Effect of age and gender on ventricular-arterial coupling estimated using a non-invasive technique.

BACKGROUND: Left ventricular-arterial coupling is assessed as the ratio of left ventricular end-systolic elastance (Ees) to arterial elastance (Ea). Previous studies have introduced non-invasive estimations of Ees/Ea. It requires only four variables, namely pre-ejection period, ejection time, end-systolic pressure and diastolic pressure. The aims of the present study were to clarify the reference values of Ees/Ea estimated using the noninvasive technique, and to investigate the effects of age and gender on Ees/Ea in healthy subjects. METHODS: This retrospective study utilized data from healthy, 30-79-year-old subjects. We recorded electrocardiogram, phonocardiogram, and brachial arterial pulse waves simultaneously using the vascular screening system, and used the observed variables to calculate Ees/Ea. We separated subjects into five groups according to their age and compared Ees/Ea among the different age groups. RESULTS: The study included 2114 males and 2292 females. Ees/Ea ranged from 1.87 to 2.04 in males, and 1.98 to 2.32 in females. We observed no age-related differences in Ees/Ea in males (p = 0.10), and significant differences in females (p < 0.001). Ees/Ea in males was not different compared to those in females in 60-69-year-old group (p = 0.92). Whereas Ees/Ea was higher in females compared to those in males in the other age groups. The differences between medians of Ees/Ea in males and those in females were 0.45 (p < 0.001), 0.24 (p < 0.001), 0.13 (p = 0.01), and 0.13 (p = 0.03) in 30-39, 40-49, 50-59, and 70-79-year-old age groups, respectively. CONCLUSIONS: We clarified the reference values of Ees/Ea in healthy subjects. The effect of age on Ees/Ea is different in males and females, although Ees/Ea is maintained within a relatively narrow range in all subjects.

Changes in EEG frequency characteristics during sevoflurane general anesthesia: feature extraction by variational mode decomposition.

Mode decomposition is a method for extracting the characteristic intrinsic mode function (IMF) from various multidimensional time-series signals. Variational mode decomposition (VMD) searches for IMFs by optimizing the bandwidth to a narrow band with the [Formula: see text] norm while preserving the online estimated central frequency. In this study, we applied VMD to the analysis of electroencephalogram (EEG) recorded during general anesthesia. Using a bispectral index monitor, EEGs were recorded from 10 adult surgical patients (the median age: 47.0, and the percentile range: 27.0-59.3 years) who were anesthetized with sevoflurane. We created an application named EEG Mode Decompositor, which decomposes the recorded EEG into IMFs and displays the Hilbert spectrogram. Over the 30-min recovery from general anesthesia, the median (25-75 percentile range) bispectral index increased from 47.1 (42.2-50.4) to 97.4 (96.5-97.6), and the central frequencies of IMF-1 showed a significant change from 0.4 (0.2-0.5) Hz to 0.2 (0.1-0.3) Hz. IMF-2, IMF-3, IMF-4, IMF-5, and IMF-6 increased significantly from 1.4 (1.2-1.6) Hz to 7.5 (1.5-9.3) Hz, 6.7 (4.1-7.6) Hz to 19.4 (6.9-20.0) Hz, 10.9 (8.8-11.4) Hz to 26.4 (24.2-27.2) Hz, 13.4 (11.3-16.6) Hz to 35.6 (34.9-36.1) Hz, and 12.4 (9.7-18.1) Hz to 43.2 (42.9-43.4) Hz, respectively. The characteristic frequency component changes in specific IMFs during emergence from general anesthesia were visually captured by IMFs derived using VMD. EEG analysis by VMD is useful for extracting distinct changes during general anesthesia.

Time-trend analysis of the center frequency of the intrinsic mode function from the Hilbert-Huang transform of electroencephalography during general anesthesia: a retrospective observational study.

BACKGROUND: Anesthesiologists are required to maintain an optimal depth of anesthesia during general anesthesia, and several electroencephalogram (EEG) processing methods have been developed and approved for clinical use to evaluate anesthesia depth. Recently, the Hilbert-Huang transform (HHT) was introduced to analyze nonlinear and nonstationary data. In this study, we assessed whether the changes in EEG characteristics during general anesthesia that are analyzed by the HHT are useful for monitoring the depth of anesthesia. METHODS: This retrospective observational study enrolled patients who underwent propofol anesthesia. Raw EEG signals were obtained from a monitor through a previously developed software application. We developed an HHT analyzer to decompose the EEG signal into six intrinsic mode functions (IMFs) and estimated the instantaneous frequencies (HHT_IF) for each IMF. Changes over time in the raw EEG waves and parameters such as HHT_IF, BIS, spectral edge frequency 95 (SEF95), and electromyogram parameter (EMGlow) were assessed, and a Gaussian process regression model was created to assess the association between BIS and HHT_IF. RESULTS: We analyzed EEG signals from 30 patients. The beta oscillation frequency range (13-25 Hz) was detected in IMF1 and IMF2 during the awake state, then after loss of consciousness, the frequency decreased and alpha oscillation (8-12 Hz) was detected in IMF2. At the emergence phase, the frequency increased and beta oscillations were detected in IMF1, IMF2, and IMF3. BIS and EMGlow changed significantly during the induction and emergence phases, whereas SEF95 showed a wide variability and no significant changes during the induction phase. The root mean square error between the observed BIS values and the values predicted by a Gaussian process regression model ranged from 4.69 to 9.68. CONCLUSIONS: We applied the HHT to EEG analyses during propofol anesthesia. The instantaneous frequency in IMF1 and IMF2 identified changes in EEG characteristics during induction and emergence from general anesthesia. Moreover, the HHT_IF in IMF2 showed strong associations with BIS and was suitable for depicting the alpha oscillation. Our study suggests that the HHT is useful for monitoring the depth of anesthesia.

A Pilot Estimation of Ventricular-Arterial Coupling Using a Vascular Screening Device (VaSera®).

BACKGROUND: Non-invasive cardiovascular assessment has become an alternative to invasive techniques. VaSera®, a vascular screening device, measures arterial stiffness with the cardio-ankle vascular index (CAVI); it also measures cardiophysiological variables of ejection time (ET) and pre-ejection period (PEP). We aimed to apply the parameters obtained by VaSera® to estimate heart function based on left ventricular end-systolic elastance/arterial elastance (Ees/Ea) and to assess the minimal required number of measurements for estimation. METHODS: We conducted an experimental laboratory study for healthy volunteers. Using the previously established formula, the Ees/Ea value of each participant was estimated using ET and PEP values measured by VaSera®. The intraclass correlation coefficient (ICC) assessed the minimum required number of measurements. Concordance correlation coefficient (CCC) and Bland and Altman analysis assessed variation of Ees/Ea estimation against the trimmed average. RESULTS: A total of 660 measurements from 132 participants were included. The Ees/Ea estimates from the VaSera® were 1.5 [1.2, 1.9]. The ICC for Ees/Ea was 0.71 (95% confidence interval: 0.65-0.77), suggesting that four measurements were required. The CCC between the trimmed average of Ees/Ea and the mean of four Ees/Ea estimates was 0.99. Bland and Altman analysis showed excellent agreement for the mean of four Ees/Ea estimates and the trimmed average of Ees/Ea. CONCLUSIONS: For screening of heart failure, the Ees/Ea estimated using non-invasive vascular-stiffness assessment device would be tolerable and four sequential measurements were required.

Power spectrum and spectrogram of EEG analysis during general anesthesia: Python-based computer programming analysis.

The commonly used principle for measuring the depth of anesthesia involves changes in the frequency components of the electroencephalogram (EEG) under general anesthesia. Therefore, it is essential to construct an effective spectrum and spectrogram to analyze the relationship between the depth of anesthesia and the EEG frequency during general anesthesia. This paper reviews the computer programming techniques for analyzing the spectrum and spectrogram derived from a single-channel EEG recorded during general anesthesia. A periodogram is obtained by repeating a Fourier transform on EEG segments separated by short time intervals, but spectral leakage (i.e., dissociation from the true spectrum) occurs as a consequence of unnatural segmentation and noise. While offsetting the securing of the dynamic range, practical analyses of the adaptation of the window function are explained. Finally, the multitaper method, which can suppress artifacts caused by the edges of the analysis segments, suppress noise, and probabilistically infer values that are close to the real power spectral density, is explained using practical examples of the analysis. All analyses were performed and all graphs plotted using Python under Jupyter Notebook. The analyses demonstrated the effectiveness of Python-based programming under the integrated development environment Jupyter Notebook for constructing an effective spectrum and spectrogram for analyzing the relationship between the depth of anesthesia and EEG frequency analysis in general anesthesia.

Relationship Between the Ambulatory Arterial Stiffness Index and the Lower Limit of Cerebral Autoregulation During Cardiac Surgery.

BACKGROUND: Pulse pressure, the ambulatory arterial stiffness index (AASI), and the symmetric AASI are established predictors of adverse cardiovascular outcomes. However, little is known about their relationship to cerebral autoregulation. This study evaluated whether these markers of vascular properties relate to the lower limit of cerebral autoregulation (LLA). METHODS AND RESULTS: The LLA was determined during cardiac surgery with transcranial Doppler ultrasonography in 181 patients. All other variables were calculated from continuous intraoperative readings obtained before cardiopulmonary bypass. The LLA varied directly with the AASI (ß=3.12 per 0.1 change in AASI, P<0.001) and to a lesser extent the symmetric AASI (ß=2.02 per 0.1 change in symmetric AASI, P≤0.022), while peripheral pulse pressure was not significantly related (ß=0.0, P>0.99). Logistic regression revealed that the likelihood of LLA being >65 mm Hg increased by 50% (95% confidence interval, 11%-102%, P=0.008) for every 0.1 increase in the AASI. The AASI was able to predict a LLA above certain thresholds (area under the curve receiver operating characteristic for AASI predicting an LLA >65 mm Hg: 0.60; 95% confidence interval, 0.51%-0.68%, P=0.043). Incorporating additional variables improved the model's predictive ability (area under the curve for AASI predicting a LLA >65 mm Hg: 0.75; 95% confidence interval, 0.68-0.82, P=0.036). CONCLUSIONS: These data indicate that the LLA is related to the mechanical properties of the vasculature as represented by the AASI. The AASI can be used to predict LLA threshold levels during cardiac surgery. It is now possible to link elevations in the LLA with an increased AASI as determined from readily accessible intraoperative variables.

Pulse wave travel distance as a novel marker of ventricular-arterial coupling.

Each stroke volume ejected by the heart is distributed along the arterial system as a pressure waveform. How far the front of the pressure waveform travels within the arterial system depends both on the pulse wave velocity (PWV) and the ejection time (ET). We tested the hypothesis that ET and PWV are coupled together, in order to produce a pulse wave travel distance (PWTD = PWV × ET) which would match the distance from the heart to the most distant site in the arterial system. The study was conducted in 11 healthy volunteers. We recorded lead II of the ECG along with pulse plethysmography at ear, finger and toe. The ET at the ear and pulse arrival time to each peripheral site were extracted. We then calculated PWV followed by PWTD for each location. Taken into account the individual subject variability PWTDToe in the supine position was 153 cm (95% CI 146-160 cm). It was not different from arterial pathway distance from the heart to the toe (D Toe 153 cm). The PWTDFinger and PWTDEar were longer than the distance from the heart to the finger and ear irrespective of body position. ETEar and PWVToe appear to be coupled in healthy subjects to produce a PWTD that is roughly equivalent to the arterial pathway distance to the toe. We propose that PWTD should be evaluated further to test its potential as a noninvasive parameter of ventricular-arterial coupling in subjects with cardiovascular diseases.

Difference between ejection times measured at two different peripheral locations as a novel marker of vascular stiffness.

Pulse wave velocity (PWV) has been recommended as an arterial damage assessment tool and a surrogate of arterial stiffness. However, the current technology does not allow to measure PWV both continuously and in real-time. We reported previously that peripherally measured ejection time (ET) overestimates ET measured centrally. This difference in ET is associated with the inherent vascular properties of the vessel. In the current study we examined ETs derived from plethysmography simultaneously at different peripheral locations and examined the influence of the underlying arterial properties on ET prolongation by changing the subject's position. We calculated the ET difference between two peripheral locations (ΔET) and its corresponding PWV for the same heartbeat. The ΔET increased with a corresponding decrease in PWV. The difference between ΔET in the supine and standing (which we call ET index) was higher in young subjects with low mean arterial pressure and low PWV. These results suggest that the difference in ET between two peripheral locations in the supine vs standing positions represents the underlying vascular properties. We propose ΔET in the supine position as a potential novel real-time continuous and non-invasive parameter of vascular properties, and the ET index as a potential non-invasive parameter of vascular reactivity.

A Pulse Wave Velocity Based Method to Assess the Mean Arterial Blood Pressure Limits of Autoregulation in Peripheral Arteries.

Background: Constant blood flow despite changes in blood pressure, a phenomenon called autoregulation, has been demonstrated for various organ systems. We hypothesized that by changing hydrostatic pressures in peripheral arteries, we can establish these limits of autoregulation in peripheral arteries based on local pulse wave velocity (PWV). Methods: Electrocardiogram and plethysmograph waveforms were recorded at the left and right index fingers in 18 healthy volunteers. Each subject changed their left arm position, keeping the right arm stationary. Pulse arrival times (PAT) at both fingers were measured and used to calculate PWV. We calculated ΔPAT (ΔPWV), the differences between the left and right PATs (PWVs), and compared them to the respective calculated blood pressure at the left index fingertip to derive the limits of autoregulation. Results: ΔPAT decreased and ΔPWV increased exponentially at low blood pressures in the fingertip up to a blood pressure of 70 mmHg, after which changes in ΔPAT and ΔPWV were minimal. The empirically chosen 20 mmHg window (75-95 mmHg) was confirmed to be within the autoregulatory limit (slope = 0.097, p = 0.56). ΔPAT and ΔPWV within a 20 mmHg moving window were not significantly different from the respective data points within the control 75-95 mmHg window when the pressure at the fingertip was between 56 and 110 mmHg for ΔPAT and between 57 and 112 mmHg for ΔPWV. Conclusions: Changes in hydrostatic pressure due to changes in arm position significantly affect peripheral arterial stiffness as assessed by ΔPAT and ΔPWV, allowing us to estimate peripheral autoregulation limits based on PWV.

The impact of posture on the cardiac depolarization and repolarization phases of the QT interval in healthy subjects.

BACKGROUND: Postural changes affect both heart rate and the QT interval. OBJECTIVE: To investigate the effects of postural changes on the depolarization and repolarization phases of the QT interval. METHODS: A three lead ECG from 12 healthy young volunteers was recorded in the standing, sitting and in the supine positions. For the purpose of this study, we defined the depolarization phase as the QRS complex plus the ST segment and the repolarization phase as the duration of the T wave. RESULTS: QTc did not change with changes in position. The ratio of the duration of the depolarization phase to the repolarization phase was higher in the supine position (0.98±0.13) compared to the standing position (0.83±0.17). CONCLUSIONS: The origin of the T wave moves closer to the QRS complex during standing compared to the supine position. The observed changes are mainly due to shortening of the ST segment during standing compared to supine position.

Ejection time: influence of hemodynamics and site of measurement in the arterial tree.

The left ventricular ejection time is routinely measured from a peripheral arterial waveform. However, the arterial waveform undergoes constant transformation as the pulse wave propagates along the arterial tree. Our goal was to determine if the left ventricular ejection time measured peripherally in the arterial tree accurately reflected the ejection time measured through the aortic valve. Moreover, we examined/accessed the modulating influence of hemodynamics on ejection time measurements. Continuous wave Doppler waveform images through the aortic valve and the simultaneously obtained radial artery pressure waveforms were analyzed to determine central and peripheral ejection times, respectively. The peripheral ejection time was significantly longer than the simultaneously measured central ejection time (174.5±25.2 ms vs. 120.7±14.4 ms; P<0.0001; 17.4±8.7% increase). Moreover, the ejection time prolongation was accentuated at lower blood pressures, lower heart rate and lower pulse wave velocity. The time difference between centrally and peripherally measured ejection times likely reflects intrinsic vascular characteristics. Moreover, given that the ejection time also depends on blood pressure, heart rate and pulse wave velocity, peripherally measured ejection times might need to be adjusted to account for changes in these variables.

Noninvasive Assessment of the Effect of Position and Exercise on Pulse Arrival to Peripheral Vascular Beds in Healthy Volunteers.

Background: The effects of position and exercise on pulse wave distribution across a healthy, compliant arterial tree are not fully understood. We studied the effects of exercise and position on the pattern of pulse arrival times (PATs) in healthy volunteers. Moreover, we compared the pulse arrival time ratios to the respective distance ratios between different locations. Methods: Thirteen young healthy volunteers were studied, using an electrocardiogram and plethysmograph to simultaneously record pulse wave arrival at the ear lobe, index finger and big toe. We compared the differences in PAT between each location at rest and post-exercise in the supine, sitting, and standing position. We also compared the PAT ratio (toe/ear, toe/finger, and finger/ear) to the corresponding pulse path distance ratios. Results: PAT was shortest at the ear then finger and longest at the toe regardless of position or exercise status. PATs were shorter post-exercise compared to rest. When transitioning from a standing to sitting or supine position, PAT to the ear decreased, while the PAT to the toe increased, and PAT to the finger didn't significantly change. PAT ratios were significantly smaller than predicted by the path distance ratios regardless of position or exercise status. Conclusions: Exercise makes PATs shorter. Standing position decrease PAT to the toe and increase to the ear. We conclude that PAT and PAT ratio represent the arterial vascular tree properties as surely as pulse transit time and pulse wave velocity.

Pilot Study: Estimation of Stroke Volume and Cardiac Output from Pulse Wave Velocity.

BACKGROUND: Transesophageal echocardiography (TEE) is increasingly replacing thermodilution pulmonary artery catheters to assess hemodynamics in patients at high risk for cardiovascular morbidity. However, one of the drawbacks of TEE compared to pulmonary artery catheters is the inability to measure real time stroke volume (SV) and cardiac output (CO) continuously. The aim of the present proof of concept study was to validate a novel method of SV estimation, based on pulse wave velocity (PWV) in patients undergoing cardiac surgery. METHODS: This is a retrospective observational study. We measured pulse transit time by superimposing the radial arterial waveform onto the continuous wave Doppler waveform of the left ventricular outflow tract, and calculated SV (SVPWV) using the transformed Bramwell-Hill equation. The SV measured by TEE (SVTEE) was used as a reference. RESULTS: A total of 190 paired SV were measured from 28 patients. A strong correlation was observed between SVPWV and SVTEE with the coefficient of determination (R2) of 0.71. A mean difference between the two (bias) was 3.70 ml with the limits of agreement ranging from -20.33 to 27.73 ml and a percentage error of 27.4% based on a Bland-Altman analysis. The concordance rate of two methods was 85.0% based on a four-quadrant plot. The angular concordance rate was 85.9% with radial limits of agreement (the radial sector that contained 95% of the data points) of ± 41.5 degrees based on a polar plot. CONCLUSIONS: PWV based SV estimation yields reasonable agreement with SV measured by TEE. Further studies are required to assess its utility in different clinical situations.

A successfully treated case of cardiac arrest after Caesarean section complicated by pheochromocytoma crisis and amniotic fluid embolism.

Both pheochromocytoma and amniotic fluid embolism (AFE) are important causes of maternal mortality. We present a case of a 29-year-old woman who developed cardiac arrest after Caesarean section, complicated by both pheochromocytoma crisis and AFE. After resuscitation, the patient developed multiple organ dysfunction, rhabdomyolysis and disseminated intravascular coagulation (DIC). After institution of multidisciplinary interventions (including the use of an intra-aortic balloon pump, extracorporeal membrane oxygenation, continuous hemodiafiltration, and neuroprotective therapeutic hypothermia) the patient made a full recovery without any apparent neurological deficit.

The Effects of Hemodynamic Changes on Pulse Wave Velocity in Cardiothoracic Surgical Patients.

The effect of blood pressure on pulse wave velocity (PWV) is well established. However, PWV variability with acute hemodynamic changes has not been examined in the clinical setting. The aim of the present study is to investigate the effect of hemodynamic changes on PWV in patients who undergo cardiothoracic surgery. Using data from 25 patients, we determined blood pressure (BP), heart rate (HR), and the left ventricular outflow tract (LVOT) velocity-time integral. By superimposing the radial arterial waveform on the continuous wave Doppler waveform of the LVOT, obtained by transesophageal echo, we were able to determine pulse transit time and to calculate PWV, stroke volume (SV), cardiac output (CO), and systemic vascular resistance (SVR). Increases in BP, HR, and SVR were associated with higher values for PWV. In contrast increases in SV were associated with decreases in PWV. Changes in CO were not significantly associated with PWV.