Heart rate variability index in trauma patients

Association between non-acute Traumatic Injury (TI) and Heart Rate Variability (HRV) in adults: A systematic review and meta-analysis

Heart rate variability (HRV) is a non-invasive measure of autonomic function. The relationship between unselected long-term traumatic injury (TI) and HRV has not been investigated. This systematic review examines the impact of non-acute TI (>7 days post-injury) on standard HRV indices in adults. Four electronic databases (CINAHL, Medline, Scopus, and Web of Science) were searched. The quality of studies, risk of bias (RoB), and quality of evidence (QoE) were assessed using Axis, RoBANS and GRADE, respectively. Using the random-effects model, mean difference (MD) for root mean square of successive differences (RMSSD) and standard deviation of NN-intervals (SDNN), and standardized mean difference (SMD) for Low-frequency (LF): High-Frequency (HF) were pooled in RevMan guided by the heterogeneity score (I2). 2152 records were screened followed by full-text retrieval of 72 studies. 31 studies were assessed on the inclusion and exclusion criteria. Only four studies met the inclusion criteria. Three studies demonstrated a high RoB (mean RoBANS score 14.5±3.31) with a low QoE. TI was associated with a significantly higher resting heart rate. Meta-analysis of three cross-sectional studies demonstrated a statistically significant reduction in RMSSD (MD -8.45ms, 95%CI-12.78, -4.12, p<0.0001) and SDNN (MD -9.93ms, 95%CI-14.82, -5.03, p<0.0001) (low QoE) in participants with TI relative to the uninjured control. The pooled analysis of four studies showed a higher LF: HF ratio among injured versus uninjured (SMD 0.20, 95%CI 0.01-0.39, p<0.04) (very low QoE). Albeit low QoE, non-acute TI is associated with attenuated HRV indicating autonomic imbalance. The findings might explain greater cardiovascular risk following TI. Trial registration PROSPERO registration number: CRD: CRD42021298530.

Early heart rate variability evaluation enables to predict ICU patients' outcome

Heart rate variability (HRV) is a mean to evaluate cardiac effects of autonomic nervous system activity, and a relation between HRV and outcome has been proposed in various types of patients. We attempted to evaluate the best determinants of such variation in survival prediction using a physiological data-warehousing program. Plethysmogram tracings (PPG) were recorded at 75 Hz from the standard monitoring system, for a 2 h period, during the 24 h following ICU admission. Physiological data recording was associated with metadata collection. HRV was derived from PPG in either the temporal and non-linear domains. 540 consecutive patients were recorded. A lower LF/HF, SD2/SD1 ratios and Shannon entropy values on admission were associated with a higher ICU mortality. SpO2/FiO2 ratio and HRV parameters (LF/HF and Shannon entropy) were independent correlated with mortality in the multivariate analysis. Machine-learning using neural network (kNN) enabled to determine a simple decision tree combining the three best determinants (SDNN, Shannon Entropy, SD2/SD1 ratio) of a composite outcome index. HRV measured on admission enables to predict outcome in the ICU or at Day-28, independently of the admission diagnosis, treatment and mechanical ventilation requirement.

Trial registration: ClinicalTrials.gov identifier NCT02893462.

Heart Rate Complexity in US Army Forward Surgical Teams During Pre Deployment Training

INTRODUCTION

For trauma triage, the US Army has developed a portable heart rate complexity (HRC) monitor, which estimates cardiac autonomic input and the activity of the hypothalamic-pituitary-adrenal (HPA) axis. We hypothesize that autonomic/HPA stress associated with predeployment training in U.S. Army Forward Surgical Teams will cause changes in HRC.

MATERIALS AND METHODS

A prospective observational study was conducted in 80 soldiers and 10 civilians at the U.S. Army Trauma Training Detachment. Heart rate (HR, b/min), cardiac output (CO, L/min), HR variability (HRV, ms), and HRC (Sample Entropy, unitless), were measured using a portable non-invasive hemodynamic monitor during postural changes, a mass casualty (MASCAL) situational training exercise (STX) using live tissue, a mock trauma (MT) STX using moulaged humans, and/or physical exercise.

RESULTS

Baseline HR, CO, HRV, and HRC averaged 72 ± 11b/min, 5.6 ± 1.2 L/min, 48 ± 24 ms, and 1.9 ± 0.5 (unitless), respectively. Supine to sitting to standing caused minimal changes. Before the MASCAL or MT, HR and CO both increased to ~125% baseline, whereas HRV and HRC both decreased to ~75% baseline. Those values all changed an additional ~5% during the MASCAL, but an additional 10 to 30% during the MT. With physical exercise, HR and CO increased to >200% baseline, while HRV and HRC both decreased to 40 to 60% baseline; these changes were comparable to those caused by the MT. All the changes were P < 0.05.

CONCLUSIONS

Various forms of HPA stress during Forward Surgical Team STXs can be objectively quantitated continuously in real time with a portable non-invasive monitor. Differences from resting baseline indicate stress anticipating an impending STX whereas differences between average and peak responses indicate the relative stress between STXs. Monitoring HRC could prove useful to field commanders to rapidly and objectively assess the readiness status of troops during STXs or repeated operational missions. In the future, health care systems and regulatory bodies will likely be held accountable for stress in their trainees and/or obliged to develop wellness options and standardize efforts to ameliorate burnout, so HRC metrics might have a role, as well.

Prognostic value of variables derived from heart rate variability in patients with traumatic brain injury after decompressive surgery

Measurement of heart rate variability can reveal autonomic nervous system function. Changes in heart rate variability can be associated with disease severity, risk of complications, and prognosis. We aimed to investigate the prognostic value of heart rate variability measurements in patients with moderate-to-severe traumatic brain injury after decompression surgery. We conducted a prospective study of 80 patients with traumatic brain injury after decompression surgery using a noninvasive electrocardiography device for data collection. Assessment of heart rate variability parameters included the time and frequency domains. The correlations between heart rate variability parameters and one-year mortality and functional outcomes were analyzed. Time domain measures of heart rate variability, using the standard deviation of the RR intervals and the square root of the mean squared differences of successive RR intervals, were statistically significantly lower in the group of patients with unfavorable outcomes and those that died. In frequency domain analysis, very low-frequency and total power were significantly higher in patients with favorable functional outcomes. High-frequency, low-frequency, and total power were statistically significantly higher in patients who survived for more than one year. Multivariate analysis using a model combining age and the Glasgow Coma Scale score with variables derived from heart rate variability substantially improved the prognostic value for predicting long-term outcome. These findings reinforced the concept that traumatic brain injury impacts the brain-heart axis and cardiac autonomic modulation even after decompression surgery, and variables derived from heart rate variability may be useful predictors of outcome.

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.

Electrocardiogram Sampling Frequency Range Acceptable for Heart Rate Variability Analysis

Objectives

Heart rate variability (HRV) has gained recognition as a noninvasive marker of autonomic activity. HRV is considered a promising tool in various clinical scenarios. The optimal electrocardiogram (ECG) sampling frequency required to ensure sufficient precision of R–R intervals for HRV analysis has not yet been determined. Here, we aimed to determine the acceptable ECG sampling frequency range by analyzing ECG signals from patients who visited an emergency department with the chief complaint of acute intoxication or overdose.

Methods

The study included 83 adult patients who visited an emergency department with the chief complaint of acute poisoning. The original 1,000-Hz ECG signals were down-sampled to 500-, 250-, 100-, and 50-Hz sampling frequencies with linear interpolation. R–R interval data were analyzed for time-domain, frequency-domain, and nonlinear HRV parameters. Parameters derived from the data on down-sampled frequencies were compared with those derived from the data on 1,000-Hz signals, and Lin's concordance correlation coefficients were calculated.

Results

Down-sampling to 500 or 250 Hz resulted in excellent concordance. Signals down-sampled to 100 Hz produced acceptable results for time-domain analysis and Poincaré plots, but not for frequency-domain analysis. Down-sampling to 50 Hz proved to be unacceptable for both time- and frequency-domain analyses. At 50 Hz, the root-mean-squared successive differences and the power of high frequency tended to have high values and random errors.

Conclusions

A 250-Hz sampling frequency would be acceptable for HRV analysis. When frequency-domain analysis is not required, a 100-Hz sampling frequency would also be acceptable.

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 matching of sinus arrhythmia to respiration: are trauma patients without serious injury comparable to healthy laboratory subjects?

We sought to better understand the physiology underlying the metrics of heart rate variability (HRV) in trauma patients without serious injury, compared to healthy laboratory controls. In trauma patients without serious injury (110 subjects, 470 2-min data segments), we studied the correlation between sinus arrhythmia (SA) rate, heart rate (HR), and respiratory rate (RR). Most segments with 2.4 < HR/RR < 4.8 exhibited SA-RR matching, whereas rate matching was absent in 81% of the segments with HR/RR < 2.4 and in 86% of the segments with HR/RR > 4.8. The findings were comparable, in some cases remarkably so, to previous reports from healthy laboratory subjects. The presence (or absence) of SA-RR matching, when SA is largely controlled by respiration, can be anticipated in this trauma population. This work provides a valuable step towards the definition of patterns of HRV found in trauma patients with and without life-threatening injury.

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

BACKGROUND

Heart rate complexity (HRC), commonly described as a "new vital sign," has shown promise in predicting injury severity, but its use in clinical practice has been precluded by the absence of real-time data. This study was conducted to evaluate the utility of real-time, automated, instantaneous, hand-held heart rate entropy analysis in predicting the need for lifesaving interventions (LSIs). We hypothesized that real-time HRC would predict LSIs.

METHODS

Prospective enrollment of patients who met criteria for trauma team activation was conducted at a Level I trauma center (September 2011 to February 2012). A novel, hand-held, portable device was used to measure HRC (by sample entropy) and time-domain heart rate variability continuously in real time for 2 hours after the moment of presentation. Electric impedance cardiography was used to determine cardiac output. Patients who received an LSI were compared with patients without any intervention (non-LSI). Multivariable analysis was performed to control for differences between the groups.

RESULTS

Of 82 patients enrolled, 21 (26%) received 67 LSIs within 24 hours of hospital arrival. Initial systolic blood pressure was similar in both groups. LSI patients had a lower Glasgow Coma Scale (GCS) score (9.2 [5.1] vs. 14.9 [0.2], p < 0.0001). The mean (SD) HRC value on presentation was 0.8 (0.6) in the LSI group compared with 1.5 (0.6) in the non-LSI group (p < 0.0001). With the use of logistic regression, initial HRC was the only significant predictor of LSI. A cutoff value for HRC of 1.1 yields sensitivity, specificity, negative predictive value, and positive predictive value of 86%, 74%, 94%, and 53%, respectively, with an accuracy of 77% for predicting an LSI.

CONCLUSION

Decreased HRC on hospital arrival is an independent predictor of the need for LSI in trauma activation patients. Real-time HRC may be a useful adjunct to standard vital signs monitoring and predicts LSIs.

LEVEL OF EVIDENCE

Prognostic and diagnostic study, level III.

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.

Personalized medicine: genetic variation and loss of physiologic complexity are associated with mortality in 644 trauma patients

OBJECTIVE

Personalized medicine merges genetics, physiology, and patient outcome. Loss of physiologic complexity (heart rate [HR] variability) is a bedside biomarker for autonomic nervous system (ANS) dysfunction. We hypothesized that variability in ANS receptor proteins (genetics) and loss of complexity (physiology) are independently associated with mortality in critical illness.

SUMMARY BACKGROUND DATA

Decreased HR complexity has been associated with increased mortality and morbidity in trauma and other critically ill populations. Genetic variations in alpha-1A and beta-2 adrenergic receptors (ADRA1A, ADRB2) have been associated with changes in smooth muscle tone in various tissues, and implicated in bronchial hyper-responsiveness, metabolic syndrome, and other disorders.

METHODS

A cohort of 644 trauma intensive care unit (ICU) admissions had complexity data and genetic samples. Two ANS receptor polymorphisms (rs1048101, Alpha ADRA1A and rs1042714, Beta ADRB2) were genotyped. Physiologic complexity at various points in the ICU stay was measured using previously-studied integer HR multiscale entropy (MSE) over 6-hour intervals (~21,600 HR data points/interval/patient). Logistic regression assessed the concurrent relationship of genotypes, complexity, and probability of survival, an acuity score incorporating age, injury mechanism/severity, and admission vitals, to risk of death.

RESULTS

Of total, 96 patients (15%) died. Nonsurvivors had lower complexity at early, middle, and late portions of ICU stay (median MSE at least 25% less in nonsurvivors, P < 0.001) and lower incidence of the GG ADRB2 genotype (7.5% vs. 18.3%, P < 0.001). In multivariable logistic regression, the GG ADRB2 genotype carried ~3-fold decrease in mortality odds (odd ratio [OR] = 0.33, P = 0.01), independent of significant effects in HR MSE (OR = 0.93, P < 0.001), and probability of survival (OR = 0.22, P < 0.001).

CONCLUSIONS

This first study to simultaneously examine ANS genetics, the biomarker complexity, and mortality concludes: (1) ANS genetics and physiologic complexity are independently related to mortality; (2) Genetics and complexity add information over traditional acuity scoring (probability of survival); and (3) Simultaneous assessment of ANS physiology and genetics may yield novel research, diagnostic, and therapeutic opportunities in critical illness.

Core temperature variation is associated with heart rate variability independent of cardiac index: a study of 278 trauma patients

PURPOSE

The purpose of this study is to determine if temperature extremes are associated with reduced heart rate variability (HRV) and "cardiac uncoupling."

MATERIALS AND METHODS

This was a retrospective, observational cohort study performed on 278 trauma intensive care unit admissions that had continuous HR, cardiac index (CI), and core temperature data from "thermodilution" Swan-Ganz catheter. Dense (captured second-by-second) physiologic data were divided into 5-minute intervals (N = 136 133; 11 344 hours of data). Mean CI, mean temperature, and integer HR SD were computed for each interval. Critically low HRV was defined as HR SD from 0.3 to 0.6 beats per minute. Temperature extremes were defined as less than 36°C or greater than 39°C.

RESULTS

Low HRV and CI vary with temperature. Temperature extremes are associated with increased risk for critically low HRV (odds ratio, >1.8). Cardiac index increases with temperature until hyperthermia (>40°C). At temperature extremes, changes in CI were not explained solely by changes in HR.

CONCLUSIONS

The conclusions of this study are (1) temperature extremes are associated with low HRV, potentially reflecting cardiac autonomic dysfunction; (2) CI increases with temperature; and (3) HRV provides additional physiologic information unobtainable via current invasive cardiac monitoring and current vital signs.

Clinical applications of heart rate variability in the triage and assessment of traumatically injured patients

Heart rate variability (HRV) is a method of physiologic assessment which uses fluctuations in the RR intervals to evaluate modulation of the heart rate by the autonomic nervous system (ANS). Decreased variability has been studied as a marker of increased pathology and a predictor of morbidity and mortality in multiple medical disciplines. HRV is potentially useful in trauma as a tool for prehospital triage, initial patient assessment, and continuous monitoring of critically injured patients. However, several technical limitations and a lack of standardized values have inhibited its clinical implementation in trauma. The purpose of this paper is to describe the three analytical methods (time domain, frequency domain, and entropy) and specific clinical populations that have been evaluated in trauma patients and to identify key issues regarding HRV that must be explored if it is to be widely adopted for the assessment of trauma patients.

Influence of acute epinephrine infusion on endotoxin-induced parameters of heart rate variability: a randomized controlled trial

OBJECTIVE

To determine whether the acute anti-inflammatory influence of epinephrine (EPI) extends to changes in heart rate variability (HRV) induced by the prototypical inflammatory stimulus, endotoxin (lipopolysaccharide [LPS]).

SUMMARY BACKGROUND DATA

HRV reflects fluctuating cardiac autonomic inputs and is acutely reduced during the systemic inflammation induced by LPS as well as during severe critical illnesses such as sepsis and traumatic injury. While EPI may diminish proinflammatory cytokine release, it is unknown whether this net anti-inflammatory activity extends to HRV.

METHODS

Healthy volunteers (n = 17) were randomized to either saline + LPS (2 ng/kg) or LPS + antecedent EPI infusion (30 ng/kg/min) from -3 to 6 hours relative to LPS. HRV and blood samples were obtained before EPI and LPS as well as hourly afterward. Plasma cytokines were measured by ELISA. Statistical analysis was by repeated measures analysis of variance. This study was registered at Clinicaltrials.gov and is listed under the following ID number: NCT00753402.

RESULTS

LPS acutely influenced all measured parameters of HRV including standard deviation of the average beat to beat intervals over a 5-minute period, percentage of interval differences of successive interbeat intervals greater than 50 milliseconds and square root of the mean squared differences, high frequency (HF), low frequency, low frequency/HF, and very low frequency (all P < 0.01). EPI infusion reduced the inflammatory cytokine response to LPS as measured by decreased TNFalpha, IL-6, and IL-8 (P < 0.01). Relative to the saline + LPS group, antecedent EPI infusion was associated with further reductions in parameters of HRV measuring vagal/parasympathetic activity including, percentage of interval differences of successive interbeat intervals greater than 50 milliseconds, square root of the mean squared differences, and HF (P < 0.05).

CONCLUSION

Prior EPI exposure exerts anti-inflammatory influences but also may reduce vagus nerve activity. Hence, acute EPI administration may be protective against early inflammatory challenges but diminish vagal nerve responsiveness to subsequent stimuli.

Early loss of heart rate complexity predicts mortality regardless of mechanism, anatomic location, or severity of injury in 2178 trauma patients

BACKGROUND

Reduced heart rate (HR) complexity (e.g., a lack of randomness or unpatterned variability) is an established predictor of trauma patient mortality. However, this finding has not been validated across the diverse spectrum of traumatic injury, and underlying mechanisms of this relationship are poorly understood.

MATERIALS AND METHODS

Two thousand one hundred seventy-eight trauma patients were admitted directly to the intensive care unit (ICU), and had sufficient (>6h) continuous integer heart rate data within the first d. Patients were stratified by location of isolated severe injury (head, torso, both, or neither), primary mechanism (blunt or penetrating), and probability of survival, an accepted scoring system based on age, admission vital signs, and injury type and severity. HR multiscale entropy (MSE) was calculated (sum of scales, Costa's algorithm, physionet.org, m=2, r=0.15) to estimate complexity. Univariate analysis was performed by comparing MSE between survivors and nonsurvivors in each subgroup. Multivariate analysis incorporated logistic regression to characterize the relationship between MSE and risk of death, controlling for probability of survival. The MSE odds ratios (OR) and area under the receiver operator curve (AUC) were calculated.

RESULTS

Reduced MSE was significantly associated with increasing mortality, and was independent of probability of survival in all multivariate analyses (OR 0.87-0.94). This range of odds ratios implies that a patient with an MSE of 15 has roughly a 2- to 6-fold increase in odds of death versus a patient with an MSE of 25. The relationship between MSE and death was moderately stronger in patients with isolated severe head injury versus torso injury, and significantly stronger in patients with penetrating versus blunt mechanism of injury. MSE measured early in the hospital stay remained a robust predictor of mortality in all subgroups, even stratified by narrow ranges of probability of survival.

CONCLUSIONS

Early reduction of heart rate complexity is an important risk factor across diverse injury etiology. This suggests common underlying physiologic mechanisms linking the loss of biologic complexity to death.