Anna E. Williams

Heart rate multiscale entropy at three hours predicts hospital mortality in 3,154 trauma patients.

Complexity is a measure of variation and randomness potentially indicating improvement or deterioration in critically ill patients. Previously, we have shown integer heart rate (HR) multiscale entropy (MSE), an indicator of complexity, predicts death based on long duration (12 h) and dense (≥0.4 Hz) windows of HR data. However, such restrictions reduce the use of MSE in the clinical setting. We hypothesized MSE predicts death using HR data of shorter duration and lower density. During the initial 24 h of intensive care unit stay, 3,154 patients had at least 3 h of continuous integer HR sampled. The first continuous window of 3, 6, 9, and 12 h was selected for each patient regardless of density, and an open-source MSE algorithm was applied (M. Costa, www.physionet.org; m = 2; r = 0.15). Risk of death based on MSE, alone and with covariates (age, sex, injury severity score), was assessed using randomly selected logistic regression in half of the cases. Area under the receiver operator curve (AUC) was computed in the other half in subgroups having various durations and densities of HR data. At days 2.3 (median) and 4.9 (mean), 441 patients (14%) died. Multiscale entropy stratified patients by mortality and was an independent predictor of death using 3 h or more of data. Multiscale entropy alone (AUC = 0.66 - 0.71) predicted death comparably to covariates alone (AUC = 0.72). We conclude: (1) Heart rate MSE within hours of admission predicts death occurring days later. (2) Multiscale entropy is robust to variation in bedside data duration and density occurring in a working intensive care unit. (3) Complexity may be a new clinical biomarker of outcome.ABBREVIATIONS-AUC-area under receiver operator characteristic curve; HR-heart rate; HRV/HRVi-heart rate/integer heart rate variability; ICU-intensive care unit; IRB-institutional review board; ISS-injury severity score; MSE-multiscale entropy; OR-odds ratio; SIMON-signal interpretation and monitoring; TRACS-Trauma Registry of the American College of Surgeons; VUMC-Vanderbilt University Medical Center

Cardiac uncoupling and heart rate variability stratify ICU patients by mortality : A study of 2088 trauma patients

Objective:We have previously shown that cardiac uncoupling (reduced heart rate variability) in the first 24 hours of trauma ICU stay is a robust predictor of mortality. We hypothesize that cardiac uncoupling over the entire ICU stay independently predicts mortality, reveals patterns of injury, and heralds complications. Methods:A total of 2088 trauma ICU patients satisfied the inclusion criteria for this study. Cardiac uncoupling by outcome was compared using the Wilcoxon rank sum test. Risk of death from cardiac uncoupling and covariates (age, ISS, AIS Head Score, total transfusion requirements) was assessed using multivariate logistic regression models at each ICU day. Univariate logistic regression was used to assess risk of death from uncoupling irrespective of covariates at each ICU day. Results:A total of 1325 (63.5%) patients displayed some degree of uncoupling over their ICU stay. The difference in uncoupling between survivors and nonsurvivors is both dramatic and consistent across the entire ICU stay, indicating that the presence of uncoupling is unrelated to the cause of death. However, the magnitude of uncoupling varies by day when data is stratified by cause of death. Conclusions:Cardiac uncoupling: 1) is an independent predictor of death throughout the ICU stay, 2) has a predictive window of 2 to 4 days, and 3) appears to increase in response to inflammation, infection, and multiple organ failure.

Cardiac uncoupling and heart rate variability are associated with intracranial hypertension and mortality: a study of 145 trauma patients with continuous monitoring.

BACKGROUND A noninvasive tool reflecting intracranial hypertension (ICH) should prompt early invasive monitoring and reduce secondary injury after traumatic brain injury. We hypothesized that integer heart rate variability (HRV) may be associated with rises in intracranial pressure (ICP); changes in HRV may precede changes in ICP; and both increases in ICP and cardiac uncoupling (low HRV) predict mortality. METHODS Of 14,330 consecutive trauma admissions, 291 of these patients had an injury requiring intracranial monitoring. Of these patients 145 had simultaneous HRV and ICP monitoring with a Camino monitor. ICP and heart rate (HR) data were matched and divided into 5-minute intervals (N = 117,956, representing 24.4 million HR and ICP data points). In each interval, the median ICP, and SD of HR (HRSD5) were calculated. Cardiac uncoupling was defined as an interval with HRSD5 between 0.3 bpm and 0.6 bpm. Cardiac uncoupling was compared between ICP categories using the Wilcoxon Rank-Sum test, and logistic regression was used to assess the continuous relationship between ICP and risk of uncoupling. RESULTS Cardiac uncoupling increases as ICP increases (p < 0.001). Uncoupling nearly doubles when comparing acceptable ICP (<20 mm Hg, 11% uncoupled) to ICH (31-50 mm Hg, 18% uncoupled), with uncoupling = 13% in the intermediate group (ICP 21-30 mm Hg). This trend continues at the level of malignant ICH (>50 mm Hg, 22% uncoupled). CONCLUSION Cardiac uncoupling increases as ICP increases. Both cardiac uncoupling and ICH predict mortality. Cardiac uncoupling may precede ICH but is not yet an indication for invasive monitoring.

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.

Genetic Variation in the Autonomic Nervous System Affects Mortality: A Study of 1,095 Trauma Patients

BACKGROUND We have previously demonstrated an unappreciated link between the autonomic nervous system and mortality, heart rate variability, and physiologic complexity. STUDY DESIGN Genetic variation in adrenergic receptors or key enzymes in catecholamine degradation could be associated with, and potentially explain, autonomic nervous system dysfunction and its impact on mortality after severe trauma. Three genetic polymorphisms critical to the adrenergic pathway were evaluated: beta-2 adrenergic receptor (ADBR2: Q27E), alpha-1a adrenergic receptor (ADRA1A:R347C), and catechol-O-methyl transferase (COMT: V158M). The study population consisted of 1,095 trauma admissions between April 2005 and April 2007. These patients all had genotyping performed using mass spectrometric analysis (Sequenom, Inc). The genetic data were linked with detailed demographic and clinical data. Trauma Related Injury Severity Score (TRISS) probability of survival was used as a composite measure of injury severity, admission physiology, and demographic factors in the multivariate logistic regression analyses of mortality outcomes data. RESULTS The overall mortality rate for the study population was 14.2% (155 of 1,095). Univariate comparisons of genotypes with mortality revealed a significant association with the ADBR2 polymorphism: CC=15.9%, GC=14.8% and GG=7.6%, p=0.02. The apparently protective ADBR2 GG genotype was seen in 15.5% (170 of 1,095) of the study population. In multivariate analysis, which included adjustment for TRISS, the ADBR2 GG genotype was associated with reduced mortality (odds ratio 0.36, p=0.002). CONCLUSIONS Genetic variation in the beta-2 adrenergic receptor (ADBR2:Q27E) associated with bronchial constriction appears protective (odds ratio 0.36), perhaps by making the receptor resistant to downregulation. These genetic data support the emerging understanding of critical role of the autonomic nervous system in the response to injury.

Genetic variation in complement component 2 of the classical complement pathway is associated with increased mortality and infection: a study of 627 patients with trauma.

BACKGROUND Trauma is a disease of inflammation. Complement Component 2 (C2) is a protease involved in activation of complement through the classical pathway and has been implicated in a variety of chronic inflammatory diseases. We hypothesized that genetic variation in C2 (E318D) identifies a high-risk subgroup of patients with trauma reflecting increased mortality and infection (ventilator-associated pneumonia [VAP]). Consequently, genetic variation in C2 may stratify patient risk and illuminate underlying mechanisms for therapeutic intervention. METHODS DNA samples from 702 patients with trauma were genotyped for C2 E318D and linked with covariates (age: mean 42.8 years, gender: 74% male, ethnicity: 80% white, mechanism: 84% blunt, injury severity score: mean 25.0, admission lactate: mean 3.13 mEq/L) and outcomes: mortality 9.9% and VAP: 18.5%. VAP was defined by quantitative bronchoalveolar lavage (> 10). Multivariate regression analysis determined the relationship of genotype and covariates to risk of death and VAP. However, patients with injury severity score > or = 45 were excluded from the multivariate analysis, as magnitude of injury overwhelms genetics and covariates in determining outcome. RESULTS Fifty-two patients (8.3%) had the high-risk heterozygous genotype, associated with a significant increase in mortality and VAP. CONCLUSION In 702 patients with trauma, 8.3% had a high-risk genetic variation in C2 associated with increased mortality (odds ratio = 2.65) and infection (odds ratio = 2.00). This variation: (1) identifies a previously unknown high-risk group for infection and mortality; (2) can be determined at admission; (3) may provide opportunity for early therapeutic intervention; and (4) requires validation in a distinct cohort of patients.