Gregory S. H. Chan

Determinants of human cerebral pressure–flow velocity relationships: new insights from vascular modelling and Ca2+ channel blockade

Non‐technical summary  Brain function is critically dependent on the regulation of cerebral blood flow (CBF) by cerebral blood vessels. We show that a mechanical blood vessel property called compliance plays an important role in determining the way cerebral blood vessels respond to changes in blood pressure. These results enhance our knowledge of how cerebral blood vessels regulate CBF, which is critical to understanding the causes and effects of cerebrovascular diseases such as stroke and dementia.

Spectral analysis of finger photoplethysmographic waveform variability in a model of mild to moderate haemorrhage.

ObjectiveSlow fluctuations in cardiovascular signals such as heart rate variability (HRV) are believed to carry important clinical information. This study investigated whether frequency spectrum analysis of the finger photoplethysmographic waveform variability (PPGV) could characterize a hypovolaemic response by using a blood donation as a model of controlled mild to moderate haemorrhage.MethodsThis was a prospective, observational study carried out in a convenience sample of blood donors. Spectral analysis was performed on the finger infrared photoplethysmographic waveform and on the electrocardiogram- derived R–R intervals obtained from 43 healthy volunteers during blood donation. Spectral powers were calculated from low frequency (LF), mid frequency (MF) and high frequency (HF) bands of the spectrum of HRV and the coherence-weighted cross-spectrum of PPGV. Comparison was made between the four stages of blood donation: pre-donation (PRE), first half of donation (FIRST), second half of donation (SECOND) and post-donation (POST).ResultsA significant increase in the sum of the sympathetic-related MF and respiratory HF powers of finger PPGV (in mean-scaled units) was observed in SECOND and POST (P < 0.01). The post-donation increase in this PPGV spectral measure occurred in 77% of the subjects, which was higher than the percentage of subjects experiencing a blood pressure drop (71% or below). Normalized LF power of HRV showed a significant rise in SECOND (P < 0.01) but not in POST.ConclusionsSpectral analysis of finger PPGV may provide valuable information in addition to vital sign measurements in characterizing a hypovolaemic response. Given the limitations of the current blood loss model, further studies are required to assess the usefulness of finger PPGV for early haemorrhage detection in the clinical setting.

Non-invasive classification of severe sepsis and systemic inflammatory response syndrome using a nonlinear support vector machine: a preliminary study

Sepsis has been defined as the systemic response to infection in critically ill patients, with severe sepsis and septic shock representing increasingly severe stages of the same disease. Based on the non-invasive cardiovascular spectrum analysis, this paper presents a pilot study on the potential use of the nonlinear support vector machine (SVM) in the classification of the sepsis continuum into severe sepsis and systemic inflammatory response syndrome (SIRS) groups. 28 consecutive eligible patients attending the emergency department with presumptive diagnoses of sepsis syndrome have participated in this study. Through principal component analysis (PCA), the first three principal components were used to construct the SVM feature space. The SVM classifier with a fourth-order polynomial kernel was found to have a better overall performance compared with the other SVM classifiers, showing the following classification results: sensitivity = 94.44%, specificity = 62.50%, positive predictive value = 85.00%, negative predictive value = 83.33% and accuracy = 84.62%. Our classification results suggested that the combinatory use of cardiovascular spectrum analysis and the proposed SVM classification of autonomic neural activity is a potentially useful clinical tool to classify the sepsis continuum into two distinct pathological groups of varying sepsis severity.

Automatic detection of left ventricular ejection time from a finger photoplethysmographic pulse oximetry waveform: comparison with Doppler aortic measurement

Left ventricular ejection time (LVET) is a useful measure of ventricular performance and preload. The present study explores a novel method of continuous LVET monitoring using a noninvasive finger photoplethysmographic pulse oximetry waveform (PPG-POW). A method for the automatic beat-to-beat detection of LVET from the finger PPG-POW is presented based on a combination of derivative analysis, waveform averaging and rule-based logic. The performance of the detection method was evaluated on 13 healthy subjects during graded head-up tilt. Overall, the correlation between the PPG-POW derived LVET and the aortic flow derived LVET was high and significant (r = 0.897, p < 0.05). The bias was -14 +/- 14 ms (mean +/- SD), and the percentage error was 9.7%. Although these results would not be sufficient to satisfy the requirement for clinical evaluation of LVET when absolute accuracy was demanded, the strong correlation between the PPG-POW LVET and the aortic LVET on an intra-subject basis (r = 0.945 +/- 0.043, mean +/- SD) would support the application of PPG-POW to detect the directional change in LVET of an individual. This could be very useful for the early identification of progressive hypovolaemia or blood loss. The present study has demonstrated a promising approach to extract potentially useful information from a noninvasive, easy-to-obtain signal that could be readily acquired either from existing patient monitoring equipment or from inexpensive instrumentation. More extensive investigation is necessary to evaluate the applicability of the present approach in clinical care monitoring.

Frequency spectrum analysis of finger photoplethysmographic waveform variability during haemodialysis.

This study investigates the peripheral circulatory and autonomic response to volume withdrawal in haemodialysis based on spectral analysis of photoplethysmographic waveform variability (PPGV). Frequency spectrum analysis was performed on the baseline and pulse amplitude variabilities of the finger infrared photoplethysmographic (PPG) waveform and on heart rate variability extracted from the ECG signal collected from 18 kidney failure patients undergoing haemodialysis. Spectral powers were calculated from the low frequency (LF, 0.04-0.145 Hz) and high frequency (HF, 0.145-0.45 Hz) bands. In eight stable fluid overloaded patients (fluid removal of >2 L) not on alpha blockers, progressive reduction in relative blood volume during haemodialysis resulted in significant increase in LF and HF powers of PPG baseline and amplitude variability (P < 0.01), when expressed in mean-scaled units. The augmentation of LF powers in PPGV during haemodialysis may indicate the recovery and possibly further enhancement of peripheral sympathetic vascular modulation subsequent to volume unloading, whilst the increase in respiratory HF power in PPGV is most likely a sign of preload reduction. Spectral analysis of finger PPGV may provide valuable information on the autonomic vascular response to blood volume reduction in haemodialysis, and can be potentially utilized as a non-invasive tool for assessing peripheral circulatory control during routine dialysis procedure.

Recent advances in the monitoring and control of haemodynamic variables during haemodialysis: a review

The human body possesses a unique set of organs that are responsible for providing homeostatic balance to the bodys fluids. Of these, the kidneys regulate fluid and electrolyte balance in order to maintain the intracellular and extracellular fluid volumes and ion composition within tight limits. When kidneys fail to function normally, fluid is retained and several ions and solutes accumulate. The consequences may be life threatening. Many kidney failure patients rely on haemodialysis (HD) as a life sustaining therapy to remove the waste products and excess fluid from the circulating blood. HD is based on the principle of diffusion of solutes and ultrafiltration of fluid across a semi-permeable membrane. Fluid removal during HD results in relative hypovolaemia during which the stability of a patient relies on compensatory mechanisms to maintain blood pressure (BP). The major compensatory mechanisms include sympathetic nervous system activation of peripheral vasoconstriction together with modest heart rate acceleration to ensure the haemodynamic stability of the patient. Over the years, many monitoring tools have been developed in the hope of predicting intra-dialytic hypotensive episodes. Similarly many methods have been utilized to prevent dialysis-induced complications: ultrafiltration and dialysate sodium profiling, varying ultrafiltration based on frequent BP measurements, etc. This paper provides a comprehensive review of those monitoring and control tools. It starts with a brief introduction to human kidneys and dialysis for non-specialized readers. The paper then reviews the monitoring tools that have been applied to assess the physiological response of patients during HD. This is followed by control techniques used to prevent dialysis-induced complications.

Contribution of arterial Windkessel in low-frequency cerebral hemodynamics during transient changes in blood pressure

The Windkessel properties of the vasculature are known to play a significant role in buffering arterial pulsations, but their potential importance in dampening low-frequency fluctuations in cerebral blood flow has not been clearly examined. In this study, we quantitatively assessed the contribution of arterial Windkessel (peripheral compliance and resistance) in the dynamic cerebral blood flow response to relatively large and acute changes in blood pressure. Middle cerebral artery flow velocity (MCA(V); transcranial Doppler) and arterial blood pressure were recorded from 14 healthy subjects. Low-pass-filtered pressure-flow responses (<0.15 Hz) during transient hypertension (intravenous phenylephrine) and hypotension (intravenous sodium nitroprusside) were fitted to a two-element Windkessel model. The Windkessel model was found to provide a superior goodness of fit to the MCA(V) responses during both hypertension and hypotension (R² = 0.89 ± 0.03 and 0.85 ± 0.05, respectively), with a significant improvement in adjusted coefficients of determination (P < 0.005) compared with the single-resistance model (R² = 0.62 ± 0.06 and 0.61 ± 0.08, respectively). No differences were found between the two interventions in the Windkessel capacitive and resistive gains, suggesting similar vascular properties during pressure rise and fall episodes. The results highlight that low-frequency cerebral hemodynamic responses to transient hypertension and hypotension may include a significant contribution from the mechanical properties of vasculature and, thus, cannot solely be attributed to the active control of vascular tone by cerebral autoregulation. The arterial Windkessel should be regarded as an important element of dynamic cerebral blood flow modulation during large and acute blood pressure perturbation.

Fundamental relationships between blood pressure and cerebral blood flow in humans

Cerebral blood flow responses to transient blood pressure challenges are frequently attributed to cerebral autoregulation (CA), yet accumulating evidence indicates vascular properties like compliance are also influential. We hypothesized that middle cerebral blood velocity (MCAv) dynamics during or following a transient blood pressure perturbation can be accurately explained by the windkessel mechanism. Eighteen volunteers underwent blood pressure manipulations, including bilateral thigh-cuff deflation and sit-to-stand maneuvers under normocapnic and hypercapnic (5% CO2) conditions. Pressure-flow recordings were analyzed using a windkessel analysis approach that partitions the frequency-dependent resistance and compliance contributions to MCAv dynamics. The windkessel was typically able to explain more than 50% of the MCAv variance, as indicated by R(2) values for both the flow recovery and postrecovery phase. The most consistent predictors of MCAv dynamics under the control condition were the windkessel capacitive gain and high-frequency resistive gain. However, there were significant interindividual variations in the composition of windkessel predictors. Hypercapnia consistently reduced the capacitive gain and enhanced the low-frequency (0.04-0.20 Hz) resistive gain for both thigh-cuff deflation and sit-to-stand trials. These findings indicate that 1) MCAv dynamics during acute transient hypotension challenges are dominated by cerebrovascular windkessel properties independent of CA; 2) there is significant heterogeneity in windkessel properties between individuals; and 3) hemodynamic effects of hypercapnia during transient blood pressure challenges primarily reflect changes in windkessel properties rather than pure CA impairment.

Spontaneous fluctuations in the peripheral photoplethysmographic waveform: roles of arterial pressure and muscle sympathetic nerve activity.

Assessment of spontaneous slow waves in the peripheral blood volume using the photoplethysmogram (PPG) has shown potential clinical value, but the physiological correlates of these fluctuations have not been fully elucidated. This study addressed the contribution of arterial pressure and muscle sympathetic nerve activity (MSNA) in beat-to-beat PPG variability in resting humans under spontaneous breathing conditions. Peripheral PPG waveforms were measured from the fingertip, earlobe, and toe in young and healthy individuals (n = 13), together with the arterial pressure waveform, electrocardiogram, respiration, and direct measurement of MSNA by microneurography. Cross-spectral coherence analysis revealed that among the PPG waveforms, low-frequency fluctuations (0.04-0.15 Hz) in the ear PPG had the highest coherence with arterial pressure (0.71 ± 0.15) and MSNA (0.44 ± 0.18, with a peak of 0.71 ± 0.16 at 0.10 ± 0.03 Hz). The normalized midfrequency powers (0.08-0.15 Hz), with an emphasis on the 0.1-Hz region, were positively correlated between MSNA and the ear PPG (r = 0.77, P = 0.002). Finger and toe PPGs had lower coherence with arterial pressure (0.35 ± 0.10 and 0.30 ± 0.11, respectively) and MSNA (0.33 ± 0.10 and 0.26 ± 0.10, respectively) in the LF band but displayed higher coherence between themselves (0.54 ± 0.09) compared with the ear (P < 0.001), which may suggest the dominance of regional vasomotor activities and a common sympathetic influence in the glabrous skin. These findings highlight the differential mechanisms governing PPG waveform fluctuations across different body sites. Spontaneous PPG variability in the ear includes a major contribution from arterial pressure and MSNA, which may provide a rationale for its clinical utility.

Changes in left ventricular ejection time and pulse transit time derived from finger photoplethysmogram and electrocardiogram during moderate haemorrhage

Objectives:  Early identification of haemorrhage is difficult when a bleeding site is not apparent. This study explored the potential use of the finger photoplethysmographic (PPG) waveform derived left ventricular ejection time (LVETp) and pulse transit time (PTT) for detecting blood loss, by using blood donation as a model of controlled mild to moderate haemorrhage.