional relations between PWTTV and HRV, which can determine the phase modulation of periodic changes in the PW propagation velocity, were revealed. [ABSTRACT FROM AUTHOR]

Background: Pulse wave transit time (PWTT) shows promise for monitoring intravascular fluid status intraoperatively. Presently, it is unknown how PWTT mirrors haemodynamic variables representing preload, inotropy, or afterload. Methods: PWTT was measured continuously in 24 adult volunteers. Stroke volume was assessed by transthoracic echocardiography. Volunteers underwent four randomly assigned manoeuvres: ‘Stand-up’ (decrease in preload), passive leg raise (increase in preload), a ‘step-test’ (adrenergic stimulation), and a ‘Valsalva manoeuvre’ (increase in intrathoracic pressure). Haemodynamic measurements were performed before and 1 and 5 min after completion of each manoeuvre. Correlations between PWTT and stroke volume were analysed using the Pearson correlation coefficient. Results: ‘Stand-up’ caused an immediate increase in PWTT (mean change +55.9 ms, P-value

Clinical studies have extensively demonstrated that central aortic blood pressure (CABP) has greater clinical significance in comparison with peripheral blood pressure. Despite the existence of various techniques for noninvasively measuring CABP, the clinical applications of most techniques are hampered by the unsatisfactory accuracy or large variability in measurement errors. In this study, we proposed a new method for noninvasively estimating CABP with improved accuracy and reduced uncertain errors. The main idea was to optimize the estimation of the pulse wave transit time from the aorta to the occluded lumen of the brachial artery under a suprasystolic cuff by identifying and utilizing the characteristic information of the cuff oscillation wave, thereby improving the accuracy and stability of the CABP estimation algorithms under various physiological conditions. The method was firstly developed and verified based on large‐scale virtual subject data (n = 800) generated by a computational model of the cardiovascular system coupled to a brachial cuff, and then validated with small‐scale in vivo data (n = 34). The estimation errors for the aortic systolic pressure were −0.05 ± 0.63 mmHg in the test group of the virtual subjects and −1.09 ± 3.70 mmHg in the test group of the patients, both demonstrating a good performance. In particular, the estimation errors were found to be insensitive to variations in hemodynamic conditions and cardiovascular properties, manifesting the high robustness of the method. The method may have promising clinical applicability, although further validation studies with larger‐scale clinical data remain necessary. [ABSTRACT FROM AUTHOR]

BACKGROUND: Several monitors have been developed that measure stroke volume (SV) in a beat-to-beat manner. Accordingly, Stroke volume variation (SVV) induced by positive pressure ventilation is widely used to predict fluid responsiveness. OBJECTIVE: The purpose of this study was to compare the ability of two different methods to predict fluid responsiveness using SVV, stroke volume variation by esCCO (esSVV) and stroke volume variation by FloTrac/VigileoTM (flSVV). METHODS: esSVV, flSVV, and stroke volume index (SVI) by both monitoring devices of 37 adult patients who underwent laparotomy surgery, were measured. Receiver operating characteristic (ROC) analysis was performed. RESULTS: The area under the ROC curve (AUC) of esSVV was significantly higher than that of flSVV (p = 0.030). esSVV and flSVV showed cutoff values of 6.1% and 10% respectively, to predict an increase of more than 10% in SVI after fluid challenge. The Youden index for esSVV was higher than flSVV, even with a cutoff value between 6% and 8%. CONCLUSION: Since esSVV and flSVV showed significant differences in AUC and cutoff values, the two systems were not comparable in predicting fluid responsiveness. Furthermore, it seems that SVV needs to be personalized to accurately predict fluid responsiveness for each patient. [ABSTRACT FROM AUTHOR]

The objective was to validate cardiac index (CI) and stroke volume variation (SVV) measured by pulse wave transit time (PWTT) technology using estimated continuous cardiac output (esCCO) technique, with pulse contour analysis (PCA) after off-pump coronary artery bypass grafting (OPCAB)Materials and methods. The study involved 21 patients after elective OPCAB. In all patients, CI and SVV were measured with both esCCO technique (CIesCCO and esSVV) and PCA (CIPCA and SVVPCA). The agreement between methods was analyzed using correlation analysis and Bland-Altman analysis. In addition, the trending ability of esCCO technique to control changes in CI during dynamic tests was investigated. Results. During the study, 178 pairs for CI and 174 pairs for SVV were collected. The mean bias between CIesCCO and CIPCA was 0.06 L·min–1 m–2 with limits of agreement of ± 0.92 L·min–1 m–2 and a percentage error of 35.3%. The concordance rate of CIesCCO was 70%. The mean bias between esSVV and SVVPCA achieved – 6.1% with limits of agreement of ± 15.5% and percentage error of 137%.Conclusions. The coherence of CIesCCO and esSVV based on PWTT in comparison with PCA is not appropriate. Further development of this monitoring algorithm may be required for more correct measurement of cardiac output and fluid responsiveness

A theoretical analysis of the literature data on the pulse-wave propagation velocity using a combination of electrocardiographic and photoplethysmographic signals was carried out. Its diagnostic value in medical practice lies in its use as a noninvasive method for measuring blood pressure, as well as for determining arterial stiffness. Some studies have shown a relationship between the velocity of pulse-wave propagation and risk factors for cardiovascular diseases. Pulse-wave propagation velocity is an early marker and predictor of cardiovascular risk in both people with normal blood pressure and people with hypertension; it is used as the "gold standard" in determining arterial stiffness; however, the issue of accuracy and automation of measuring the pulse-wave propagation velocity remains unresolved. [ABSTRACT FROM AUTHOR]

Abstract Background Aim of this study is to test the predictive value of Pulse Wave Transit Time (PWTT) for fluid responsiveness in comparison to the established fluid responsiveness parameters pulse pressure (ΔPP) and corrected flow time (FTc) during major abdominal surgery. Methods Forty patients undergoing major abdominal surgery were enrolled with continuous monitoring of PWTT (LifeScope® Modell J BSM-9101 Nihon Kohden Europe GmbH, Rosbach, Germany) and stroke volume (Esophageal Doppler Monitoring CardioQ-ODM®, Deltex Medical Ltd, Chichester, UK). In case of hypovolemia (difference in pulse pressure [∆PP] ≥ 9%, corrected flow time [FTc] ≤ 350 ms) a fluid bolus of 7 ml/kg ideal body weight was administered. Receiver operating characteristics (ROC) curves and corresponding areas under the curve (AUCs) were used to compare different methods of determining PWTT. A Wilcoxon test was used to discriminate fluid responders (increase in stroke volume of ≥ 10%) from non-responders. The predictive value of PWTT for fluid responsiveness was compared by testing for differences between ROC curves of PWTT, ΔPP and FTc using the methods by DeLong. Results AUCs (area under the ROC-curve) to predict fluid responsiveness for PWTT-parameters were 0.61 (raw c finger Q), 0.61 (raw c finger R), 0.57 (raw c ear Q), 0.53 (raw c ear R), 0.54 (raw non-c finger Q), 0.52 (raw non-c finger R), 0.50 (raw non-c ear Q), 0.55 (raw non-c ear R), 0.63 (∆ c finger Q), 0.61 (∆ c finger R), 0.64 (∆ c ear Q), 0.66 (∆ c ear R), 0.59 (∆ non-c finger Q), 0.57 (∆ non-c finger R), 0.57 (∆ non-c ear Q), 0.61 (∆ non-c ear R) [raw measurements vs. ∆ = respiratory variation; c = corrected measurements according to Bazett’s formula vs. non-c = uncorrected measurements; Q vs. R = start of PWTT-measurements with Q- or R-wave in ECG; finger vs. ear = pulse oximetry probe location]. Hence, the highest AUC to predict fluid responsiveness by PWTT was achieved by calculating its respiratory variation (∆PWTT), with a pulse oximeter attached to the earlobe, using the R-wave in ECG, and correction by Bazett’s formula (AUC best-PWTT 0.66, 95% CI 0.54–0.79). ∆PWTT was sufficient to discriminate fluid responders from non-responders (p = 0.029). No difference in predicting fluid responsiveness was found between best-PWTT and ∆PP (AUC 0.65, 95% CI 0.51–0.79; p = 0.88), or best-PWTT and FTc (AUC 0.62, 95% CI 0.49–0.75; p = 0.68). Conclusion ΔPWTT shows poor ability to predict fluid responsiveness intraoperatively. Moreover, established alternatives ΔPP and FTc did not perform better. Trial registration Prior to enrolement on clinicaltrials.gov (NC T03280953; date of registration 13/09/2017).

To compare the reliability of cardiac index (CI) and stroke-volume variation (SVV) measured by the pulse-wave transit-time (PWTT) method using estimated continuous cardiac output (esCCO) technique with conventional pulse-contour analysis after off-pump coronary artery bypass grafting (OPCAB). A single-center, prospective, observational study. At a 1,000-bed university hospital. A total of 21 patients were enrolled after elective OPCAB. The study authors performed a method comparison study with simultaneous measurement of CI and SVV based on the esCCO technique (CI esCCO and esSVV, correspondingly) and pulse-contour analysis (CI PCA and SVV PCA , correspondingly). As a secondary analysis, they also assessed the trending ability of CI esCCO versus CI PCA. The authors analyzed 178 measurement pairs for CI, and 174 pairs for SVV during the 10 study stages. The mean bias between CI esCCO and CI PCA was 0.06 L min/m2, with limits of agreement of ± 0.92 L min/m2 and a percentage error (PE) of 35.3%. The analysis of the trending ability of CI measured by PWTT revealed a concordance rate of 70%. The mean bias between esSVV and SVV PCA was –6.1%, with limits of agreement of ± 15.5% and a PE of 137%. The overall performance of CI esCCO and esSVV versus CI PCA and SVV PCA is not clinically acceptable. A further improvement of the PWTT algorithm may be required for an accurate and precise assessment of CI and SVV. [ABSTRACT FROM AUTHOR]

Background: Aim of this study is to test the predictive value of Pulse Wave Transit Time (PWTT) for fluid responsiveness in comparison to the established fluid responsiveness parameters pulse pressure (ΔPP) and corrected flow time (FTc) during major abdominal surgery. Methods: Forty patients undergoing major abdominal surgery were enrolled with continuous monitoring of PWTT (LifeScope® Modell J BSM-9101 Nihon Kohden Europe GmbH, Rosbach, Germany) and stroke volume (Esophageal Doppler Monitoring CardioQ-ODM®, Deltex Medical Ltd, Chichester, UK). In case of hypovolemia (difference in pulse pressure [∆PP] ≥ 9%, corrected flow time [FTc] ≤ 350 ms) a fluid bolus of 7 ml/kg ideal body weight was administered. Receiver operating characteristics (ROC) curves and corresponding areas under the curve (AUCs) were used to compare different methods of determining PWTT. A Wilcoxon test was used to discriminate fluid responders (increase in stroke volume of ≥ 10%) from non-responders. The predictive value of PWTT for fluid responsiveness was compared by testing for differences between ROC curves of PWTT, ΔPP and FTc using the methods by DeLong. Results: AUCs (area under the ROC-curve) to predict fluid responsiveness for PWTT-parameters were 0.61 (raw c finger Q), 0.61 (raw c finger R), 0.57 (raw c ear Q), 0.53 (raw c ear R), 0.54 (raw non-c finger Q), 0.52 (raw non-c finger R), 0.50 (raw non-c ear Q), 0.55 (raw non-c ear R), 0.63 (∆ c finger Q), 0.61 (∆ c finger R), 0.64 (∆ c ear Q), 0.66 (∆ c ear R), 0.59 (∆ non-c finger Q), 0.57 (∆ non-c finger R), 0.57 (∆ non-c ear Q), 0.61 (∆ non-c ear R) [raw measurements vs. ∆ = respiratory variation; c = corrected measurements according to Bazett's formula vs. non-c = uncorrected measurements; Q vs. R = start of PWTT-measurements with Q- or R-wave in ECG; finger vs. ear = pulse oximetry probe location]. Hence, the highest AUC to predict fluid responsiveness by PWTT was achieved by calculating its respiratory variation (∆PWTT), with a pulse oximeter attached to the earlobe, using the R-wave in ECG, and correction by Bazett's formula (AUC best-PWTT 0.66, 95% CI 0.54–0.79). ∆PWTT was sufficient to discriminate fluid responders from non-responders (p = 0.029). No difference in predicting fluid responsiveness was found between best-PWTT and ∆PP (AUC 0.65, 95% CI 0.51–0.79; p = 0.88), or best-PWTT and FTc (AUC 0.62, 95% CI 0.49–0.75; p = 0.68). Conclusion: ΔPWTT shows poor ability to predict fluid responsiveness intraoperatively. Moreover, established alternatives ΔPP and FTc did not perform better. Trial registration: Prior to enrolement on clinicaltrials.gov (NC T03280953; date of registration 13/09/2017). [ABSTRACT FROM AUTHOR]

Pulse wave transit time (PWTT) is the time difference between the occurrence of an R-wave on an electrocardiogram and the detection of pulsatile signals on a pulse oximeter, which reflects changes in blood pressure (BP) corresponding to the vessel wall compliance. However, the factors affecting PWTT variability have not been determined. Thus, we investigated the BP changes associated with variations in PWTT and identified the clinical characteristics associated with these variations. Data related to 605 cases of dental procedures performed under intravenous conscious sedation from April 2020 to November 2021 were collected, and 485 cases were enrolled. Heart rate, systolic blood pressure before and after local anesthesia (LA) administration, and crest and trough PWTT waves during LA administration were recorded. Thereafter, PWTT variability was calculated; cases were divided into two groups: large PWTT variability (LPV, n = 357) and small PWTT variability (SPV, n = 128). The index of large PWTT variability could not detect changes in BP. Logistic regression analysis revealed that factors, such as LA use, age, hypertension, and dental treatment phobia were associated with PWTT variability. The use of epinephrine more than 36.25 µg in each LA resulted in PWTT variability of more than 15 ms. [ABSTRACT FROM AUTHOR]

Objective To investigate the changes in left wrist pulse wave transit time （PTT） in patients with hypertension， as well as the effects of serological indicators and unhealthy lifestyle. Methods We recruited 321 hypertensive patients admitted to Chinese PLA General Hospital Hainan Branch from June 2020 to April 2021 and divided them into two groups according to the simple randomization method. Totally 135 patients in the control group drank 20 mL of water after getting up in the morning and 186 patients in the observation group took the nifedipine controlled release tablets on the basis of the control group. A smart watch was used to collect the PTT at 0. 5 h，4. 5 h，and 8. 5 h after taking the medicine（drinking water）for the two groups. Repeated measurement analysis of variance was used to observe the influences of the time， interaction effect， and medicine on PTT. The data of gender， age， height， weight， left arm circumference， left arm length， resting heart rate， smoking， and alcohol drinking were collected. Fasting blood of 4 mL was collected to detect indicators such as fasting blood glucose（FBG）， total cholesterol（TC）， triglyceride（TG）， and uric acid（UA） to analyze possible factors affecting PTT. Results The time effect was statistically significant（F= 12. 065， P<0. 001）， while the interaction effect was not（F=0. 089， P=0. 915）. There was no statistically significant difference between the two groups （F=2. 074， P=0. 155）. FBG， TC， TG， resting heart rate， and limited alcohol drinking differed significantly （P<0. 05）. Conclusion PTT gradually shortens with time， and it has no significant relationship with antihypertensive drugs， but may be related to FBG， TC， TG， resting heart rate， alcohol drinking and other indicators. [ABSTRACT FROM AUTHOR]

Background: Pulse wave transit time is a novel method of estimating continuous cardiac output (esCCO). Since there are not many studies evaluating esCCO, we compared it with arterial pressure based cardiac output (APCO) method (FloTrac). Methods: In this prospective single-center observational study, we included 50 adult patients planned to undergo supramajor oncosurgeries, where major blood loss and extensive fluid shifts were expected. Cardiac output (CO) measurements were obtained by both methods at five distinct time points, giving us 250 paired readings of stroke volume index (SVI) and cardiac index (CI). We analyzed these readings using Pearson's correlation coefficient and Bland-Altman plots, along with other appropriate statistical tests. Results: There was significant correlation between CI and SVI measured by the esCCO and APCO. Bland-Altman plot analysis for CI showed a bias of -0.44 L/minute/m², precision of 0.74, and the limits of agreement of -1.89 and +1.01, while the percentage error was 46.29%. Bland-Altman analysis for SVI showed a bias -5.07 mL with a precision of 9.36, and the limits of agreement to be -23.4 to +13.28. The percentage error was 46.56%. Conclusion: This study demonstrated that esCCO tended to underestimate the CI to a large degree, particularly while estimating the cardiac output in the lower range. We found that the limits of agreement between two methods were wide, which are not likely to be clinically acceptable. Further studies with larger number of data points, obtained in a similar subset of patients, for cardiac output measurement in the perioperative period will certainly help determine if pulse wave transit time (PWTT) is here to stay (CTRI No.: CTRI/2019/08/020543). [ABSTRACT FROM AUTHOR]

Blood pressure is one of the key physiological parameters for determining human health, and can prove whether human cardiovascular function is healthy or not. In general, what we call blood pressure refers to arterial blood pressure. Blood pressure fluctuates greatly and, due to the influence of various factors, even varies with each heartbeat. Therefore, achievement of continuous blood pressure measurement is particularly important for more accurate diagnosis. It is difficult to achieve long-term continuous blood pressure monitoring with traditional measurement methods due to the continuous wear of measuring instruments. On the other hand, radar technology is not easily affected by environmental factors and is capable of strong penetration. In this study, by using machine learning, tried to develop a linear blood pressure prediction model using data from a public database. The radar sensor evaluates the measured object, obtains the pulse waveform data, calculates the pulse transmission time, and obtains the blood pressure data through linear model regression analysis. Confirm its availability to facilitate follow-up research, such as integrating other sensors, collecting temperature, heartbeat, respiratory pulse and other data, and seeking medical treatment in time in case of abnormalities. [ABSTRACT FROM AUTHOR]

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The article discusses a new method for the pulse wave velocity estimation using a pneumatic blood pressure sensor previously developed by the authors and the capability of that method for the early atherosclerosis diagnosis. The method proposed is based on measuring by the pneumatic sensor of the so-called pulse transit time - the time delay between the pulse wave signal and the synchronous ECG record. The article substantiates the way of determining, according to the waveform of the pulse signal, of that front characteristic time moment, which is more reliable for the measuring the delay to the R-peak of an ECG. The issues of accounting the variability of the pulse wave front delay at different points of the artery in the calculating the mean value and standard deviation of the pulse wave propagation velocity are discussed in detail. Almost all discussed features of the proposed methodology are illustrated by experimental data. [ABSTRACT FROM AUTHOR]

RESPIRATORY CHANGES IN PI OR PLETH VARIABILITY INDEX In mechanically ventilated patients, the respiratory changes in left ventricular stroke volume induce proportional changes in arterial pulse pressure (also known as pulse pressure variation [PPV]) and in PI (pleth variability index [PVI]) (10). When assessing the predictive value of absolute PI changes, because pulse oximeters display PI values with only one decimal, Beurton et al (1) showed that the sensitivity dropped to 63%. THE PI AS A MARKER OF TISSUE PERFUSION The PI is the ratio of the pulsatile component of the photoplethysmographic waveform to the total amplitude of the signal (Fig. Other variables, including the peripheral perfusion index (PI), can be measured by pulse oximeters and may have value for hemodynamic monitoring and management, as illustrated by the study from Beurton et al (1) published in this issue in Critical Care Medicine. [Extracted from the article]

Background: Pulse wave transit time (PWTT) shows promise for monitoring intravascular fluid status intraoperatively. Presently, it is unknown how PWTT mirrors haemodynamic variables representing preload, inotropy, or afterload., Methods: PWTT was measured continuously in 24 adult volunteers. Stroke volume was assessed by transthoracic echocardiography. Volunteers underwent four randomly assigned manoeuvres: 'Stand-up' (decrease in preload), passive leg raise (increase in preload), a 'step-test' (adrenergic stimulation), and a 'Valsalva manoeuvre' (increase in intrathoracic pressure). Haemodynamic measurements were performed before and 1 and 5 min after completion of each manoeuvre. Correlations between PWTT and stroke volume were analysed using the Pearson correlation coefficient., Results: 'Stand-up' caused an immediate increase in PWTT (mean change +55.9 ms, P -value <0.0001, 95% confidence interval 46.0-65.7) along with an increase in mean arterial pressure and heart rate and a drop in stroke volume ( P -values <0.0001). Passive leg raise caused an immediate drop in PWTT (mean change -15.4 ms, P -value=0.0024, 95% confidence interval -25.2 to -5.5) along with a decrease in mean arterial pressure ( P -value=0.0052) and an increase in stroke volume ( P -value=0.001). After 1 min, a 'step-test' caused no significant change in PWTT measurements ( P -value=0.5716) but an increase in mean arterial pressure and heart rate ( P -values <0.0001), without changes in stroke volume ( P -value=0.1770). After 5 min, however, PWTT had increased significantly ( P -value <0.0001). Measurements after the Valsalva manoeuvre caused heterogeneous results., Conclusion: Noninvasive assessment of PWTT shows promise to register immediate preload changes in healthy adults. The clinical usefulness of PWTT may be hampered by late changes because of reasons different from fluid shifts., Clinical Trial Registration: German clinical trial register (DRKS, ID: DRKS00031978, https://www.drks.de/DRKS00031978)., (© 2024 The Authors.)

Goal of the study: to evaluate the accuracy of invasive measurement of cardiac output (CO) by pulse wave transit time (PWTT) (esCCO, Japan) compared to transpulmonary thermodilution (TPTD) (PiCCO2 , Germany) after aortocoronary bypass (ACB) without cardiopulmonary bypass (ACB without CPB). Methods. 21 patients with ACB without CPB were enrolled into the study. During early post-operative period CO was simultaneously registered at eight stages basing on PWTT (COPWTT) and TPTD (COTPTD). Statistic analysis included evaluation of congruence of CO absolute values and capability to follow-up changes in CO. Results. In accordance with Bland-Altman analysis the average difference between two methods made 0.3 l/min. with consistency limits of ± 2.1 l/min. and percent error of 40%. Polar chart analysis showed the angular difference of 2.6°, radial consistency limits ± 53.3° and polar concordance of 69%. Conclusion: Lower repeatability of CO measurement by PWTT and insufficient capability to follow the changes in CO after ACB without CPB don not allow recommending this method in its invasive variant for routine practice as an alternative to thermodilution methods.

The survival rate of patients with ischemic heart disease (IHD) is increasing. However, survivors experience increased risk for neurological complications. The mechanisms for this increased risk are unknown. We tested the hypothesis that patients with IHD have greater carotid and cerebrovascular stiffness, and these indexes predict white matter small vessel disease. Fifty participants (age, 40-78 yr), 30 with IHD with preserved ejection fraction and 20 healthy age-matched controls, were studied using ultrasound imaging of the common carotid artery (CCA) and middle cerebral artery (MCA), as well as magnetic resonance imaging (T1, T2-FLAIR), to measure white matter lesion volume (WMLv). Carotid β-stiffness provided the primary measure of peripheral vascular stiffness. Carotid-cerebral pulse wave transit time (ccPWTT) provided a marker of cerebrovascular stiffness. Pulsatility index (PI) and resistive index (RI) of the MCA were calculated as measures of downstream cerebrovascular resistance. When compared with controls, patients with IHD exhibited greater β-stiffness [8.5 ± 3.3 vs. 6.8 ± 2.2 arbitrary units (AU); P = 0.04], MCA PI (1.1 ± 0.20 vs. 0.98 ± 0.18 AU; P = 0.02), and MCA RI (0.66 ± 0.06 vs. 0.62 ± 0.07 AU; P = 0.04). There was no difference in WMLv between IHD and control groups (0.95 ± 1.2 vs. 0.86 ± 1.4 mL; P = 0.81). In pooled patient data, WMLv correlated with both β-stiffness (R = 0.34, P = 0.02) and cerebrovascular ccPWTT (R = -0.43, P = 0.02); however, β-stiffness and ccPWTT were not associated (P = 0.13). In multivariate analysis, WMLv remained independently associated with ccPWTT (P = 0.02) and carotid β-stiffness (P = 0.04). Patients with IHD expressed greater β-stiffness and cerebral microvascular resistance. However, IHD did not increase risk of WMLv or cerebrovascular stiffness. Nonetheless, pooled data indicate that both carotid and cerebrovascular stiffness are independently associated with WMLv. NEW & NOTEWORTHY This study found that patients with ischemic heart disease (IHD) with preserved ejection fraction and normal blood pressures exhibit greater carotid β-stiffness, as well as middle cerebral artery pulsatility and resistive indexes, than controls. White matter lesion volume (WMLv) was not different between vascular pathology groups. Cerebrovascular pulse wave transit time (ccPWTT) and carotid β-stiffness independently associate with WMLv in pooled participant data, suggesting that regardless of heart disease history, ccPWTT and β-stiffness are associated with structural white matter damage. [ABSTRACT FROM AUTHOR]

The pulse wave transit time (PWTT) is easily measured as the time from the R wave of an electrocardiogram to the arrival of the pulse wave measured by an oxygen saturation monitor at the earlobe. We investigated whether the change of PWTT during exercise testing reflects cardiopulmonary function. Eighty-nine cardiac patients who underwent cardiopulmonary exercise testing (CPX) were enrolled. We analyzed the change of PWTT during exercise and the relationship between the shortening of the PWTT and CPX parameters. PWTT was significantly shortened from rest to peak exercise (204.6 ± 33.6 vs. 145.6 ± 26.4 msec, p < 0.001) in all of the subjects. The patients with heart failure had significantly higher PWTT at peak exercise than the patients without heart failure (152.7 ± 27.1 vs. 140.4 ± 24.8 msec, p = 0.031). The shortening of PWTT from rest to peak exercise showed significant positive correlations with the peak O2 uptake (VO2) (r = 0.56, p < 0.001), anaerobic threshold (r = 0.40, p = 0.016), and % increase of systolic blood pressure during exercise (r = 0.75, p < 0.001), and a negative correlation with the slope of the increase in ventilation versus the increase in CO2 output (VE-VCO2 slope) (r = - 0.42, p = 0.010) in the patients with heart failure. PWTT was shortened during exercise as the exercise intensity increased. In the patients with heart failure, the shortening of PWTT from rest to peak exercise was smaller in those with lower exercise capacity and those with higher VE-VCO2 slope, an established index known to reflect the severity of heart failure. [ABSTRACT FROM AUTHOR]

For hypertensive patients, a real-time human physiological signal monitoring system helps to track blood pressure status and provides valuable data to clinicians for early diagnosis and timely intervention. Optical fiber pulse sensing has superior conditions such as resistance to electromagnetic interference and richness of measured pulse characteristics. In this study, a monitoring system based on a single-point curved fiber pulse sensor (CFPS) was used to collect the pulse wave signal of a human radial artery. The features of the pulse wave signal were used to estimate the pulse wave transit time (PTT) and Blood Pressure—systolic blood pressure (SBP) and diastolic blood pressure (DBP)—based on support vector regression (SVR) optimized by a genetic algorithm (GA) (GA-SVR model). The results show that the root mean square error (RMSE) of SBP, DBP and PTT were 1.571 mmHg, 3.250 mmHg and 5.719 ms, respectively, and the results met the Advancement of Medical Instrumentation (AAMI) criteria. Therefore, a real-time pulse wave monitoring system based on a single-point CFPS can well predict human physiological signals such as PTT, SBP and DBP. [ABSTRACT FROM AUTHOR]

Objective . Since pulse wave transit time (PWTT) shortens as pulmonary artery pressure (PAP) increases it was suggested as a potential non-invasive surrogate for PAP. The state of tidal lung filling is also known to affect PWTT independently of PAP. The aim of this retrospective analysis was to test whether respiratory gating improved the correlation coefficient between PWTT and PAP. Approach . In each one of five anesthetized and mechanically ventilated pigs two high-fidelity pressure catheters were placed, one directly behind the pulmonary valve, and the second one in a distal branch of the pulmonary artery. PAP was raised using the thromboxane A2 analogue U46619 and animals were ventilated in a pressure controlled mode (I:E ratio 1:2, respiratory rate 12/min, tidal volume of 6 ml kg -1 ). All signals were recorded using the multi-channel platform PowerLab ® . The arrival of the pulse wave at each catheter tip was determined using a MATLAB-based modified hyperbolic tangent algorithm and PWTT calculated as the time interval between these arrivals. Main results . Correlation coefficient for PWTT and mean PAP was r = 0.932 for thromboxane. This correlation coefficient increased considerably when heart beats either at end-inspiration ( r = 0.978) or at end-expiration ( r = 0.985) were selected (=respiratory gating). Significance . The estimation of mean PAP from PWTT improved significantly when taking the respiratory cycle into account. Respiratory gating is suggested to improve for the estimation of PAP by PWTT., (Creative Commons Attribution license.)

The monitoring and optimization of cardiac output (CO) are central components of perioperative hemodynamic management in patients undergoing cardiothoracic surgery. Until recently, echocardiography and invasive indicator dilution methods have been the mainstays of CO monitoring in these patients. However, completely noninvasive methods to estimate CO have become available during recent years. In this review, the physical measurement principles, limitations, and measurement performance of the different techniques for continuous noninvasive CO estimation in the setting of cardiothoracic surgery are described. Methods to estimate CO in a completely noninvasive manner include noninvasive pulse wave analysis (using a finger cuff method or automated radial artery applanation tonometry), thoracic electrical bioimpedance and bioreactance, pulse wave transit time, and partial carbon dioxide rebreathing. All these technologies have been evaluated in cardiothoracic surgery patients, but the validation studies describing the measurement performance in comparison with invasive reference methods have shown inconsistent and, in part, contradictory results. In addition, all technologies have major limitations with regard to the applicability during routine clinical care in the operating room or the intensive care unit. Therefore, the methods for noninvasive CO estimation described in this review still require technological improvements with regard to measurement performance and clinical applicability before they can be recommended for routine perioperative hemodynamic management of cardiothoracic surgery patients outside of studies. [ABSTRACT FROM AUTHOR]

Background: Pulse wave transit time (PWTT) is widely used to characterize the dynamic properties of the arteries. PWTT is most often calculated as the time interval from the R peak in the electrocardiogram (start of the pulse wave) to the rise in the finger photoplethysmogram (arrival of the pulse wave). This is the PWTTHF. The aim of this study was to analyse the effect of cuff occlusion on PWTT, and using this information to improve the reliability of cuff-based indirect blood pressure (BP) measurement. Methods: PWTT was measured with a home health monitoring device that inflates and deflates the cuff slowly (6 mmHg/s). The change in the arterial wall rigidity caused by cuff occlusion is different in the parts of the arterial section proximal and distal to the cuff. Accordingly, PWTT was divided into two parts: PWTT from the heart to the cuff (PWTTHC) and PWTT from the cuff to the fingertip (PWTTCF). Seven patients with various cardiovascular diseases (55–66 years old), seven healthy senior subjects (55–65 years old) and seven healthy young subjects (22–26 years old) were included in the research. Results: Changes in PWTT characterise appropriately the effect of cuff occlusion on BP measurement. Cuff occlusion affected PWTTHC and PWTTCF differently; it increased the former and decreased the latter. Increased PWTTHC reflects a less rigid arterial wall, resulting in an underestimation of BP. The changes in PWTT values are person-specific and not group-specific (patient, healthy senior, and healthy youth). Conclusion: Occlusion with the cuff is an excitation to the cardiovascular system, causing a temporary change in the dynamic properties of the arteries from the heart to the cuff. The change influences the result of indirect BP measurement. Arterial rigidity in the part proximal to the cuff can be characterized by PWTTHC, which provides different information about the arteries than the widely used PWTTHF.

Background: Non-invasive continuous blood pressure monitoring can provide an important reference and guidance for doctors wishing to analyze the physiological and pathological status of patients and to prevent and diagnose cardiovascular diseases in the clinical setting. Therefore, it is very important to explore a more accurate method of non-invasive continuous blood pressure measurement.Objective: To address the shortcomings of existing blood pressure measurement models based on pulse wave transit time or pulse wave parameters, a new method of non-invasive continuous blood pressure measurement - the GA-MIV-BP neural network model - is presented.Method: The mean impact value (MIV) method is used to select the factors that greatly influence blood pressure from the extracted pulse wave transit time and pulse wave parameters. These factors are used as inputs, and the actual blood pressure values as outputs, to train the BP neural network model. The individual parameters are then optimized using a genetic algorithm (GA) to establish the GA-MIV-BP neural network model.Results: Bland-Altman consistency analysis indicated that the measured and predicted blood pressure values were consistent and interchangeable.Conclusions: Therefore, this algorithm is of great significance to promote the clinical application of a non-invasive continuous blood pressure monitoring method. [ABSTRACT FROM AUTHOR]

Aims and Objectives: Cardiac output (CO) measurement is essential for many therapeutic decisions in anesthesia and critical care. Most available non-invasive CO measuring methods have an invasive component. We investigate "pulse wave transit time" (estimated continuous cardiac output [esCCO]) a method of CO measurement that has no invasive component to its use. Materials and Methods: After institutional ethical committee approval, 14 adult (21-85 years) patients undergoing surgery and requiring pulmonary artery catheter (PAC) for measuring CO, were included. Postoperatively CO readings were taken simultaneously with thermodilution (TD) via PAC and esCCO, whenever a change in CO was expected due to therapeutic interventions. Both monitoring methods were continued until patients′ discharge from the Intensive Care Unit and observer recording values using TD method was blinded to values measured by esCCO system. Results: Three hundred and one readings were obtained simultaneously from both methods. Correlation and concordance between the two methods was derived using Bland-Altman analysis. Measured values showed significant correlation between esCCO and TD ( r = 0.6, P < 0.001, 95% confidence limits of 0.51-0.68). Mean and (standard deviation) for bias and precision were 0.13 (2.27) L/min and 6.56 (2.19) L/min, respectively. The 95% confidence interval for bias was - 4.32 to 4.58 L/min and for precision 2.27 to10.85 L/min. Conclusions: Although, esCCO is the only true non-invasive continuous CO monitor available and even though its values change proportionately to TD method (gold standard) with the present degree of error its utility for clinical/therapeutic decision-making is questionable.

Objective: The aim of the study was to compare the esCCO Vismo (Nihon Kohden, Japan) monitor to the routinely used LiDCOrapid (LiDCO Group, Great Britain) monitor in patients undergoing abdominal surgery. Design: Observational study. Setting: General surgery operating theatres in a University Hospital. Materials and methods: ASA III patients scheduled for elective major abdominal surgery with expected operation duration over 90 minutes were included in the study. Cardiac output measurements by esCCO and LiDCOrapid were recorded before induction of anaesthesia, every 15 min throughout the surgery and after extubation. The agreement and trending ability of the two methods were tested with the Bland-Altman analysis and polar plot, respectively. Results: A total of 141 paired readings from 10 patients were collected. The Bland-Altman analysis corrected for repeated measures showed a bias of +1.2 l/min, limits of agreement ±2.6 l/min and percentage error of 57%. The direction of change between consecutive esCCO measurements and the corresponding LiDCOrapid measurements showed a concordance rate of 80%. In the polar plot, the angular bias was +11° with radial limits of agreement from -40° to +62°. Conclusion: Hemodynamic monitoring with esCCO yields cardiac output values different from those measured by LiDCOrapid. esCCO cannot be currently recommended as a reliable surrogate for LiDCOrapid. [ABSTRACT FROM AUTHOR]

A method of blood pressure estimation is proposed based on pulse waves collected by the cellphone cameras， referred to as multiparameter estimation of systolic blood pressure based on pulse waves (MBPP). Through the exercise test， some different timing pulse wave data and blood pressure data are obtained. Then， the pulse wave data are denoised and the acceleration pulse waves are calculated， to get the pulse wave transit time. And then， the characteristics of the pulse wave are calculated to get the heart rate. At last， the pulse wave transit time， heart rate and blood pressure can be selected to generate the linear fitting formula. Experimental results show that the MBPP proposed is a high accuracy method， and can be used to measure blood pressure. [ABSTRACT FROM AUTHOR]

We present a technique based on self-mixing interferometry for acquiring the pulse wave transit time (PWTT) and heartbeat. A signal processing method based on Continuous Wavelet Transform and Hilbert Transform is applied to extract potentially useful information in the self-mixing interference (SMI) signal, including PWTT and heartbeat. Then, some cardiovascular characteristics of the human body are easily acquired without retrieving the SMI signal by complicated algorithms. Experimentally, the PWTT is measured on the finger and the toe of the human body using double-path self-mixing interferometry. Experimental statistical data show the relation between the PWTT and blood pressure, which can be used to estimate the systolic pressure value by fitting. Moreover, the measured heartbeat shows good agreement with that obtained by a photoplethysmography sensor. The method that we demonstrate, which is based on self-mixing interferometry with significant advantages of simplicity, compactness and non-invasion, effectively illustrates the viability of the SMI technique for measuring other cardiovascular signals. [ABSTRACT FROM AUTHOR]

We present a case report of a 55-year-old lady who presented with progressive dysphagia and was diagnosed with a Kommerell′s aneurysm and a right-sided aortic arch. This case report outlines our management strategy and the challenges encountered during the perioperative period in a patient with this rare anomaly.

Patients with peripheral arterial disease may have elongated upstroke time in pulse waves in the lower extremities. We investigated upstroke time as a diagnostic tool of peripheral arterial disease and predictor of mortality in an elderly (≥60 years) Chinese population. We recorded pulse waves at the left and right ankles by pneumoplethysmography and calculated the percentage of upstroke time per cardiac cycle. Diagnostic accuracy was compared with the conventional ankle-brachial index method (n=4055) and computed tomographic angiography (34 lower extremities in 17 subjects). Upstroke time per cardiac cycle at baseline (mean±SD, 16.4%±3.1%) was significantly (P<0.0001) associated with ankle-brachial index in men (n=1803; r=-0.44) and women (n=2252; r=-0.32) and had an overall sensitivity and specificity of 86% and 80%, respectively, for the diagnosis of peripheral arterial disease (upstroke time per cardiac cycle, ≥21.7%) in comparison with computed tomographic angiography. During 5.9 years (median) of follow-up, all-cause and cardiovascular deaths occurred in 366 and 183 subjects, respectively. In adjusted Cox regression analyses, an upstroke time per cardiac cycle ≥21.7% (n=219; 5.4%) significantly (P<0.0001) predicted total and cardiovascular mortality. The corresponding hazard ratios were 1.98 (95% confidence interval, 1.48-2.65) and 2.29 (1.58-3.32), respectively, when compared with that of 2.10 (1.48-3.00) and 2.44 (1.57-3.79), respectively, associated with an ankle-brachial index of ≤0.90 (n=115; 2.8%). In conclusion, pulse waves in the lower extremities may behave as an accurate and ease of use diagnostic tool of peripheral arterial disease and predictor of mortality in the elderly. [ABSTRACT FROM AUTHOR]

Aims and Objectives: Cardiac output (CO) measurement is essential for many therapeutic decisions in anesthesia and critical care. Most available non-invasive CO measuring methods have an invasive component. We investigate "pulse wave transit time" (estimated continuous cardiac output [esCCO]) a method of CO measurement that has no invasive component to its use. Materials and Methods: After institutional ethical committee approval, 14 adult (21-85 years) patients undergoing surgery and requiring pulmonary artery catheter (PAC) for measuring CO, were included. Postoperatively CO readings were taken simultaneously with thermodilution (TD) via PAC and esCCO, whenever a change in CO was expected due to therapeutic interventions. Both monitoring methods were continued until patients' discharge from the Intensive Care Unit and observer recording values using TD method was blinded to values measured by esCCO system. Results: Three hundred and one readings were obtained simultaneously from both methods. Correlation and concordance between the two methods was derived using Bland-Altman analysis. Measured values showed significant correlation between esCCO and TD (r = 0.6, P < 0.001, 95% confidence limits of 0.51-0.68). Mean and (standard deviation) for bias and precision were 0.13 (2.27) L/min and 6.56 (2.19) L/min, respectively. The 95% confidence interval for bias was - 4.32 to 4.58 L/min and for precision 2.27 to10.85 L/min. Conclusions: Although, esCCO is the only true non-invasive continuous CO monitor available and even though its values change proportionately to TD method (gold standard) with the present degree of error its utility for clinical/therapeutic decision-making is questionable. [ABSTRACT FROM AUTHOR]

The inaccuracy of arterial waveform analysis for measuring continuos cardiac output (CCO) associated with changes in systemic vascular resistance (SVR) has been well documented. A new non-invasive continuous cardiac output monitoring system (esCCO) mainly utilizing pulse wave transit time (PWTT) in place of arterial waveform analysis has been developed. However, the trending ability of esCCO to measure cardiac output during changes in SVR remains unclear. After a previous multicenter study on esCCO measurement, we retrospectively identified two cases in which apparent changes in SVR developed in a short period during data collection. In each case, the trending ability of esCCO to measure cardiac output and time component of PWTT were analyzed. Recorded data suggest that the time component of PWTT may have a significant impact on the accuracy of estimating stroke volume during changes in SVR. However, further prospective clinical studies are required to test this hypothesis. [ABSTRACT FROM AUTHOR]

Eustachian valve (EV), a remnant of the right valve of sinus venosus in the right atrium can be puzzling. Often it is confused with Chiari network or atrial adhesions and is reported with unusual complications. We report a case of large EV impeding cannulation of inferior vena cava (IVC) during aortic valve replacement. Transesophageal echocardiography diagnosed the presence of large EV and warned of the difficulty with IVC cannulation and helped preparedness for an alternative plan during surgery.