New Hemodynamic Parameters in Peri-Operative and Critical Care-Challenges in Translation.

Hemodynamic monitoring technologies are evolving continuously-a large number of bedside monitoring options are becoming available in the clinic. Methods such as echocardiography, electrical bioimpedance, and calibrated/uncalibrated analysis of pulse contours are becoming increasingly common. This is leading to a decline in the use of highly invasive monitoring and allowing for safer, more accurate, and continuous measurements. The new devices mainly aim to monitor the well-known hemodynamic variables (e.g., novel pulse contour, bioreactance methods are aimed at measuring widely-used variables such as blood pressure, cardiac output). Even though hemodynamic monitoring is now safer and more accurate, a number of issues remain due to the limited amount of information available for diagnosis and treatment. Extensive work is being carried out in order to allow for more hemodynamic parameters to be measured in the clinic. In this review, we identify and discuss the main sensing strategies aimed at obtaining a more complete picture of the hemodynamic status of a patient, namely: (i) measurement of the circulatory system response to a defined stimulus; (ii) measurement of the microcirculation; (iii) technologies for assessing dynamic vascular mechanisms; and (iv) machine learning methods. By analyzing these four main research strategies, we aim to convey the key aspects, challenges, and clinical value of measuring novel hemodynamic parameters in critical care.

Automated detection and classification of patient-ventilator asynchrony by means of machine learning and simulated data.

BACKGROUND AND OBJECTIVE: Mechanical ventilation is a lifesaving treatment for critically ill patients in an Intensive Care Unit (ICU) or during surgery. However, one potential harm of mechanical ventilation is related to patient-ventilator asynchrony (PVA). PVA can cause discomfort to the patient, damage to the lungs, and an increase in the length of stay in the ICU and on the ventilator. Therefore, automated detection algorithms are being developed to detect and classify PVAs, with the goal of optimizing mechanical ventilation. However, the development of these algorithms often requires large labeled datasets; these are generally difficult to obtain, as their collection and labeling is a time-consuming and labor-intensive task, which needs to be performed by clinical experts. METHODS: In this work, we aimed to develop a computer algorithm for the automatic detection and classification of PVA. The algorithm employs a neural network for the detection of the breath of the patient. The development of the algorithm was aided by simulations from a recently published model of the patient-ventilator interaction. RESULTS: The proposed method was effective, providing an algorithm with reliable detection and classification results of over 90% accuracy. Besides presenting a detection and classification algorithm for a variety of PVAs, here we show that using simulated data in combination with clinical data increases the variability in the training dataset, leading to a gain in performance and generalizability. CONCLUSIONS: In the future, these algorithms can be utilized to gain a better understanding of the clinical impact of PVAs and help clinicians to better monitor their ventilation strategies.

On the value of MRI for improved understanding of cuff-based oscillometric measurements.

Blood pressure (BP) is a key parameter in critical care and in cardiovascular disease management. BP is typically measured via cuff-based oscillometry. This method is highly inaccurate in hypo- and hypertensive patients. Improvements are difficult to achieve because oscillometry is not yet fully understood; many assumptions and uncertainties exist in models describing the process by which arterial pulsations become expressed within the cuff signal. As a result, it is also difficult to estimate other parameters via the cuff such as arterial stiffness, cardiac output and pulse wave velocity (PWV)-BP calibration. Many research modalities have been employed to study oscillometry (ultrasound, computer simulations, ex-vivo studies, measurement of PWV, mechanical analysis). However, uncertainties remain; additional investigation modalities are needed. In this study, we explore the extent to which MRI can help investigate oscillometric assumptions. Four healthy volunteers underwent a number of MRI scans of the upper arm during cuff inflation. It is found that MRI provides a novel perspective over oscillometry; the artery, surrounding tissue, veins and the cuff can be simultaneously observed along the entire length of the upper arm. Several existing assumptions are challenged: tissue compression is not isotropic, arterial transmural pressure is not uniform along the length of the cuff and propagation of arterial pulsations through tissue is likely impacted by patient-specific characteristics (vasculature position and tissue composition). Clinical Relevance- The cuff interaction with the vasculature is extremely complex; existing models are oversimplified. MRI is a valuable tool for further development of cuff-based physiological measurements.

Modulation of pulse travel and blood flow during cuff inflation- An experimental case study.

The blood pressure (BP) cuff can be used to modulate blood flow and propagation of pressure pulse along the artery. In our previous work, we researched methods to adapt cuff modulation techniques for pulse transit time vs. BP calibration and for measurement of other hemodynamic indices of potential interest to critical care, such as arterial compliance. A model characterized the response of the vasculature located directly under the cuff, but assumed that no significant changes occur in the distal vasculature.This study has been tailored to gain insights into the response of distal BP and pulse transit time to cuff inflation. Invasive BP data collected downstream from the cuff demonstrates that highly dynamic processes occur in the distal arm during cuff inflation. Mean arterial pressure increases in the distal artery by up to 20 mmHg, leading to a decrease in pulse transit time of up to 20 ms. Clinical Relevance: Such significant changes need to be taken into account in order to improve non-invasive BP estimations and to enable inference of other hemodynamic parameters from vasculature response to cuff inflation. A simple model is developed in order to reproduce the observed behaviors. The lumped-parameter model demonstrates opportunities for cuff modulation measurements which can reveal information on parameters such as systemic resistance, distal arterial, venous compliances and artery-vein interaction.

Modulation of Pulse Propagation and Blood Flow via Cuff Inflation-New Distal Insights.

In standard critical care practice, cuff sphygmomanometry is widely used for intermittent blood pressure (BP) measurements. However, cuff devices offer ample possibility of modulating blood flow and pulse propagation along the artery. We explore underutilized arrangements of sensors involving cuff devices which could be of use in critical care to reveal additional information on compensatory mechanisms. In our previous work, we analyzed the response of the vasculature to occlusion perturbations by means of observations obtained non-invasively. In this study, our aim is to (1) acquire additional insights by means of invasive measurements and (2) based on these insights, further develop cuff-based measurement strategies. Invasive BP experimental data is collected downstream from the cuff in two patients monitored in the OR. It is found that highly dynamic processes occur in the distal arm during cuff inflation. Mean arterial pressure increases in the distal artery by 20 mmHg, leading to a decrease in pulse transit time by 20 ms. Previous characterizations neglected such distal vasculature effects. A model is developed to reproduce the observed behaviors and to provide a possible explanation of the factors that influence the distal arm mechanisms. We apply the new findings to further develop measurement strategies aimed at acquiring information on pulse arrival time vs. BP calibration, artery compliance, peripheral resistance, artery-vein interaction.

A modelling framework for assessment of arterial compliance by fusion of oscillometry and pulse wave velocity information.

BACKGROUND AND OBJECTIVES: Measurement of arterial compliance is recognized as important for clinical use and for enabling better understanding of circulatory system regulation mechanisms. Estimation of arterial compliance involves either a direct measure of the ratio between arterial volume and pressure changes or an inference from the pulse wave velocity (PWV). In this study we demonstrate an approach to assess arterial compliance by fusion of these two information sources. The approach is based on combining oscillometry as used for blood pressure inference and PWV measurements based on ECG/PPG. Enabling reliable arterial compliance measurements will contribute to the understanding of regulation mechanisms of the arterial tree, possibly establishing arterial compliance as a key measure relevant in hemodynamic monitoring. METHODS: A measurement strategy, a physiological model, and a framework based on Bayesian principles are developed for measuring changes in arterial compliance based on combining oscillometry and PWV data. A simulation framework is used to study and validate the algorithm and measurement principle in detail, motivated by previous experimental findings. RESULTS: Simulations demonstrate the possibility of inferring arterial compliance via fusion of simultaneously acquired volume/pressure relationships and PWV data. In addition, the simulation framework demonstrates how Bayesian principles can be used to handle low signal - to - noise ratio and partial information loss. CONCLUSIONS: The developed simulation framework shows the feasibility of the proposed approach for assessment of arterial compliance by combining multiple data sources. This represents a first step towards integration of arterial compliance measurements in hemodynamic monitoring using existing clinical technology. The Bayesian approach is of particular relevance for such patient monitoring settings, where measurements are repeated frequently, context is relevant, and data is affected by artefacts. In addition, the simulation framework is necessary for future clinical-study design, in order to determine device specifications and the extent to which noise affects the inference process.

A ventilation technique for oxygenation and carbon dioxide elimination in CPR: Continuous insufflation of oxygen at three levels of pressure in a pig model.

AIM: Pulmonary ventilation remains an important part of cardiopulmonary resuscitation, affecting gas exchange and haemodynamics. We designed and studied an improved method of ventilation for CPR, constructed specifically to support both gas exchange and haemodynamics. This method uses continuous insufflation of oxygen at three levels of pressure, resulting in tri-level pressure ventilation (TLPV). We hypothesized that TLPV improves gas exchange and haemodynamics compared to manual gold standard ventilation (GSV). METHODS: In 14 pigs, ventricular fibrillation was induced and automated CPR performed for 10 min with either TLPV or GSV. After defibrillation, CPR was repeated with the other ventilation method. Gas exchange and haemodynamics were monitored. Data are presented as mean±standard error of the mean. RESULTS: TLPV was superior to GSV for PaO2 (163±36 mmHg difference; P=0.001), and peak AWP (-20±2 cmH2O difference; P=0.000) and higher for mean AWP (8±0.2 cmH2O difference; P=0.000). TLPV was comparable to GSV for CPP (5±3 mmHg difference; P=0.012), VCO2 (0.07±0.3 mL/min/kg difference; P=0.001), SvO2 (4±3%-point; P=0.001), mean carotid flow (-0.5±4 mL/min difference; P=0.016), and pHa (0.00±0.03 difference; P=0.002). The PaCO2 data do not provide a conclusive result (4±4 mmHg difference). CONCLUSION: We conclude that the ventilation strategy with a tri-level pressure cycle performs comparable to an expert, manual ventilator in an automated-CPR swine model.

Detection of a spontaneous pulse in photoplethysmograms during automated cardiopulmonary resuscitation in a porcine model.

INTRODUCTION: Reliable, non-invasive detection of return of spontaneous circulation (ROSC) with minimal interruptions to chest compressions would be valuable for high-quality cardiopulmonary resuscitation (CPR). We investigated the potential of photoplethysmography (PPG) to detect the presence of a spontaneous pulse during automated CPR in an animal study. METHODS: Twelve anesthetized pigs were instrumented to monitor circulatory and respiratory parameters. Here we present the simultaneously recorded PPG and arterial blood pressure (ABP) signals. Ventricular fibrillation was induced, followed by 20 min of automated CPR and subsequent defibrillation. After defibrillation, pediatric-guidelines-style life support was given in cycles of 2 min. PPG and ABP waveforms were recorded during all stages of the protocol. Raw PPG waveforms were acquired with a custom-built photoplethysmograph controlling a commercial reflectance pulse oximetry probe attached to the nose. ABP was measured in the aorta. RESULTS: In nine animals ROSC was achieved. Throughout the protocol, PPG and ABP frequency content showed strong resemblance. We demonstrate that (1) the PPG waveform allows for the detection of a spontaneous pulse during ventilation pauses, and that (2) frequency analysis of the PPG waveform allows for the detection of a spontaneous pulse and the determination of the pulse rate, even during ongoing chest compressions, if the pulse and compression rates are sufficiently distinct. CONCLUSIONS: These results demonstrate the potential of PPG as a non-invasive means to detect pulse presence or absence, as well as pulse rate during CPR.

The influence of nonlinear intra-thoracic vascular behaviour and compression characteristics on cardiac output during CPR.

Clinical observations suggest that the assumption of a linear relationship between chest compression pressure and cardiac output may be oversimplified. More complex behaviour may occur when the transmural pressure is large, changing the compliances and resistances in the intra-thoracic vasculature. A fundamental understanding of these compression induced phenomena is required for improving CPR. An extensively used, lumped element computer model (model I) of the circulation was upgraded and refined to include the intrathoracic vasculature (model II). After validation, model II was extended by adding variable compliances and resistances (model III) to the vascular structures. Successively, ranges of compression pressures, frequencies, duty cycles and compression pulse shapes were applied while controlling all other parameters. Cardiac output was then compared. The nonlinearities in compliance and resistance become important, limiting factors in cardiac output, starting in our experimental series at 70 mmHg peak compression pressure, and increasing with higher pressures. This effect is reproducible for sinusoidal and trapezoidal compression forms, resulting in lower cardiac output in all experiments at high compression pressures. Duty cycle and wait time are key parameters for cardiac output. Our data strongly indicate that vascular compliance, especially the ability of vessels to collapse (and potentially the cardiac chambers), can be a central factor in the limited output generated by chest compressions. Just pushing 'harder' or 'faster' is not always better, as an 'optimal' force and frequency may exist. Overly forceful compression can limit blood flow by restricting filling or depleting volume in the cardiac chambers and central great vessels.

The impact of compliant surfaces on in-hospital chest compressions: effects of common mattresses and a backboard.

PURPOSE: To evaluate, in a hospital setting, the influence of different, common mattresses, with and without a backboard, on chest movement during CPR. DESIGN AND SETTING: Sixty CPR sessions (140s each, 30:2, C:R ratio 1:1) were performed using a manikin on standard hospital mattresses, with or without a backboard in combination with variable weights. Sternum-to-spine compression distance was controlled (range 30-60mm) allowing evaluation of the underlying compliant surface on total hand travel. RESULTS: Movement of the caregiver's hands was significantly larger (up to 111mm at 50mm compression depth, p<0.0001) when sternum-to-spine compressions were performed without a backboard than with one. The extent of this variable extra travel effect depended on the type of mattress as well as the force of compression. Foam mattresses and air chamber systems act as springs and follow hand movement, while 'slow foam' mattresses incorporate time delays, making depth and force sensing harder. A backboard decreases the extra hand movement due to mattress effects by more than 50%, strongly reducing caregiver work. CONCLUSIONS: Total vertical hand movement is significantly, and clinically relevantly much, larger than sternum-to-spine compression depth when CPR is performed on a mattress. Additional movement depends on the type of mattress and can be strongly reduced, but not eliminated, when a backboard is applied. The additional motion and increased work load adds extra complexity to in-hospital CPR. We propose that this should be taken into account during training by in-hospital caregivers.