Real-time heart rate entropy predicts the need for lifesaving interventions in trauma activation patients

Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients

Background

Triage trauma scores are utilised to determine patient disposition, interventions and prognostication in the care of trauma patients. Heart rate variability (HRV) and heart rate complexity (HRC) reflect the autonomic nervous system and are derived from electrocardiogram (ECG) analysis. In this study, we aimed to develop a model incorporating HRV and HRC, to predict the need for life-saving interventions (LSI) in trauma patients, within 24 h of emergency department presentation.

Methods

We included adult trauma patients (≥ 18 years of age) presenting at the emergency department of Singapore General Hospital between October 2014 and October 2015. We excluded patients who had non-sinus rhythms and larger proportions of artefacts and/or ectopics in ECG analysis. We obtained patient demographics, laboratory results, vital signs and outcomes from electronic health records. We conducted univariate and multivariate analyses for predictive model building.

Results

Two hundred and twenty-five patients met inclusion criteria, in which 49 patients required LSIs. The LSI group had a higher proportion of deaths (10, 20.41% vs 1, 0.57%, p < 0.001). In the LSI group, the mean of detrended fluctuation analysis (DFA)-α1 (1.24 vs 1.12, p = 0.045) and the median of DFA-α2 (1.09 vs 1.00, p = 0.027) were significantly higher. Multivariate stepwise logistic regression analysis determined that a lower Glasgow Coma Scale, a higher DFA-α1 and higher DFA-α2 were independent predictors of requiring LSIs. The area under the curve (AUC) for our model (0.75, 95% confidence interval, 0.66-0.83) was higher than other scoring systems and selected vital signs.

Conclusions

An HRV/HRC model outperforms other triage trauma scores and selected vital signs in predicting the need for LSIs but needs to be validated in larger patient populations.

Autonomic impairment of patients in coma with different Glasgow coma score assessed with heart rate variability

PRIMARY OBJECTIVE

The objective of this study is to assess the functional state of the autonomic nervous system in healthy individuals and in individuals in coma using measures of heart rate variability (HRV) and to evaluate its efficiency in predicting mortality.

DESIGN AND METHODS

Retrospective group comparison study of patients in coma classified into two subgroups, according to their Glasgow coma score, with a healthy control group. HRV indices were calculated from 7 min of artefact-free electrocardiograms using the Hilbert-Huang method in the spectral range 0.02-0.6 Hz. A special procedure was applied to avoid confounding factors. Stepwise multiple regression logistic analysis (SMLRA) and ROC analysis evaluated predictions.

RESULTS

Progressive reduction of HRV was confirmed and was associated with deepening of coma and a mortality score model that included three spectral HRV indices of absolute power values of very low, low and very high frequency bands (0.4-0.6 Hz). The SMLRA model showed sensitivity of 95.65%, specificity of 95.83%, positive predictive value of 95.65%, and overall efficiency of 95.74%.

CONCLUSIONS

HRV is a reliable method to assess the integrity of the neural control of the caudal brainstem centres on the hearts of patients in coma and to predict patient mortality.

Complexity of Wake Electroencephalography Correlates With Slow Wave Activity After Sleep Onset

Sleep electroencephalography (EEG) provides an opportunity to study sleep scientifically, whose chaotic, dynamic, complex, and dissipative nature implies that non-linear approaches could uncover some mechanism of sleep. Based on well-established complexity theories, one hypothesis in sleep medicine is that lower complexity of brain waves at pre-sleep state can facilitate sleep initiation and further improve sleep quality. However, this has never been studied with solid data. In this study, EEG collected from healthy subjects was used to investigate the association between pre-sleep EEG complexity and sleep quality. Multiscale entropy analysis (MSE) was applied to pre-sleep EEG signals recorded immediately after light-off (while subjects were awake) for measuring the complexities of brain dynamics by a proposed index, CI₁₋₃₀. Slow wave activity (SWA) in sleep, which is commonly used as an indicator of sleep depth or sleep intensity, was quantified based on two methods, traditional Fast Fourier transform (FFT) and ensemble empirical mode decomposition (EEMD). The associations between wake EEG complexity, sleep latency, and SWA in sleep were evaluated. Our results demonstrated that lower complexity before sleep onset is associated with decreased sleep latency, indicating a potential facilitating role of reduced pre-sleep complexity in the wake-sleep transition. In addition, the proposed EEMD-based method revealed an association between wake complexity and quantified SWA in the beginning of sleep (90 min after sleep onset). Complexity metric could thus be considered as a potential indicator for sleep interventions, and further studies are encouraged to examine the application of EEG complexity before sleep onset in populations with difficulty in sleep initiation. Further studies may also examine the mechanisms of the causal relationships between pre-sleep brain complexity and SWA, or conduct comparisons between normal and pathological conditions.

Diffuse optical monitoring of peripheral tissues during uncontrolled internal hemorrhage in a porcine model

Reliable, continuous and noninvasive blood flow and hemoglobin monitoring in trauma patients remains a critical, but generally unachieved goal. Two optical sensing methods - diffuse correlation spectroscopy (DCS) and diffuse reflectance spectroscopy (DRS) - are used to monitor and detect internal hemorrhage. Specifically, we investigate if cutaneous perfusion measurements acquired using DCS and DRS in peripheral (thighs and ear-lobe) tissues could detect severe hemorrhagic shock in a porcine model. Four animals underwent high-grade hepato-portal injury in a closed abdomen, to induce uncontrolled hemorrhage and were subsequently allowed to bleed for 10 minutes before fluid resuscitation. DRS and DCS measurements of cutaneous blood flow were acquired using fiber optical probes placed on the thigh and earlobe of the animals and were obtained repeatedly starting from 1 to 5 minutes pre-injury, up to several minutes post shock. Clear changes were observed in measured optical spectra across all animals at both sites. DCS-derived cutaneous blood flow decreased sharply during hemorrhage, while DRS-derived vascular saturation and hemoglobin paralleled cardiac output. All derived optical parameters had the steepest changes during the rapid initial hemorrhage unambiguously. This suggests that a combined DCS and DRS based device might provide an easy-to-use, non-invasive, internal-hemorrhage detection system that can be used across a wide array of clinical settings.

Effect of salt intake on beat-to-beat blood pressure nonlinear dynamics and entropy in salt-sensitive versus salt-protected rats

Blood pressure exhibits substantial short- and long-term variability (BPV). We assessed the hypothesis that the complexity of beat-to-beat BPV will be differentially altered in salt-sensitive hypertensive Dahl rats (SS) versus rats protected from salt-induced hypertension (SSBN13) maintained on high-salt versus low-salt diet. Beat-to-beat systolic and diastolic BP series from nine SS and six SSBN13 rats (http://www.physionet.org) were analyzed following 9 weeks on low salt and repeated after 2 weeks on high salt. BP complexity was quantified by detrended fluctuation analysis (DFA), short- and long-range scaling exponents (αS and αL), sample entropy (SampEn), and traditional standard deviation (SD) and coefficient of variation (CV(%)). Mean systolic and diastolic BP increased on high-salt diet (P < 0.01) particularly for SS rats. SD and CV(%) were similar across groups irrespective of diet. Salt-sensitive and -protected rats exhibited similar complexity indices on low-salt diet. On high salt, (1) SS rats showed increased scaling exponents or smoother, systolic (P = 0.007 [αL]) and diastolic (P = 0.008 [αL]) BP series; (2) salt-protected rats showed lower SampEn (less complex) systolic and diastolic BP (P = 0.046); and (3) compared to protected SSBN13 rats, SS showed higher αL for systolic (P = 0.01) and diastolic (P = 0.005) BP Hypertensive SS rats are more susceptible to high salt with a greater rise in mean BP and reduced complexity. Comparable mean pressures in sensitive and protective rats when on low-salt diet coupled with similar BPV dynamics suggest a protective role of low-salt intake in hypertensive rats. This effect likely reflects better coupling of biologic oscillators.

Sample entropy predicts lifesaving interventions in trauma patients with normal vital signs

INTRODUCTION

Heart rate complexity, commonly described as a "new vital sign," has shown promise in predicting injury severity, but its use in clinical practice is not yet widely adopted. We previously demonstrated the ability of this noninvasive technology to predict lifesaving interventions (LSIs) in trauma patients. This study was conducted to prospectively evaluate the utility of real-time, automated, noninvasive, instantaneous sample entropy (SampEn) analysis to predict the need for an LSI in a trauma alert population presenting with normal vital signs.

METHODS

Prospective enrollment of patients who met criteria for trauma team activation and presented with normal vital signs was conducted at a level I trauma center. High-fidelity electrocardiogram recording was used to calculate SampEn and SD of the normal-to-normal R-R interval (SDNN) continuously in real time for 2 hours with a portable, handheld device. Patients who received an LSI were compared to patients without any intervention (non-LSI). Multivariable analysis was performed to control for differences between the groups. Treating clinicians were blinded to results.

RESULTS

Of 129 patients enrolled, 38 (29%) received 136 LSIs within 24 hours of hospital arrival. Initial systolic blood pressure was similar in both groups. Lifesaving intervention patients had a lower Glasgow Coma Scale. The mean SampEn on presentation was 0.7 (0.4-1.2) in the LSI group compared to 1.5 (1.1-2.0) in the non-LSI group (P < .0001). The area under the curve with initial SampEn alone was 0.73 (95% confidence interval [CI], 0.64-0.81) and increased to 0.93 (95% CI, 0.89-0.98) after adding sedation to the model. Sample entropy of less than 0.8 yields sensitivity, specificity, negative predictive value, and positive predictive value of 58%, 86%, 82%, and 65%, respectively, with an overall accuracy of 76% for predicting an LSI. SD of the normal-to-normal R-R interval had no predictive value.

CONCLUSIONS

In trauma patients with normal presenting vital signs, decreased SampEn is an independent predictor of the need for LSI. Real-time SampEn analysis may be a useful adjunct to standard vital signs monitoring. Adoption of real-time, instantaneous SampEn monitoring for trauma patients, especially in resource-constrained environments, should be considered.

The influence of anesthesia on heart rate complexity during elective and urgent surgery in 128 patients

BACKGROUND

As an emerging "new vital sign," heart rate complexity (by sample entropy [SampEn]) has been shown to be a useful trauma triage tool by predicting occult physiologic compromise and need for life-saving interventions. Sample entropy may be confounded by anesthesia possibly limiting its value intraoperatively. We investigated the effects of anesthesia on SampEn during elective and urgent surgical procedures. We hypothesized that SampEn is reduced by general anesthesia.

METHODS

With institutional review board-approved waiver of informed consent, 128 patients undergoing elective or urgent general surgery were prospectively enrolled. Real-time heart rate complexity was calculated using SampEn through electrocardiogram recordings of 200 consecutive beats in a continuous sliding-window fashion. We recorded SampEn starting 10 minutes before induction until 10 minutes after emergence from anesthesia. The time before induction of anesthesia was categorized as period 1, the time after induction and before emergence as period 2 (intraoperative), and the time after emergence as period 3. We analyzed SampEn changes as patients moved between the different periods and made 3 comparisons: from period 1 with period 2 (comparison A), from period 2 with period 3 (comparison B). We also compared period 1 with period 3 SampEn (comparison C).

RESULTS

The mean SampEn value for all patients before induction of anesthesia was 1.55 ± 0.58. In each 1 of the 3, comparisons there was a decline in SampEn. Comparison A had a mean decrease of 0.53 ± 0.55 (P < .0001), comparison B had a decrease of 0.13 ± 0.52 (P < .0051), and the mean SampEn difference for comparison C was 0.66 ± 0.53 (P < .0001). Certain pharmacologics had significant effect on SampEn as did need for urgent surgery and American Society of Anesthesiologists class.

CONCLUSION

Sample entropy decreases after induction of anesthesia and continues to decrease even immediately after emergence in patients without any immediately life-threatening conditions. This finding may complicate interpretation low complexity as a predictor of life-saving interventions in patients in the perioperative period.

Real-time sample entropy predicts life-saving interventions after the Boston Marathon bombing

PURPOSE

Identifying patients in need of a life-saving intervention (LSI) during a mass casualty event is a priority. We hypothesized that real-time, instantaneous sample entropy (SampEn) could predict the need for LSI in the Boston Marathon bombing victims.

MATERIALS AND METHODS

Severely injured Boston Marathon bombing victims (n = 10) had sample entropy (SampEn) recorded upon presentation using a continuous 200-beat rolling average in real time. Treating clinicians were blinded to real-time results. The correlation between SampEn, injury severity, number, and type of LSI was examined.

RESULTS

Victims were males (60%) with a mean age of 39.1 years. Injuries involved lower extremities (50.0%), head and neck (24.2%), or upper extremities (9.7%). Sample entropy negatively correlated with Injury Severity Score (r = -0.70; P = .023), number of injuries (r = -0.70; P = .026), and the number and need for LSI (r = -0.82; P = .004). Sample entropy was reduced under a variety of conditions. (Table see text).

CONCLUSIONS

Sample entropy strongly correlates with injury severity and predicts LSI after blast injuries sustained in the Boston Marathon bombings. Sample entropy may be a useful triage tool after blast injury.