Assessment of changes in blood volume during lower body negative pressure-induced hypovolemia using bioelectrical impedance analysis.

BACKGROUND: Lower body negative Pressure (LBNP)-induced hypovolemia is simulating acute hemorrhage by sequestrating blood into lower extremities. Bioelectrical Impedance Analysis (BIA) is based on the electrical properties of biological tissues, as electrical current flows along highly conductive body tissues (such as blood). Changes in blood volume will lead to changes in bioimpedance. This study aims to study changes in upper (UL) and lower (LL) extremities bioimpedance during LBNP-induced hypovolemia. METHODS: This was a prospective observational study of healthy volunteers who underwent gradual LBNP protocol which consisted of 3-minute intervals: at baseline, -15, -30, -45, -60 mmHg, then recovery phases at -30 mmHg and baseline. The UL&LL extremities bioimpedance were measured and recorded at each phase of LBNP and the percentage changes of bioimpedance from baseline were calculated and compared using student's t-test. A P-value of < 0.05 was considered significant. Correlation between relative changes in UL&LL bioimpedance and estimated blood loss (EBL) from LBNP was calculated using Pearson correlation. RESULTS: 26 healthy volunteers were enrolled. As LBNP-induced hypovolemia progressed, there were a significant increase in UL bioimpedance and a significant decrease in LL bioimpedance. During recovery phases (where blood was shifted from the legs to the body), there were a significant increase in LL bioimpedance and a reduction in UL bioimpedance. There were significant correlations between estimated blood loss from LBNP model with UL (R = 0.97) and LL bioimpedance (R = - 0.97). CONCLUSION: During LBNP-induced hypovolemia, there were reciprocal changes in UL&LL bioimpedance. These changes reflected hemodynamic compensatory mechanisms to hypovolemia.

Signal quality assessment of peripheral venous pressure.

Develop a signal quality index (SQI) for the widely available peripheral venous pressure waveform (PVP). We focus on the quality of the cardiac component in PVP. We model PVP by the adaptive non-harmonic model. When the cardiac component in PVP is stronger, the PVP is defined to have a higher quality. This signal quality is quantified by applying the synchrosqueezing transform to decompose the cardiac component out of PVP, and the SQI is defined as a value between 0 and 1. A database collected during the lower body negative pressure experiment is utilized to validate the developed SQI. All signals are labeled into categories of low and high qualities by experts. A support vector machine (SVM) learning model is trained for practical purpose. The developed signal quality index coincide with human experts' labels with the area under the curve 0.95. In a leave-one-subject-out cross validation (LOSOCV), the SQI achieves accuracy 0.89 and F1 0.88, which is consistently higher than other commonly used signal qualities, including entropy, power and mean venous pressure. The trained SVM model trained with SQI, entropy, power and mean venous pressure could achieve an accuracy 0.92 and F1 0.91 under LOSOCV. An exterior validation of SQI achieves accuracy 0.87 and F1 0.92; an exterior validation of the SVM model achieves accuracy 0.95 and F1 0.96. The developed SQI has a convincing potential to help identify high quality PVP segments for further hemodynamic study. This is the first work aiming to quantify the signal quality of the widely applied PVP waveform.

Improving pulse oximetry accuracy in dark-skinned patients: technical aspects and current regulations.

Recent concerns regarding the clinical accuracy of pulse oximetry in dark-skinned patients, specifically in detecting occult hypoxaemia, have motivated research on this topic and recently reported in this journal. We provide an overview of the technical aspects of the issue, the sources of inaccuracy, and the current regulations and limitations. These insights offer perspectives on how pulse oximetry can be improved to address these potential limitations.

Using the ear photoplethysmographic waveform as an early indicator of central hypovolemia in healthy volunteers utilizing LBNP induced hypovolemia model.

Objective. To study the photoplethysmographic (PPG) waveforms of different locations (ear and finger) during lower body negative pressure (LBNP) induced hypovolemia. Then, to determine whether the PPG waveform can be used to detect hypovolemia during the early stage of LBNP.Approach. 36 healthy volunteers were recruited for progressive LBNP induced hypovolemia, with an endpoint of -60 mmHg or development of hypoperfusion symptoms, whichever comes first. Subjects tolerating the entire protocol without symptoms were designated as high tolerance (HT), while symptomatic subjects were designated as low tolerance (LT). Subjects were monitored with an electrocardiogram, continuous noninvasive blood pressure monitor, and two pulse oximetry probes, one on the ear (Xhale) and one the finger (Nellcor). Stroke volume was measured non-invasively utilizing Non-Invasive Cardiac Output Monitor (NICOM, Cheetah Medical). The waveform morphology was analyzed using novel PPG waveforms indices, including phase hemodynamic index (PHI) and amplitude hemodyamaic index and were evaluated from the ear PPG and finger PPG at different LBNP stages.Main results. The PHI, particularly the phase relationship between the second harmonic and the fundamental component of the ear PPG denoted as∇φ2,during the early stage of LBNP (-15 mmHg) in the HT and LT groups is statistically significantly different (pvalue = 0.0033) with the area under curve 0.81 (CI: 0.616-0.926). The other indices are not significantly different. The 5 fold cross validation shows that∇φ2during the early stage of LBNP (-15 mmHg) as the single index could predict the tolerance of the subject with the sensitivity, specificity, accuracy andF1 as 0.771 ± 0.192, 0.71 ± 0.107, 0.7 ± 0.1 and 0.771 ± 0.192 respectively.Significance. The ear's PPG PHI which compares the phases of the fundamental and second harmonic has the potential to be used as an early predictor of central hypovolemia.

Inaccuracy of pulse oximetry with dark skin pigmentation: clinical implications and need for improvement.

Recent reports highlight potential inaccuracies of pulse oximetry in patients with various degrees of skin pigmentation. We summarise the literature, provide an overview of potential clinical implications, and provide insights into how pulse oximetry could be improved to mitigate against such potential shortcomings.

Amplitude and phase measurements from harmonic analysis may lead to new physiologic insights: lower body negative pressure photoplethysmographic waveforms as an example.

The photoplethysmographic (PPG) waveform contains hemodynamic information in its oscillations. We provide a new method for quantitative study of the waveform morphology and its relationship to the hemodynamics. A data adaptive modeling of the waveform shape is used to describe the PPG waveforms recorded from ear and finger. Several indices, based on the phase and amplitude information of different harmonics, are proposed to describe the PPG morphology. The proposed approach is illustrated by analyzing PPG waveforms recorded during a lower body negative pressure (LBNP) experiment. Different phase and amplitude dynamics are observed during the LBNP experiment. Specifically, we observe that the phase difference between the high order harmonics and fundamental components change more significantly when the PPG signal is recorded from the ear than the finger at the beginning of the study. In contrast, the finger PPG amplitude changes more when compared to the ear PPG during the recovery period. A more complete harmonic analysis of the PPG appears to provide new hemodynamic information when used during a LBNP experiment. We encourage other investigators who possess modulated clinical waveform data (e.g. PPG, arterial pressure, respiratory, and autonomic) to re-examine their data, using phase information and higher harmonics as a potential source of new insights into underlying physiologic mechanisms.

Tribute to Dr. Takuo Aoyagi, inventor of pulse oximetry.

INTRODUCTION: Dr. Takuo Aoyagi invented pulse oximetry in 1974. Pulse oximeters are widely used worldwide, most recently making headlines during the COVID-19 pandemic. Dr. Aoyagi passed away on April 18, 2020, aware of the significance of his invention, but still actively searching for the theory that would take his invention to new heights. METHOD: Many people who knew Dr. Aoyagi, or knew of him and his invention, agreed to participate in this tribute to his work. The authors, from Japan and around the world, represent all aspects of the development of medical devices, including scientists and engineers, clinicians, academics, business people, and clinical practitioners. RESULTS: While the idea of pulse oximetry originated in Japan, device development lagged in Japan due to a lack of business, clinical, and academic interest. Awareness of the importance of anesthesia safety in the US, due to academic foresight and media attention, in combination with excellence in technological innovation, led to widespread use of pulse oximetry around the world. CONCLUSION: Dr. Aoyagi's final wish was to find a theory of pulse oximetry. We hope this tribute to him and his invention will inspire a new generation of scientists, clinicians, and related organizations to secure the foundation of the theory.

A new approach to complicated and noisy physiological waveforms analysis: peripheral venous pressure waveform as an example.

We introduce a recently developed nonlinear-type time-frequency analysis tool, synchrosqueezing transform (SST), to quantify complicated and noisy physiological waveform that has time-varying amplitude and frequency. We apply it to analyze a peripheral venous pressure (PVP) signal recorded during a seven hours aortic valve replacement procedure. In addition to showing the captured dynamics, we also quantify how accurately we can estimate the instantaneous heart rate from the PVP signal.

COVID-19: Pulse oximeters in the spotlight.

From home to intensive care units, innovations in pulse oximetry are susceptible to improve the monitoring and management of patients developing acute respiratory failure, and particularly those with the coronavirus disease 2019 (COVID-19). They include self-monitoring of oxygen saturation (SpO2) from home, continuous wireless SpO2 monitoring on hospital wards, and the integration of SpO2 as the input variable for closed-loop oxygen administration systems. The analysis of the pulse oximetry waveform may help to quantify respiratory efforts and prevent intubation delays. Tracking changes in the peripheral perfusion index during a preload-modifying maneuver may be useful to predict preload responsiveness and rationalize fluid therapy.

Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia.

Identifying trauma patients at risk of imminent hemorrhagic shock is a challenging task in intraoperative and battlefield settings given the variability of traditional vital signs, such as heart rate and blood pressure, and their inability to detect blood loss at an early stage. To this end, we acquired N = 58 photoplethysmographic (PPG) recordings from both trauma patients with suspected hemorrhage admitted to the hospital, and healthy volunteers subjected to blood withdrawal of 0.9 L. We propose four features to characterize each recording: goodness of fit (r2), the slope of the trend line, percentage change, and the absolute change between amplitude estimates in the heart rate frequency range at the first and last time points. Also, we propose a machine learning algorithm to distinguish between blood loss and no blood loss. The optimal overall accuracy of discriminating between hypovolemia and euvolemia was 88.38%, while sensitivity and specificity were 88.86% and 87.90%, respectively. In addition, the proposed features and algorithm performed well even when moderate blood volume was withdrawn. The results suggest that the proposed features and algorithm are suitable for the automatic discrimination between hypovolemia and euvolemia, and can be beneficial and applicable in both intraoperative/emergency and combat casualty care.

Ventilation-Induced Modulation of Pulse Oximeter Waveforms: A Method for the Assessment of Early Changes in Intravascular Volume During Spinal Fusion Surgery in Pediatric Patients.

BACKGROUND: Scoliosis surgery is often associated with substantial blood loss, requiring fluid resuscitation and blood transfusions. In adults, dynamic preload indices have been shown to be more reliable for guiding fluid resuscitation, but these indices have not been useful in children undergoing surgery. The aim of this study was to introduce frequency-analyzed photoplethysmogram (PPG) and arterial pressure waveform variables and to study the ability of these parameters to detect early bleeding in children during surgery. METHODS: We studied 20 children undergoing spinal fusion. Electrocardiogram, arterial pressure, finger pulse oximetry (finger PPG), and airway pressure waveforms were analyzed using time domain and frequency domain methods of analysis. Frequency domain analysis consisted of calculating the amplitude density of PPG and arterial pressure waveforms at the respiratory and cardiac frequencies using Fourier analysis. This generated 2 measurements: The first is related to slow mean arterial pressure modulation induced by ventilation (also known as DC modulation when referring to the PPG), and the second corresponds to pulse pressure modulation (AC modulation or changes in the amplitude of pulse oximeter plethysmograph when referring to the PPG). Both PPG and arterial pressure measurements were divided by their respective cardiac pulse amplitude to generate DC% and AC% (normalized values). Standard hemodynamic data were also recorded. Data at baseline and after bleeding (estimated blood loss about 9% of blood volume) were presented as median and interquartile range and compared using Wilcoxon signed-rank tests; a Bonferroni-corrected P value <0.05 was considered statistically significant. RESULTS: There were significant increases in PPG DC% (median [interquartile range] = 359% [210 to 541], P = 0.002), PPG AC% (160% [87 to 251], P = 0.003), and arterial DC% (44% [19 to 84], P = 0.012) modulations, respectively, whereas arterial AC% modulations showed nonsignificant increase (41% [1 to 85], P = 0.12). The change in PPG DC% was significantly higher than that in PPG AC%, arterial DC%, arterial AC%, and systolic blood pressure with P values of 0.008, 0.002, 0.003, and 0.002, respectively. Only systolic blood pressure showed significant changes (11% [4 to 21], P = 0.003) between bleeding phase and baseline. CONCLUSIONS: Finger PPG and arterial waveform parameters (using frequency analysis) can track changes in blood volume during the bleeding phase, suggesting the potential for a noninvasive monitor for tracking changes in blood volume in pediatric patients. PPG waveform baseline modulation (PPG DC%) was more sensitive to changes in venous blood volume when compared with respiration-induced modulation seen in the arterial pressure waveform.

Photoplethysmography.

The photoplethysmographic (PPG) waveform, also known as the pulse oximeter waveform, is one of the most commonly displayed clinical waveforms. First described in the 1930s, the technology behind the waveform is simple. The waveform, as displayed on the modern pulse oximeter, is an amplified and highly filtered measurement of light absorption by the local tissue over time. It is optimized by medical device manufacturers to accentuate its pulsatile components. Physiologically, it is the result of a complex, and not well understood, interaction between the cardiovascular, respiratory, and autonomic systems. All modern pulse oximeters extract and display the heart rate and oxygen saturation derived from the PPG measurements at multiple wavelengths. "As is," the PPG is an excellent monitor for cardiac arrhythmia, particularly when used in conjunction with the electrocardiogram (ECG). With slight modifications in the display of the PPG (either to a strip chart recorder or slowed down on the monitor screen), the PPG can be used to measure the ventilator-induced modulations which have been associated with hypovolemia. Research efforts are under way to analyze the PPG using improved digital signal processing methods to develop new physiologic parameters. It is hoped that when these new physiologic parameters are combined with a more modern understanding of cardiovascular physiology (functional hemodynamics) the potential utility of the PPG will be expanded. The clinical researcher's objective is the use of the PPG to guide early goal-directed therapeutic interventions (fluid, vasopressors, and inotropes), in effect to extract from the simple PPG the information and therapeutic guidance that was previously only obtainable from an arterial pressure line and the pulmonary artery catheter.

Impact of lower body negative pressure induced hypovolemia on peripheral venous pressure waveform parameters in healthy volunteers.

Lower body negative pressure (LBNP) creates a reversible hypovolemia by sequestrating blood volume in the lower extremities. This study sought to examine the impact of central hypovolemia on peripheral venous pressure (PVP) waveforms in spontaneously breathing subjects. With IRB approval, 11 healthy subjects underwent progressive LBNP (baseline, -30, -75, and -90 mmHg or until the subject became symptomatic). Each was monitored for heart rate (HR), finger arterial blood pressure (BP), a chest respiratory band and PVP waveforms which are generated from a transduced upper extremity intravenous site. The first subject was excluded from PVP analysis because of technical errors in collecting the venous pressure waveform. PVP waveforms were analyzed to determine venous pulse pressure, mean venous pressure, pulse width, maximum and minimum slope (time domain analysis) together with cardiac and respiratory modulations (frequency domain analysis). No changes of significance were found in the arterial BP values at -30 mmHg LBNP, while there were significant reductions in the PVP waveforms time domain parameters (except for 50% width of the respiration induced modulations) together with modulation of the PVP waveform at the cardiac frequency but not at the respiratory frequency. As the LBNP progressed, arterial systolic BP, mean BP and pulse pressure, PVP parameters and PVP cardiac modulation decreased significantly, while diastolic BP and HR increased significantly. Changes in hemodynamic and PVP waveform parameters reached a maximum during the symptomatic phase. During the recovery phase, there was a significant reduction in HR together with a significant increase in HR variability, mean PVP and PVP cardiac modulation. Thus, in response to mild hypovolemia induced by LBNP, changes in cardiac modulation and other PVP waveform parameters identified hypovolemia before detectable hemodynamic changes.

Analysis of plethysmographic waveform changes induced by beach chair positioning under general anesthesia.

During shoulder surgery, patients typically are placed in the beach chair position. In rare cases, this positioning has resulted in devastating outcomes of postoperative cerebral ischemia (Cullen and Kirby in APSF Newsl 22(2):25-27, 2007; Munis in APSF Newsl 22(4):82-83, 2008). This study presents a method to noninvasively and continuously hemodynamically monitor patients during beach chair positioning by using the photoplethysmograph signal recorded from a commercial pulse oximeter. Twenty-nine adults undergoing shoulder surgery were monitored before and after beach chair positioning with electrocardiogram, intermittent blood pressure, end tidal carbon dioxide, and photoplethysmograph via Nellcor finger pulse oximeter. Fast Fourier transform (FFT) was used to perform frequency-domain analysis on the photoplethysmograph (PPG) signal for data segments taken 80-120 s before and after beach chair positioning. The amplitude density of respiration-associated PPG oscillations was quantified measuring the height of the FFT peak at respiratory frequency. Results were reported as (median, interquartile range) and statistical analysis was performed using Wilcoxon sign rank test. Data were also collected when vasoactive drugs phenylephrine and ephedrine were used to maintain acceptable mean arterial pressure during a case. With beach chair positioning, all subjects who did not receive vasoactive drugs showed an increase in the FFT amplitude density of respiration-associated PPG oscillations (p < 0.0001) without change in pulse-associated PPG oscillations. The PPG was more accurate at monitoring the change to beach chair position than blood pressure or heart rate. With vasoactive drugs, pulse-associated PPG oscillations decreased only with phenylephrine while respiration-associated oscillations did not change. Frequency domain analysis of the PPG signal may be a better tool than traditional noninvasive hemodynamic parameters at monitoring patients during beach chair position surgery.

New utility for an old tool: can a simple gait speed test predict ambulatory surgical discharge outcomes?

OBJECTIVE: The primary aims of this study were to design prediction models based on a functional marker (preoperative gait speed) to predict readiness for home discharge time of 90 mins or less and to identify those at risk for unplanned admissions after elective ambulatory surgery. DESIGN: This prospective observational cohort study evaluated all patients scheduled for elective ambulatory surgery. Home discharge readiness and unplanned admissions were the primary outcomes. Independent variables included preoperative gait speed, heart rate, and total anesthesia time. The relationship between all predictors and each primary outcome was determined in separate multivariable logistic regression models. RESULTS: After adjustment for covariates, gait speed with adjusted odds ratio of 3.71 (95% confidence interval, 1.21-11.26), P = 0.02, was independently associated with early home discharge readiness of 90 mins or less. Importantly, gait speed dichotomized as greater or less than 1 m/sec predicted unplanned admissions, with odds ratio of 0.35 (95% confidence interval, 0.16-0.76, P = 0.008) for those with speeds 1 m/sec or greater in comparison with those with speeds less than 1 m/sec. In a separate model, history of cardiac surgery with adjusted odds ratio of 7.5 (95% confidence interval, 2.34-24.41; P = 0.001) was independently associated with unplanned admissions after elective ambulatory surgery, when other covariates were held constant. CONCLUSIONS: This study demonstrates the use of novel prediction models based on gait speed testing to predict early home discharge and to identify those patients at risk for unplanned admissions after elective ambulatory surgery.