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

The value of circadian heart rate variability for the estimation of obstructive sleep apnea severity in adult males

OBJECTIVES

Heart rate variability (HRV) is becoming more prevalent as a measurable parameter in wearable sleep-monitoring devices, which are simple and effective instruments for illness evaluation. Currently, most studies on investigating OSA severity and HRV have measured heart rates during wakefulness or sleep. Therefore, the objective of this study was to investigate the circadian rhythm of HRV in male patients with OSA and its value for the estimation of OSA severity using group-based trajectory modeling.

METHODS

Patients with complaints of snoring were enrolled from the Sleep Center of Shandong Qianfoshan Hospital. Patients were divided into 3 groups according to apnea hypopnea index (AHI in events/h), as follows: (<15, 15≤AHI<30, and ≥30). HRV parameters were calculated using 24 h Holter monitoring, which included time-domain and frequency-domain indices. Circadian differences in the standard deviation of normal to normal (SDNN) were evaluated for OSA severity using analysis of variance, trajectory analysis, and multinomial logistic regression.

RESULTS

A total of 228 patients were enrolled, 47 with mild OSA, 48 moderate, and 133 severe. Patients with severe OSA exhibited reduced triangular index and higher very low frequency than those in the other groups. Circadian HRV showed that nocturnal SDNN was considerably higher than daytime SDNN in patients with severe OSA. The difference among the OSA groups was significant at 23, 24, 2, and 3 o'clock sharp between the severe and moderate OSA groups (all P<0.05). The heterogeneity of circadian HRV trajectories in OSA was strongly associated with OSA severity, including sleep structure and hypoxia-related parameters. Among the low-to-low, low-to-high, high-to-low, and high-to-high groups, OSA severity in the low-to-high group was the most severe, especially compared with the low-to-low and high-to-low SDNN groups, respectively.

CONCLUSIONS

Circadian HRV in patients with OSA emerged as low daytime and high nocturnal in SDNN, particularly in men with severe OSA. The heterogeneity of circadian HRV revealed that trajectories with low daytime and significantly high nighttime were more strongly associated with severe OSA. Thus, circadian HRV trajectories may be useful to identify the severity of OSA.

The Influence of Physical and Mental Health Mediators on the Relationship Between Combat-Related Traumatic Injury and Ultra-Short-Term Heart Rate Variability in a U.K. Military Cohort: A Structural Equation Modeling Approach

INTRODUCTION

Combat-related traumatic injury (CRTI) adversely affects heart rate variability (HRV). The mediating effect of mental and physical health factors on the relationship between CRTI, its severity and HRV has not been previously studied and investigated.

MATERIALS AND METHODS

A cross-sectional mediation analysis of the ArmeD SerVices TrAuma and RehabilitatioN OutComE (ADVANCE) prospective cohort study was performed. The sample consisted of injured and uninjured British male servicemen who were frequency-matched based on their age, rank, role-in-theater, and deployment to Afghanistan (2003-2014). CRTI and injury severity (the New Injury Severity Scores [NISS] [NISS < 25 and NISS ≥ 25]) were included as exposure variables. HRV was quantified using the root mean square of successive differences (RMSSD) obtained using pulse waveform analysis. Depression and anxiety mediators were quantified using the Patient Health Questionnaire and Generalized Anxiety Disorder, respectively. Body mass index and the 6-minute walk test (6MWT) represented physical health measures. Two mediation pathways between exposure and outcome variables were examined in comparison with the uninjured group using structural equation modeling.

RESULTS

Of 862 servicemen, 428 were injured and 434 were uninjured with the mean age at assessment of 33.9 ± 5.4 (range 23-59) years. Structural equation modeling revealed that depression, anxiety, and body mass index did not significantly mediate the relationship between injury/injury severity and RMSSD. However, the 6MWT significantly mediated the relationship between CRTI and RMSSD (27% mediation). The indirect effect of 6MWT on the relationship between injury severity (NISS ≥ 25 vs. uninjured) and RMSSD was -0.06 (95% CI: -0.12, -0.00, P < .05).

CONCLUSIONS

The findings suggest that greater physical function may improve HRV following CRTI. Longitudinal studies are warranted to further validate these findings.

Central autonomic network and early prognosis in patients with disorders of consciousness

The central autonomic network (CAN) plays a crucial role in modulating the autonomic nervous system. Heart rate variability (HRV) is a valuable marker for assessing CAN function in disorders of consciousness (DOC) patients. We used HRV analysis for early prognosis in 58 DOC patients enrolled within ten days of hospitalization. They underwent a five-minute electrocardiogram during baseline and acoustic/visual stimulation. The coma recovery scale-revised (CRS-R) was used to define the patient's consciousness level and categorize the good/bad outcome at three months. The high-frequency Power Spectrum Density and the standard deviation of normal-to-normal peaks in baseline, the sample entropy during the stimulation, and the time from injury features were used in the support vector machine analysis (SVM) for outcome prediction. The SVM predicted the patients' outcome with an accuracy of 96% in the training test and 100% in the validation test, underscoring its potential to provide crucial clinical information about prognosis.

Relationship between combat-related traumatic injury and ultrashort term heart rate variability in a UK military cohort: findings from the ADVANCE study

INTRODUCTION

Combat-related traumatic injury (CRTI) has been linked to an increased cardiovascular disease (CVD) risk. The long-term impact of CRTI on heart rate variability (HRV)-a robust CVD risk marker-has not been explored. This study investigated the relationship between CRTI, the mechanism of injury and injury severity on HRV.

METHODS

This was an analysis of baseline data from the ArmeD SerVices TrAuma and RehabilitatioN OutComE (ADVANCE) prospective cohort study. The sample consisted of UK servicemen with CRTI sustained during deployment (Afghanistan, 2003-2014) and an uninjured comparison group who were frequency matched to the injured group based on age, rank, deployment period and role in theatre. Root mean square of successive differences (RMSSD) was measured as a measure of ultrashort term HRV via <16 s continuous recording of the femoral arterial pulse waveform signal (Vicorder). Other measures included injury severity (New Injury Severity Scores (NISS)) and injury mechanism.

RESULTS

Overall, 862 participants aged 33.9±5.4 years were included, of whom 428 (49.6%) were injured and 434 (50.3%) were uninjured. The mean time from injury/deployment to assessment was 7.91±2.05 years. The median (IQR) NISS for those injured was 12 (6-27) with blast being the predominant injury mechanism (76.8%). The median (IQR) RMSSD was significantly lower in the injured versus the uninjured (39.47 ms (27.77-59.77) vs 46.22 ms (31.14-67.84), p<0.001). Using multiple linear regression (adjusting for age, rank, ethnicity and time from injury), geometric mean ratio (GMR) was reported. CRTI was associated with a 13% lower RMSSD versus the uninjured group (GMR 0.87, 95% CI 0.80-0.94, p<0.001). A higher injury severity (NISS ≥25) (GMR 0.78, 95% CI 0.69-0.89, p<0.001) and blast injury (GMR 0.86, 95% CI 0.79-0.93, p<0.001) were also independently associated with lower RMSSD.

CONCLUSION

These results suggest an inverse association between CRTI, higher severity and blast injury with HRV. Longitudinal studies and examination of potential mediating factors in this CRTI-HRV relationship are needed.

Normative values of resting heart rate variability in young male contact sport athletes: Reference values for the assessment and treatment of concussion

Objective

The objective of this study was to identify the main determinants of heart rate variability (HRV) in male athletes aged 14 to 21 years who practice competitive contact sports and to integrate these determinants with the aim of defining normative values of short-term HRV in the time and frequency domains.

Methods

Participants (n = 369) were aged 14 to 21 years and included 221 football players and 148 ice hockey players. HRV was measured for 5 min at rest, and standard HRV parameters in the time and frequency domains were calculated. Heart rate (HR), age, body mass index (BMI), number of sports weekly practices (WSP) and concussion history (mTBI) were considered determinants potentially able to influence HRV.

Results

Multiple regression analysis revealed that HR was the primary determinant of standard HRV parameters. The models accounted for 13% to 55% of the total variance of HRV and the contribution of HR to this model was the strongest (β ranged from -0.34 to -0.75). HR was the only determinant that significantly contributes to all HRV parameters. To counteract this dependence, we calculated HRV corrected by the mean RR interval (RRm). Such corrections do not remove any physiological differences in HRV; they simply remove the mathematical bias. HRV parameters were therefore normalized, and their normative limits were developed relative to the mean heart rate. After correction, the correlation coefficients between HR and all corrected HRV parameters were not statistically significant and ranged from -0.001 to 0.045 (p > 0.40 for all). The automatically corrected HRV calculator, which recalculates standard HRV parameters and converts them into corrected parameters in addition to determining whether a given value is within normal limits, facilitates clinical interpretation.

Conclusion

This study provides for the first time corrected normative values of short-term and resting state HRV parameters in competitive contact sport athletes aged 14 to 21 years. These values were developed independently of the major determinants of HRV. The baseline values for HRV parameters given here could be used in clinical practice when assessing and monitoring cerebral concussions. They may assist in decision making for a safe return to play.

Heart rate complexity: An early prognostic marker of patient outcome after cardiac arrest

OBJECTIVE

Early prognostication in comatose patients after cardiac arrest (CA) is difficult but essential to inform relatives and optimize treatment. Here we investigate the predictive value of heart-rate variability captured by multiscale entropy (MSE) for long-term outcomes in comatose patients during the first 24 hours after CA.

METHODS

In this retrospective analysis of prospective multi-centric cohort, we analyzed MSE of the heart rate in 79 comatose patients after CA while undergoing targeted temperature management and sedation during the first day of coma. From the MSE, two complexity indices were derived by summing values over short and long time scales (CI_s and CI_l). We splitted the data in training and test datasets for analysing the predictive value for patient outcomes (defined as best cerebral performance category within 3 months) of CI_s and CI_l.

RESULTS

Across the whole dataset, CI_l provided the best sensitivity, specificity, and accuracy (88%, 75%, and 82%, respectively). Positive and negative predictive power were 81% and 84%.

CONCLUSIONS

Characterizing the complexity of the ECG in patients after CA provides an accurate prediction of both favorable and unfavorable outcomes.

SIGNIFICANCE

The analysis of heartrate variability by means of MSE provides accurate outcome prediction on the first day of coma.

Pain Perception in Disorder of Consciousness: A Scoping Review on Current Knowledge, Clinical Applications, and Future Perspective

Pain perception in individuals with prolonged disorders of consciousness (PDOC) is still a matter of debate. Advanced neuroimaging studies suggest some cortical activations even in patients with unresponsive wakefulness syndrome (UWS) compared to those with a minimally conscious state (MCS). Therefore, pain perception has to be considered even in individuals with UWS. However, advanced neuroimaging assessment can be challenging to conduct, and its findings are sometimes difficult to be interpreted. Conversely, multichannel electroencephalography (EEG) and laser-evoked potentials (LEPs) can be carried out quickly and are more adaptable to the clinical needs. In this scoping review, we dealt with the neurophysiological basis underpinning pain in PDOC, pointing out how pain perception assessment in these individuals might help in reducing the misdiagnosis rate. The available literature data suggest that patients with UWS show a more severe functional connectivity breakdown among the pain-related brain areas compared to individuals in MCS, pointing out that pain perception increases with the level of consciousness. However, there are noteworthy exceptions, because some UWS patients show pain-related cortical activations that partially overlap those observed in MCS individuals. This suggests that some patients with UWS may have residual brain functional connectivity supporting the somatosensory, affective, and cognitive aspects of pain processing (i.e., a conscious experience of the unpleasantness of pain), rather than only being able to show autonomic responses to potentially harmful stimuli. Therefore, the significance of the neurophysiological approach to pain perception in PDOC seems to be clear, and despite some methodological caveats (including intensity of stimulation, multimodal paradigms, and active vs. passive stimulation protocols), remain to be solved. To summarize, an accurate clinical and neurophysiological assessment should always be performed for a better understanding of pain perception neurophysiological underpinnings, a more precise differential diagnosis at the level of individual cases as well as group comparisons, and patient-tailored management.

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.

Delirium in patients with hip fracture is associated with increased heart rate variability

BACKGROUND

Heart rate variability (HRV) is a method to assess the autonomic nervous system and reflects possibly central brain states. HRV has previously not been examined in patients with hip fracture and delirium.

AIMS

To explore HRV parameters in hip fracture patients with and without delirium.

METHODS

Patients admitted to Oslo University Hospital with hip fracture and sinus rhythm in electrocardiogram (ECG) were included. Delirium was diagnosed using the confusion assessment method. HRV was assessed preoperatively after a relaxing period of five minutes, by measuring an ECG signal over 5 min. Parameters in time domain (the standard deviation of the QRS distances-SDNN) and frequency domain (total power (TP), low frequency (LF), high frequency (HF) and LF/HF ratio) were calculated.

RESULTS

Seventy-five patients were included in the study, and 21 of them had subsyndromal delirium and were excluded from the analysis. Fifty-four patients with a mean age of 83.5 years (SD 8.6, 78% females) were included. Twenty-six patients (48%) had preoperative delirium, 11 (20%) developed delirium postoperatively, whereas 17 (31%) never developed delirium. SDNN, TP and HF values were significantly higher in patients with delirium compared to patients without delirium, and LF and LF/HF were lower. Patients developing postoperative delirium had decreased LF and increased HF before symptom onset.

DISCUSSION

Increased SDNN, TP and HF and decreased LF values might reflect an abnormal stress response in delirium.

CONCLUSION

HRV measurements in patients with hip fractures provide additional information beyond heart rate and might be used to identify relevant pathophysiological factors in delirium.

The Trace Conditional Learning of the Noxious Stimulus in UWS Patients and Its Prognostic Value in a GSR and HRV Entropy Study

The assessment of the consciousness level of Unresponsive Wakefulness Syndrome (UWS) patients often depends on a subjective interpretation of the observed spontaneous and volitional behavior. To date, the misdiagnosis level is around 30%. The aim of this study was to observe the behavior of UWS patients, during the administration of noxious stimulation by a Trace Conditioning protocol, assessed by the Galvanic Skin Response (GSR) and Heart Rate Variability (HRV) entropy. We recruited 13 Healthy Control (HC) and 30 UWS patients at 31 ± 9 days from the acute event evaluated by Coma Recovery Scale–Revised (CRS-R) and Nociception Coma Scale (NCS). Two different stimuli [musical stimulus (MUS) and nociceptive stimulus (NOC)], preceded, respectively by two different tones, were administered following the sequences (A) MUS1 – NOC1 – MUS2 – MUS3 – NOC2 – MUS4 – NOC3 – NOC^*, and (B) MUS1^*, NOC1^*, NOC2^*, MUS2^*, NOC3^*, MUS3^*, NOC4^*, MUS4^*. All the (^*) indicate the only tones administration. CRS-R and NCS assessments were repeated for three consecutive weeks. MUS4, NOC3, and NOC^* were compared for GSR wave peak magnitude, time to reach the peak, and time of wave's decay by Wilcoxon's test to assess the Conditioned Response (CR). The Sample Entropy (SampEn) was recorded in baseline and both sequences. Machine Learning approach was used to identify a rule to discriminate the CR. The GSR magnitude of CR was higher comparing music stimulus (p < 0.0001) and CR extinction (p < 0.002) in nine patients and in HC. Patients with CR showed a higher SampEn in sequence A compared to patients without CR. Within the third and fourth weeks from protocol administration, eight of the nine patients (88.9%) evolved into MCS. The Machine-learning showed a high performance to differentiate presence/absence of CR (≥95%). The possibility to observe the CR to the noxious stimulus, by means of the GSR and SampEn, can represent a potential method to reduce the misdiagnosis in UWS patients.

Heart Rate Variability as a Biomarker of Neurocardiogenic Injury After Subarachnoid Hemorrhage

BACKGROUND

The objective of this study was to examine whether heart rate variability (HRV) measures can be used to detect neurocardiogenic injury (NCI).

METHODS

Three hundred and twenty-six consecutive admissions with aneurysmal subarachnoid hemorrhage (SAH) met criteria for the study. Of 326 subjects, 56 (17.2%) developed NCI which we defined by wall motion abnormality with ventricular dysfunction on transthoracic echocardiogram or cardiac troponin-I > 0.3 ng/mL without electrocardiogram evidence of coronary artery insufficiency. HRV measures (in time and frequency domains, as well as nonlinear technique of detrended fluctuation analysis) were calculated over the first 48 h. We applied longitudinal multilevel linear regression to characterize the relationship of HRV measures with NCI and examine between-group differences at baseline and over time.

RESULTS

There was decreased vagal activity in NCI subjects with a between-group difference in low/high frequency ratio (β 3.42, SE 0.92, p = 0.0002), with sympathovagal balance in favor of sympathetic nervous activity. All time-domain measures were decreased in SAH subjects with NCI. An ensemble machine learning approach translated these measures into a classification tool that demonstrated good discrimination using the area under the receiver operating characteristic curve (AUROC 0.82), the area under precision recall curve (AUPRC 0.75), and a correct classification rate of 0.81.

CONCLUSIONS

HRV measures are significantly associated with our label of NCI and a machine learning approach using features derived from HRV measures can classify SAH patients that develop NCI.

What impact can hospitalization environment produce on the ANS functioning in patients with Unresponsive Wakefulness Syndrome? - 24-hour monitoring

Objectives: Studies showed that the recovery of patients with Unresponsive Wakefulness Syndrome (UWS) is also correlated to the recovery of circadian rhythms. In this study, we observed the correlations between patients with UWS biometrical and ambient parameters. Methods: A dedicated monitoring system was realized to record and correlate the level of noise and luminosity with biometric Heart Rate (HR), Heart Rate Variability (HRV) and Breath Rate (BR) parameters. Eleven patients with UWS were recruited and monitored for 13 ± 7 days. Correlation of ambient and biometric parameters was analyzed by Spearman's test. Wilcoxon's test was used to compare the biometric parameters in two different moments of daily activity in the rehabilitation unit (night and day). Patients showed a moderate negative or positive correlation between biometric and ambient parameters. Results: Significant differences between night and morning (0.0001 < p ≤ 0.001) were found for HR, HRV and BR in seven, five and four patients, respectively, at Wilcoxon's test. HR and BR were higher during the night while HRV was lower. Conclusion: In patients with UWS, lower HRV and higher HR and BR during the night might be indicative of interference in sleep/wake cycles. The modifications of the environment surrounding the patient due to the unit procedures of the staff and/or some interaction modalities of the relatives may have an effect on residual endogenous mechanisms of self-regulation. However, differences between night and day in the biometrical parameters are not necessarily linked to the changes in the environment care unit.

Circadian Rhythms and Measures of CNS/Autonomic Interaction

The physiological role and relevance of the mechanisms sustaining circadian rhythms have been acknowledged. Abnormalities of the circadian and/or sleep-wakefulness cycles can result in major metabolic disorders or behavioral/professional inadequacies and stand as independent risk factors for metabolic, psychiatric, and cerebrovascular disorders and early markers of disease. Neuroimaging and clinical evidence have documented functional interactions between autonomic (ANS) and CNS structures that are described by a concept model (Central Autonomic Network) based on the brain-heart two-way interplay. The circadian rhythms of autonomic function, ANS-mediated processes, and ANS/CNS interaction appear to be sources of variability adding to a variety of environmental factors, and may become crucial when considering the ANS major role in internal environment constancy and adaptation that are fundamental to homeostasis. The CNS/ANS interaction has not yet obtained full attention and systematic investigation remains overdue.

Measures of CNS-Autonomic Interaction and Responsiveness in Disorder of Consciousness

Neuroimaging studies have demonstrated functional interactions between autonomic (ANS) and brain (CNS) structures involved in higher brain functions, including attention and conscious processes. These interactions have been described by the Central Autonomic Network (CAN), a concept model based on the brain-heart two-way integrated interaction. Heart rate variability (HRV) measures proved reliable as non-invasive descriptors of the ANS-CNS function setup and are thought to reflect higher brain functions. Autonomic function, ANS-mediated responsiveness and the ANS-CNS interaction qualify as possible independent indicators for clinical functional assessment and prognosis in Disorders of Consciousness (DoC). HRV has proved helpful to investigate residual responsiveness in DoC and predict clinical recovery. Variability due to internal (e.g., homeostatic and circadian processes) and environmental factors remains a key independent variable and systematic research with this regard is warranted. The interest in bidirectional ANS-CNS interactions in a variety of physiopathological conditions is growing, however, these interactions have not been extensively investigated in DoC. In this brief review we illustrate the potentiality of brain-heart investigation by means of HRV analysis in assessing patients with DoC. The authors' opinion is that this easy, inexpensive and non-invasive approach may provide useful information in the clinical assessment of this challenging patient population.

A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality. Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN). Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients.

Autonomic nervous system monitoring in intensive care as a prognostic tool. Systematic review

Objective

To present a systematic review of the use of autonomic nervous system monitoring as a prognostic tool in intensive care units by assessing heart rate variability.

Methods

Literature review of studies published until July 2016 listed in PubMed/Medline and conducted in intensive care units, on autonomic nervous system monitoring, via analysis of heart rate variability as a prognostic tool (mortality study). The following English terms were entered in the search field: ("autonomic nervous system" OR "heart rate variability") AND ("intensive care" OR "critical care" OR "emergency care" OR "ICU") AND ("prognosis" OR "prognoses" OR "mortality").

Results

There was an increased likelihood of death in patients who had a decrease in heart rate variability as analyzed via heart rate variance, cardiac uncoupling, heart rate volatility, integer heart rate variability, standard deviation of NN intervals, root mean square of successive differences, total power, low frequency, very low frequency, low frequency/high frequency ratio, ratio of short-term to long-term fractal exponents, Shannon entropy, multiscale entropy and approximate entropy.

Conclusion

In patients admitted to intensive care units, regardless of the pathology, heart rate variability varies inversely with clinical severity and prognosis.

Respiratory induced heart rate variability during slow mechanical ventilation : Marker to exclude brain death patients

BACKGROUND

Respiratory induced heart rate variability (rHRV) was analysed in mechanically ventilated patients during two levels of sedation and brain death. Our aim was to determine whether rHRV can distinguish between different levels of sedation and especially between brain death and sedated patients.

METHODS

In this study 30 critically ill and 23 brain death patients were included and four respiratory rates of 15, 12, 8 and 6 breaths per minute, each lasting 5 min were used. Two sedation levels, basal and deep, were performed in the critically ill patients. Heart rate and blood pressure changes induced by ventilation were subsequently detected and analysed.

RESULTS

Significant differences were found in rHRV and rHRV adjusted for tidal volume (rHRV/VT) between critically ill and brain death patients during slow breathing at 6 or 8 breaths per minute. The rHRV at 6 breaths per minute was below 15 ms in all brain death subjects except one. The rHRV/VT was lower than 25 ms/l at both 6 and 8 breaths per minute in all brain death patients and simultaneously at 75% of non-brain death patients was higher (specificity 1, sensitivity 0.24). Differences in rHRV and rHRV/VTs between basal and deep sedation were not significant.

CONCLUSIONS

The main clinical benefit of the study is the finding that rHRV and rHRV/VT during 6 and 8 breaths per minute can differentiate between critically ill and brain death patients. An rHRV/VT exceeding 25 ms/l reliably excludes brain death.

A novel cardiovascular risk stratification model incorporating ECG and heart rate variability for patients presenting to the emergency department with chest pain

BACKGROUND

Risk stratification models can be employed at the emergency department (ED) to evaluate patient prognosis and guide choice of treatment. We derived and validated a new cardiovascular risk stratification model comprising vital signs, heart rate variability (HRV) parameters, and demographic and electrocardiogram (ECG) variables.

METHODS

We conducted a single-center, observational cohort study of patients presenting to the ED with chest pain. All patients above 21 years of age and in sinus rhythm were eligible. ECGs were collected and evaluated for 12-lead ECG abnormalities. Routine monitoring ECG data were processed to obtain HRV parameters. Vital signs and demographic data were obtained from electronic medical records. Thirty-day major adverse cardiac events (MACE) were the primary endpoint, including death, acute myocardial infarction, and revascularization. Candidate variables were identified using univariate analysis; the model for the final risk score was derived by multivariable logistic regression. We compared the performance of the new model with that of the thrombolysis in myocardial infarct (TIMI) score using receiver operating characteristic (ROC) analysis.

RESULTS

In total, 763 patients were included in this study; 254 (33 %) met the primary endpoint, the mean age was 60 (σ = 13) years, and the majority was male (65 %). Nineteen candidate predictors were entered into the multivariable model for backward variable elimination. The final model contained 10 clinical variables, including age, gender, heart rate, three HRV parameters (average R-to-R interval (RR), triangular interpolation of normal-to-normal (NN) intervals, and high-frequency power), and four 12-lead ECG variables (ST elevation, ST depression, Q wave, and QT prolongation). Our proposed model outperformed the TIMI score for prediction of MACE (area under the ROC curve 0.780 versus 0.653). At the cutoff score of 9 (range 0-37), our model had sensitivity of 0.709 (95 % CI 0.653, 0.765), specificity of 0.674 (95 % CI 0.633, 0.715), positive predictive value of 0.520 (95 % CI 0.468, 0.573), and negative predictive value of 0.823 (95 % CI 0.786, 0.859).

CONCLUSIONS

A non-invasive and objective ECG- and HRV-based risk stratification tool performed well against the TIMI score, but future research warrants use of an external validation cohort.

How Can Music Influence the Autonomic Nervous System Response in Patients with Severe Disorder of Consciousness?

Activations to pleasant and unpleasant musical stimuli were observed within an extensive neuronal network and different brain structures, as well as in the processing of the syntactic and semantic aspects of the music. Previous studies evidenced a correlation between autonomic activity and emotion evoked by music listening in patients with Disorders of Consciousness (DoC). In this study, we analyzed retrospectively the autonomic response to musical stimuli by mean of normalized units of Low Frequency (nuLF) and Sample Entropy (SampEn) of Heart Rate Variability (HRV) parameters, and their possible correlation to the different complexity of four musical samples (i.e., Mussorgsky, Tchaikovsky, Grieg, and Boccherini) in Healthy subjects and Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) patients. The complexity of musical sample was based on Formal Complexity and General Dynamics parameters defined by Imberty's semiology studies. The results showed a significant difference between the two groups for SampEn during the listening of Mussorgsky's music and for nuLF during the listening of Boccherini and Mussorgsky's music. Moreover, the VS/UWS group showed a reduction of nuLF as well as SampEn comparing music of increasing Formal Complexity and General Dynamics. These results put in evidence how the internal structure of the music can change the autonomic response in patients with DoC. Further investigations are required to better comprehend how musical stimulation can modify the autonomic response in DoC patients, in order to administer the stimuli in a more effective way.

Predictive Potential of Heart Rate Complexity Measurement: An Indication for Laparotomy Following Solid Organ Injury

Background:

Nonlinear analysis of heart rate variability (HRV) has been recently used as a predictor of prognosis in trauma patients.

Objectives:

We applied nonlinear analysis of HRV in patients with blunt trauma and intraperitoneal bleeding to assess our ability to predict the outcome of conservative management.

Patients and Methods:

An analysis of electrocardiography (ECG) from 120 patients with blunt trauma was conducted at the onset of admission to the emergency department. ECGs of 65 patients were excluded due to inadequacy of noise-free length. Of the remaining 55 patients, 47 survived (S group) and eight patients died in the hospital (Non-S group). Nineteen patients were found to have intra-abdominal bleeding, eight of which ultimately underwent laparotomy to control bleeding (Op group) and 11 underwent successful non-operative management (non-Op). Demographic data including vital signs, glasgow coma scale (GCS), arterial blood gas and injury severity scores (ISS) were recorded. Heart rate complexity (HRC) methods, including entropy, were used to analyze the ECG.

Results:

There were no differences in age, gender, heart rate (HR) and blood pressure between the S and Non-S groups. However, approximate entropy, used as a method of HRC measurement, and GCS were significantly higher in S group, compared to the Non-S group. The base deficit and ISS were significantly higher in the Non-S group. Regarding age, sex, ISS, base deficit, vital signs and GCS, no difference was found between Op and Non-Op groups. Approximate entropy was significantly lower in the Op group, compared to the Non-Op group.

Conclusions:

The loss of HRC at the onset of admission may predict mortality in patients with blunt trauma. Lower entropy, in recently admitted patients with intra-abdominal bleeding, may indicate laparotomy when the vital signs are stable.

Residual vasomotor activity assessed by heart rate variability in a brain-dead case

A patient assessed by heart rate variability (HRV) methodology, beginning just after the completion of brain death (BD) diagnosis, showed remaining very low frequency (VLF) waves for approximately 10 min. A time-varying spectral analysis showed that during the first 550 s, a significant power spectral density remained in the high-frequency (HF), low-frequency (LF) and VLF bands. From 550 to 675 s, the HF oscillations totally vanished, and a marked progressive decay of the LF and VLF power density occurred. After 700 s the VLF undulations stopped and remaining small amplitude oscillations at 0.2 Hz coincided with the ventilator frequency. The VLF oscillations recorded in our case might be related to residual sympathetic vasomotor activity that progressively disappeared due to the extension of necrosis affecting the nervous centres of the lower part of the medulla and the first 2-3 cervical spine segments.

The impact of noise on the reliability of heart-rate variability and complexity analysis in trauma patients

This study focused on the impact of noise on the reliability of heart-rate variability and complexity (HRV, HRC) to discriminate between different trauma patients and to monitor individual patients. Life-saving interventions (LSIs) were chosen as an endpoint because performance of LSIs is a critical aspect of trauma patient care. Noise was modeled and simulated by modifying original R-R interval (RRI) sequences via decimation, concatenation, and division of RRIs, as well as R-wave detection using the electrocardiogram. Results showed that under increasing simulated noise, entropy and autocorrelation measures can still effectively discriminate between LSI and non-LSI patients and monitor individuals over time.

The effects of green tea consumption on cardiometabolic alterations induced by experimental diabetes

We evaluated cardiac autonomic modulation by heart rate (HRV), and arterial pressure variability (APV), and metabolic response in streptozotocin diabetic rats treated with green tea. Male Wistar rats were separated in groups: control, drinking tap water (C), green tea-treated (GT) group, diabetic, drinking tap water (D), and diabetic, treated with green tea (DGT). Kidney mass was greater in D and DGT than in C and GT, but reduced in DGT compared to D. Green tea prevented the increase in creatinine clearance and reduced hyperglycemia in DGT compared to D. Arterial pressure was increased in GT and decreased in D compared to C. HRV was reduced in D compared with all groups. APV was decreased in D compared to C and recovery in DGT. Sympathetic modulation of APV was decreased in D compared with all groups. Green tea reduced hyperglycemia, prevented renal injury and autonomic dysfunction, suggesting reduced cardiovascular risk and target organ damage in diabetes.

Heart Rate Variability during Simulated Hemorrhage with Lower Body Negative Pressure in High and Low Tolerant Subjects

Heart rate variability (HRV) decreases during hemorrhage, and has been proposed as a new vital sign to assess cardiovascular stability in trauma patients. The purpose of this study was to determine if any of the HRV metrics could accurately distinguish between individuals with different tolerance to simulated hemorrhage. Specifically, we hypothesized that (1) HRV would be similar in low tolerant (LT) and high tolerant (HT) subjects at presyncope when both groups are on the verge of hemodynamic collapse; and (2) HRV could distinguish LT subjects at presyncope from hemodynamically stable HT subjects (i.e., at a submaximal level of hypovolemia). Lower body negative pressure (LBNP) was used as a model of hemorrhage in healthy human subjects, eliciting central hypovolemia to the point of presyncopal symptoms (onset of hemodynamic collapse). Subjects were classified as LT if presyncopal symptoms occurred during the −15 to −60 mmHg levels of LBNP, and HT if symptoms occurred after LBNP of −60 mmHg. A total of 20 HRV metrics were derived from R–R interval measurements at the time of presyncope, and at one level prior to presyncope (submax) in LT and HT groups. Only four HRV metrics (Long-range Detrended Fluctuation Analysis, Forbidden Words, Poincaré Plot Descriptor Ratio, and Fractal Dimensions by Curve Length) supported both hypotheses. These four HRV metrics were evaluated further for their ability to identify individual LT subjects at presyncope when compared to HT subjects at submax. Variability in individual LT and HT responses was so high that LT responses overlapped with HT responses by 85–97%. The sensitivity of these HRV metrics to distinguish between individual LT from HT subjects was 6–33%, and positive predictive values were 40–73%. These results indicate that while a small number of HRV metrics can accurately distinguish between LT and HT subjects using group mean data, individual HRV values are poor indicators of tolerance to hypovolemia.

Noninvasive hemodynamic monitoring in the emergency department

PURPOSE OF REVIEW

Emergency department patients are frequently undifferentiated, need accurate risk assessment and stratification, and are time-critical in their need for diagnosis and resuscitation. Valid, noninvasive hemodynamic monitoring modalities are essential to differentiate high from low risk patients, and to perform goal-directed management. This review analyses recent literature, which describes innovation in the range of noninvasive monitoring tools and places them in the emergency medicine context.

RELEVANT FINDINGS

A range of noninvasive measures of hemodynamic status are both commonly used, or are in the research and development phase. Pulse oximetry waveforms, electrocardiogram-based heart rate variability, Doppler and B-mode ultrasound, echocardiography, transthoracic bioimpedance, pressure pulse waveform analysis and near-infrared spectroscopy all have potential value in diagnosis and monitoring of hemodynamics, particularly used to explore autonomic nervous system control of cardiovascular function and by extension the early phases of compensation for illness and injury. Noninvasive techniques coupled with advances in data visualization and pattern recognition bring the potential for revolution to emergency department hemodynamic monitoring.

SUMMARY

Noninvasive measures of hemodynamic status and function are increasingly being used, although much still remains in the research domain. Noninvasive measures may not only offer similar variables to traditional vital signs, but add a new dimension of hemodynamic descriptors.