Heart rate variability and outcome in acute severe stroke: role of power spectral analysis

Heart rate variability in chronic ischemic stroke: analysis during the sleep-wake cycle

BACKGROUND

 Alterations of the autonomic nervous system (ANS) in the chronic stage of ischemic stroke (IS) are not well understood. Heart rate variability (HRV) provides a noninvasive approach to assess autonomic function.

OBJECTIVE

 To compare the HRV parameters during the sleep-wake cycle between patients with IS in the chronic stage and healthy subjects.

METHODS

 We conducted a retrospective transversal study based on clinical records and 24-hour electrocardiogram (EKG) monitoring registries of 179 patients with a confirmed IS diagnosis and 184 age- and sex-matched healthy subjects. Circadian variation was calculated according to the variation of the total autonomic activity (VTAI) and the parasympathetic activity (VPAI) indexes. Comparisons were performed using nonparametric tests. Multivariable analyses were performed with canonical discriminant analysis (CDA) and a three-way analysis of variance (ANOVA). Statistical significance was established with a confidence level of 95%.

RESULTS

 During waking hours, the healthy group exhibited higher variability in the time domain and frequency domain parameters: standard deviation of NN intervals (SDNN, p < 0.001) and of the average NN intervals (SDANN, p < 0.001), as well as low-frequency (LF) band (p < 0.001). During sleep, the difference was higher in the high-frequency (HF) band (p < 0.001), and lower in the low-/high-frequency ratio (LF/HF, p < 0.001). Both VPAI and VTAI showed less significant difference in IS patients (p < 0.001).

CONCLUSION

 There was diminished heart vagal activity among IS patients, as measured through HRV. During sleep, this is likely caused by an imbalance in the sympathetic and parasympathetic systems shifting through the sleep phases. These imbalances could persist over time in patients with IS, lasting months after the initial injury.

Effect of trehalose on heart functions in rats model after myocardial infarction: assessment of novel intraventricular pressure and heart rate variability

Background

Myocardial infarctions remain a leading cause of global deaths. Developing novel drugs to target cardiac remodeling after myocardial injury is challenging. There is an increasing interest in exploring natural cardioprotective agents and non-invasive tools like intraventricular pressure gradients (IVPG) and heart rate variability (HRV) analysis in myocardial infarctions. Trehalose (TRE), a natural disaccharide, shows promise in treating atherosclerosis, myocardial infarction, and neurodegenerative disorders.

Objectives

The objective of this study was to investigate the effectiveness of TRE in improving cardiac functions measured by IVPG and HRV and reducing myocardial remodeling following myocardial infarction in rat model.

Methods

Rats were divided into three groups: sham, myocardial infarction (MI), and trehalose-treated MI (TRE) groups. The animals in the MI and TRE groups underwent permanent ligation of the left anterior descending artery. The TRE group received 2% trehalose in their drinking water for four weeks after the surgery. At the end of the experiment, heart function was assessed using conventional echocardiography, novel color M-mode echocardiography for IVPG evaluation, and HRV analysis. After euthanasia, gross image scoring, histopathology, immunohistochemistry, and quantitative real-time PCR were performed to evaluate inflammatory reactions, oxidative stress, and apoptosis.

Results

The MI group exhibited significantly lower values in multiple IVPG parameters. In contrast, TRE administration showed an ameliorative effect on IVPG changes, with results comparable to the sham group. Additionally, TRE improved HRV parameters, mitigated morphological changes induced by myocardial infarction, reduced histological alterations in wall mass, and suppressed inflammatory reactions within the infarcted heart tissues. Furthermore, TRE demonstrated antioxidant, anti-apoptotic and anti-fibrotic properties.

Conclusion

The investigation into the effect of trehalose on a myocardial infarction rat model has yielded promising outcomes, as evidenced by improvements observed through conventional echocardiography, histological analysis, and immunohistochemical analysis. While minor trends were noticed in IVPG and HRV measurements. However, our findings offer valuable insights and demonstrate a correlation between IVPG, HRV, and other traditional markers of echo assessment in the myocardial infarction vs. sham groups. This alignment suggests the potential of IVPG and HRV as additional indicators for future research in this field.

Automated diagnosis of coronary artery disease using scalogram-based tensor decomposition with heart rate signals

Early identification of coronary artery disease (CAD) can facilitate timely clinical intervention and save lives. This study aims to develop a machine learning framework that uses tensor analysis on heart rate (HR) signals to automate the CAD detection task. A third-order tensor representing a time-frequency relationship is constructed by fusing scalograms as vertical slices of the tensor. Each scalogram is computed from the considered time frame of a given HR signal. The derived scalogram represents the heterogeneity of data as a two-dimensional map. These two-dimensional maps are stacked one after the other horizontally along the z-axis to form a 3-way tensor for each HR signal. Each two-dimensional map is represented as a vertical slice in the xy - plane. Tensor factorization of such a fused tensor for every HR signal is performed using canonical polyadic (CP) decomposition. Only the core factor is retained later, excluding the three unitary matrices to provide the latent feature set for the detection task. The resultant latent features are then fed to machine learning classifiers for binary classification. Bayesian optimization is performed in a five-fold cross-validation strategy in search of the optimal machine learning classifier. The experimental results yielded the accuracy, sensitivity, and specificity of 96.62%, 96.53%, and 96.67%, respectively, with the bagged trees ensemble method. The proposed tensor decomposition deciphered higher-order interrelations among the considered time-frequency representations of HR signals.

Does the Heart Fall Asleep?-Diurnal Variations in Heart Rate Variability in Patients with Disorders of Consciousness

The current study investigated heart rate (HR) and heart rate variability (HRV) across day and night in patients with disorders of consciousness (DOC). We recorded 24-h electrocardiography in 26 patients with DOC (i.e., unresponsive wakefulness syndrome (UWS; n = 16) and (exit) minimally conscious state ((E)MCS; n = 10)). To examine diurnal variations, HR and HRV indices in the time, frequency, and entropy domains were computed for periods of clear day- (forenoon: 8 a.m.-2 p.m.; afternoon: 2 p.m.-8 p.m.) and nighttime (11 p.m.-5 a.m.). The results indicate that patients' interbeat intervals (IBIs) were larger during the night than during the day, indicating HR slowing. The patients in UWS showed larger IBIs compared to the patients in (E)MCS, and the patients with non-traumatic brain injury showed lower HRV entropy than the patients with traumatic brain injury. Additionally, higher HRV entropy was associated with higher EEG entropy during the night. Thus, cardiac activity varies with a diurnal pattern in patients with DOC and can differentiate between patients' diagnoses and etiologies. Moreover, the interaction of heart and brain appears to follow a diurnal rhythm. Thus, HR and HRV seem to mirror the integrity of brain functioning and, consequently, might serve as supplementary measures for improving the validity of assessments in patients with DOC.

Test-retest reliability of heart-rate variability metrics in individuals with aphasia

Individuals with aphasia may have impairments in cognition, higher incidences of depression, and a variety of post-stroke functional impairments. However, evaluating these issues is challenging since most assessments require some degree of linguistic processing and task instructions are often verbal. Heart rate variability has shown to be an objective marker for cognitive functioning in neurologically healthy individuals, depression and post-stroke depression, and post-stroke functional impairments. However, before the utility of heart rate variability is established in persons with aphasia, its test-retest reliability needs to be established. The purpose of this study was to assess test-retest reliability of heart rate variability metrics in persons with aphasia. Heart rate variability was recorded at rest while in a sitting position in twenty-one persons with aphasia at two time points. Heart rate variability metrics were mostly moderately reliable. The majority of participants had resting heart rate variability parasympathetic and sympathetic indexes similar to those of neurologically healthy individuals. Further research is needed to establish the test-retest reliability of heart rate variability metrics in different postures and breathing conditions in persons with aphasia.

Heart rate variability predicts decline in sensorimotor rhythm control

Objective.Voluntary control of sensorimotor rhythms (SMRs, 8-12 Hz) can be used for brain-computer interface (BCI)-based operation of an assistive hand exoskeleton, e.g. in finger paralysis after stroke. To gain SMR control, stroke survivors are usually instructed to engage in motor imagery (MI) or to attempt moving the paralyzed fingers resulting in task- or event-related desynchronization (ERD) of SMR (SMR-ERD). However, as these tasks are cognitively demanding, especially for stroke survivors suffering from cognitive impairments, BCI control performance can deteriorate considerably over time. Therefore, it would be important to identify biomarkers that predict decline in BCI control performance within an ongoing session in order to optimize the man-machine interaction scheme.Approach.Here we determine the link between BCI control performance over time and heart rate variability (HRV). Specifically, we investigated whether HRV can be used as a biomarker to predict decline of SMR-ERD control across 17 healthy participants using Granger causality. SMR-ERD was visually displayed on a screen. Participants were instructed to engage in MI-based SMR-ERD control over two consecutive runs of 8.5 min each. During the 2nd run, task difficulty was gradually increased.Main results.While control performance (p= .18) and HRV (p= .16) remained unchanged across participants during the 1st run, during the 2nd run, both measures declined over time at high correlation (performance: -0.61%/10 s,p= 0; HRV: -0.007 ms/10 s,p< .001). We found that HRV exhibited predictive characteristics with regard to within-session BCI control performance on an individual participant level (p< .001).Significance.These results suggest that HRV can predict decline in BCI performance paving the way for adaptive BCI control paradigms, e.g. to individualize and optimize assistive BCI systems in stroke.

Initial in-hospital heart rate is associated with three-month functional outcomes after acute ischemic stroke

Background

Increased heart rate (HR) has been associated with stroke risk and outcomes.

Material and methods

We analyzed 1,420 patients from a hospital-based stroke registry with acute ischemic stroke (AIS). Mean initial in-hospital HR and the coefficient of variation of HR (HR-CV) were derived from the values recorded during the first 3 days of hospitalization. The study outcome was the 3-month functional outcome. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated using multivariable logistic regression analysis.

Results

A higher mean HR level was significantly and continuously associated with a higher probability of unfavorable functional outcomes. Compared with the reference group (mean HR < 70 beats per minute), the multivariate-adjusted OR for an unfavorable outcome was 1.81 (95% CI, 1.25–2.61) for a mean HR ≥ 70 and < 80 beats per minute, 2.52 (95% CI, 1.66 − 3.52) for a mean HR ≥ 80 and < 90 beats per minute, and 3.88 (95% CI, 2.20–6.85) for mean HR ≥ 90 beats per minute. For stroke patients with a history of hypertension, the multivariate-adjusted OR for patients with a HR-CV ≥ 0.12 (versus patients with a HR-CV < 0.08 as a reference) was 1.73 (95% CI, 1.11–2.70) for an unfavorable outcome.

Conclusions

Our results indicated that a high initial in-hospital HR was significantly associated with unfavorable 3-month functional outcomes in patients with AIS. In addition, stroke patients with a HR-CV ≥ 0.12 also had unfavorable outcomes compared with those with a HR-CV < 0.08 if they had a history of hypertension.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02252-2.

The Impact of Remote Ischaemic Conditioning on Beat-to-Beat Heart Rate Variability Circadian Rhythm in Healthy Adults

BACKGROUND

Remote ischaemic conditioning (RIC) is an intervention that may exert a protective effect over multiple tissues or organs by regulating neuronal signal transduction. Heart rate variability (HRV) can assess the state of the autonomic nervous system. However, whether RIC can also regulate HRV in humans remains unknown.

METHOD

This was a self-controlled interventional study in which serial beat-to-beat monitoring was performed at the same seven time points (7, 9, and 11 AM; 2, 5, and 8 PM; and 8 AM on the next day) with or without RIC in 50 healthy adults. The seven time points on the RIC day were defined as baseline, 1 hour, 3 hours, 6 hours, 9 hours, 12 hours, and 24 hours after RIC. The RIC protocol consisted of 4×5-minute inflation/deflation in one arm and one thigh cuff at 200 mmHg pressure from 7:20 to 8 AM. This study is registered on ClinicalTrials.gov (NCT02965547).

RESULTS

We included 50 healthy adult volunteers (aged 34.54±12.01 years, 22 men [44%], all Asian). The variables analysed in frequency-domain measures performed as power of low-frequency in normalised units (0.04-0.15 Hz), high-frequency in normalised units (0.15-0.40 Hz), and ratio of low frequency to high frequency. The time-domain parameters standard deviation (SD) of all normal to normal (NN) intervals (SDNN), mean of the 5-minute SD of the NN intervals, SD of the consecutive 5-minute averages of NN intervals, and the root mean square of successive differences of NN intervals, and time-domain parameters calculated from Poincaré plots, SD of the short diagonal axis in Poincaré plot (SD1), SD of the long diagonal axis in Poincaré plot (SD2), and SD1/SD2 were also obtained. The SDNN and SD2 significantly increased 1 hour after RIC (p=0.029 and p=0.045, respectively). Additionally, the SD2 increased a second time 12 hours after RIC (p=0.041), which represented inhibited sympathetic activity.

CONCLUSIONS

Heart rate variability increase and sympathetic inhibition induced by RIC appeared both on the early and delayed protective window of RIC, which may indicate some of the underlying mechanisms by which RIC may offer protection.

Effects of short-term exposure to particulate matters on heart rate variability: A systematic review and meta-analysis based on controlled animal studies

BACKGROUND

Exposure to particulate matters (PM) is recognized as an important risk factor for cardiovascular disease. A change in cardiac autonomic function is one postulated mechanism leading to PM related cardiovascular events. This study therefore evaluated the associations of short-term exposure to PM and heart rate variability (HRV) parameters, which can reflect the cardiac autonomic function.

METHODS

Four electronic databases were searched for controlled studies of rodents published prior to December 2018. A systematic review and meta-analysis was conducted. Effect sizes were calculated for five main HRV parameters, including standard deviation of normal-to-normal intervals (SDNN), square root of mean squared differences between successive normal-to-normal intervals (rMSSD), low frequency (LF), high frequency (HF), and the ratio of LF and HF (LF/HF).

RESULTS

The review included 23 studies with 401 animals. Short-term exposure to PM by instillation yielded statistically significant effects on SDNN (Standardized Mean Difference [SMD] = -1.11, 95% Confidence Intervals [CI] = -2.22 to -0.01, P = 0.05), LF (SMD = -1.19, 95% CI = -1.99 to -0.40, P = 0.003) and LF/HF (SMD = -1.05, 95% CI = -2.03 to -0.07, P = 0.04). Short-term exposure to PM by inhalation only yielded statistically significant effect on LF/HF (SMD = -0.83, 95% CI = -1.39 to -0.27, P = 0.004). There was no evidence that animal model and exposure frequency influenced the relationship of PM and HRV.

CONCLUSIONS

Short-term exposure to PM can decrease HRV of rodents, affecting cardiac autonomic function. Exposure methods can influence the relationships of PM and HRV parameters. Further studies should focus on the effects of long-term PM exposure, on human beings, and potential influential factors of PM-HRV associations.

Comparison of methods for the assessment of nonlinearity in short-term heart rate variability under different physiopathological states

Despite the widespread diffusion of nonlinear methods for heart rate variability (HRV) analysis, the presence and the extent to which nonlinear dynamics contribute to short-term HRV are still controversial. This work aims at testing the hypothesis that different types of nonlinearity can be observed in HRV depending on the method adopted and on the physiopathological state. Two entropy-based measures of time series complexity (normalized complexity index, NCI) and regularity (information storage, IS), and a measure quantifying deviations from linear correlations in a time series (Gaussian linear contrast, GLC), are applied to short HRV recordings obtained in young (Y) and old (O) healthy subjects and in myocardial infarction (MI) patients monitored in the resting supine position and in the upright position reached through head-up tilt. The method of surrogate data is employed to detect the presence and quantify the contribution of nonlinear dynamics to HRV. We find that the three measures differ both in their variations across groups and conditions and in the percentage and strength of nonlinear HRV dynamics. NCI and IS displayed opposite variations, suggesting more complex dynamics in O and MI compared to Y and less complex dynamics during tilt. The strength of nonlinear dynamics is reduced by tilt using all measures in Y, while only GLC detects a significant strengthening of such dynamics in MI. A large percentage of detected nonlinear dynamics is revealed only by the IS measure in the Y group at rest, with a decrease in O and MI and during T, while NCI and GLC detect lower percentages in all groups and conditions. While these results suggest that distinct dynamic structures may lie beneath short-term HRV in different physiological states and pathological conditions, the strong dependence on the measure adopted and on their implementation suggests that physiological interpretations should be provided with caution.

Ischemic Stroke Detection by Analyzing Heart Rate Variability in Rat Middle Cerebral Artery Occlusion Model

Although early reperfusion therapy is effective for acute ischemic stroke, limited therapeutic time-window resulted in only 10% of patients receiving reperfusion therapy. A fast and reliable stroke detection method is desired so that patients can receive early reperfusion therapy. It has been reported that ischemic stroke affects heart rate variability (HRV), which reflects activities of the autonomic nervous function. Thus, ischemic stroke may be detected at an acute stage through monitoring HRV. This paper proposes an HRV-based ischemic stroke detection algorithm by using multivariate statistical process control (MSPC), which is a well-known anomaly detection algorithm. As a feasibility study before collecting a large amount of clinical data from human patients, this paper used the middle cerebral artery occlusion (MCAO) model in rats for collecting HRV data shortly after ischemic stroke onsets. The 11 MCAO-operated rats and 11 sham-operated rats were prepared, and HRV data of three sham-operated rats were used for model construction. The data on the other 19 rats were used for its validation. The experimental result showed that sensitivity and specificity of the proposed algorithm were 82% and 75%, respectively. Thus, the present work shows the possibility of realizing an HRV-based ischemic stroke detection system for human patients.

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.

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.

Heart Rate Variability as a Biomarker for Predicting Stroke, Post-stroke Complications and Functionality

Background:

Heart rate variability (HRV) is a non-invasive measure of the function of the autonomic nervous system, and its dynamic nature may provide a means through which stroke and its associated complications may be predicted, monitored, and managed.

Objective:

The objective of this review is to identify and provide a critique on the most recent uses of HRV in stroke diagnosis/management and highlight areas that warrant further research.

Methods:

The MEDLINE, CINAHL, and OVID MEDLINE databases were canvassed using a systematic search strategy, for articles investigating the use of HRV in stroke diagnosis and management. Initial paper selections were based on title alone, and final paper inclusion was informed by a full-text critical appraisal.

Results:

The systematic search returned 98 records, of which 51 were unique. Following screening, 22 records were included in the final systematic review. The included papers provided some information regarding predicting incident stroke, which largely seems to be best predicted by time- and frequency-domain HRV parameters. Furthermore, post-stroke complications and functionality are similarly predicted by time- and frequency-domain parameters, as well as non-linear parameters in some instances.

Conclusions:

Current research provides good evidence that HRV parameters may have utility as a biomarker for stroke and for post-stroke complications and/or functionality. Future research would benefit from the integration of non-linear, and novel parameters, the hybridisation of HRV parameters, and the expansion of the utilisation of predictive regression and hazard modelling.

Increases in Heart Rate Variability Signal Improved Outcomes in Rapid Response Team Consultations: A Cohort Study

Background

Reduced heart rate variability (HRV) indicates dominance of the sympathetic system and a state of “physiologic stress.” We postulated that, in patients with critical illness, increases in HRV might signal successful resuscitation and improved prognosis.

Methods

We carried out a prospective observational study of HRV on all patients referred to the rapid response team (RRT) and correlated with serial vital signs, lactate clearance, ICU admission, and mortality.

Results

Ninety-one patients were studied. Significantly higher HRV was observed in patients who achieved physiological stability and did not need ICU admission: ASDNN 19 versus 34.5, p=0.032; rMSSD 13.5 versus 25, p=0.046; mean VLF 9.4 versus 17, p=0.021; mean LF 5.8 versus 12.4, p=0.018; and mean HF 4.7 versus 10.5, p=0.017. ROC curves confirmed the change in very low frequencies at 2 hours as a strong predictor for ICU admission with an AUC of 0.772 (95% CI 0.633, 0.911, p=0.001) and a cutoff value of −0.65 associated with a sensitivity of 78.6% and a specificity of 61%.

Conclusions

Reduced HRV, specifically VLF, appears closely related to greater severity of critical illness, identifies unsuccessful resuscitation, and can be used to identify consultations that need early ICU admission.

Addition of 24-Hour Heart Rate Variability Parameters to the Cardiovascular Health Study Stroke Risk Score and Prediction of Incident Stroke: The Cardiovascular Health Study

Background

Heart rate variability (HRV) characterizes cardiac autonomic functioning. The association of HRV with stroke is uncertain. We examined whether 24‐hour HRV added predictive value to the Cardiovascular Health Study clinical stroke risk score (CHS‐SCORE), previously developed at the baseline examination.

Methods and Results

N=884 stroke‐free CHS participants (age 75.3±4.6), with 24‐hour Holters adequate for HRV analysis at the 1994–1995 examination, had 68 strokes over ≤8 year follow‐up (median 7.3 [interquartile range 7.1–7.6] years). The value of adding HRV to the CHS‐SCORE was assessed with stepwise Cox regression analysis. The CHS‐SCORE predicted incident stroke (HR=1.06 per unit increment, P=0.005). Two HRV parameters, decreased coefficient of variance of NN intervals (CV%, P=0.031) and decreased power law slope (SLOPE, P=0.033) also entered the model, but these did not significantly improve the c‐statistic (P=0.47). In a secondary analysis, dichotomization of CV% (LOWCV% ≤12.8%) was found to maximally stratify higher‐risk participants after adjustment for CHS‐SCORE. Similarly, dichotomizing SLOPE (LOWSLOPE <−1.4) maximally stratified higher‐risk participants. When these HRV categories were combined (eg, HIGHCV% with HIGHSLOPE), the c‐statistic for the model with the CHS‐SCORE and combined HRV categories was 0.68, significantly higher than 0.61 for the CHS‐SCORE alone (P=0.02).

Conclusions

In this sample of older adults, 2 HRV parameters, CV% and power law slope, emerged as significantly associated with incident stroke when added to a validated clinical risk score. After each parameter was dichotomized based on its optimal cut point in this sample, their composite significantly improved prediction of incident stroke during ≤8‐year follow‐up. These findings will require validation in separate, larger cohorts.

Heart Rate Variability in Patients with Acute Ischemic Stroke at Different Stages of Renal Dysfunction: A Cross-sectional Observational Study

Background:

Renal function is associated with mortality and functional disabilities in stroke patients, and impaired autonomic function is common in stroke, but little is known regarding its effects on stroke patients with renal dysfunction. This study sought to evaluate the association between autonomic function and stroke in patients with renal dysfunction.

Methods:

This study comprised 232 patients with acute ischemic stroke consecutively enrolled from February 2013 to November 2014 at Guangdong Provincial Hospital of Chinese Medicine in China. All patients recruited underwent laboratory evaluation and 24 h Holter electrocardiography (ECG). Autonomic function was measured based on the heart rate variability (HRV) using 24 h Holter ECG. Renal damage was assessed through the estimated glomerular filtration rate (eGFR), and stroke severity was rated according to the National Institutes of Health Stroke Scale (NIHSS). The Barthel index and modified Rankin score were also determined following admission. All the clinical covariates that could potentially affect autonomic outcome variables were adjusted with linear regression.

Results:

In the patients with a mild or moderate decreased eGFR, the values for the standard deviation of the averaged normal-to-normal RR interval (SDANN) index (P = 0.022), very low frequency (VLF) (P = 0.043), low frequency (LF) (P = 0.023), and ratio of low-to-high frequency power (LF/HF) (P = 0.001) were significantly lower than those in the patients with a normal eGFR. A multinomial linear regression indicated that eGFR (t = 2.47, P = 0.014), gender (t = −3.60, P < 0.001), and a history of hypertension (t = −2.65, P = 0.008) were the risk factors of LF/HF; the NIHSS score (SDANN index: t = −3.83, P < 0.001; VLF: t = −3.07, P = 0.002; LF: t = −2.79, P = 0.006) and a history of diabetes (SDANN index: t = −3.58, P < 0.001; VLF: t = −2.54, P = 0.012; LF: t = −2.87, P = 0.004) were independent factors for the SDANN index, VLF, and LF; the Oxfordshire Community Stroke Project (t = −2.38, P = 0.018) was related to the SDANN index.

Conclusions:

Autonomic dysfunction is aggravated with the progression of eGFR stage in patients with acute ischemic stroke; the eGFR is an independent factor of LF/HF in the adjusted models. Stroke severity and a history of diabetes are more significantly associated with HRV in patients with acute ischemic stroke at different stages of renal dysfunction.

External Counterpulsation Increases Beat-to-Beat Heart Rate Variability in Patients with Ischemic Stroke

BACKGROUND AND PURPOSE

External counterpulsation (ECP) is a noninvasive method used to augment cerebral perfusion in ischemic stroke. However, the response of beat-to-beat heart rate variability (HRV) in patients with ischemic stroke during ECP remains unknown.

METHODS

Forty-eight patients with unilateral ischemic stroke at the subacute stage and 14 healthy controls were recruited. Beat-to-beat heart rate before, during, and after ECP was monitored. The frequency components of HRV were calculated using power spectral analysis. Very low frequency (VLF; <.04 Hz), low frequency (LF; .04-.15 Hz), high frequency (HF; .15-.40 Hz), total power spectral density (TP; <.40 Hz), and LF/HF ratio were calculated.

RESULTS

In stroke patients, although there were no statistical differences in all of the HRV components, the HRV at VLF showed a trend of increase during ECP compared with baseline in the left-sided stroke patients (P = .083). After ECP, the HRV at LF and TP remained higher than baseline in the right-sided stroke patients (LF, 209.4 versus 117.9, P = .050; TP, 1275.6 versus 390.2, P = .017, respectively). Besides, the HRV at TP also increased after ECP compared with baseline in the left-sided stroke patients (563.0 versus 298.3, P = .029).

CONCLUSIONS

Irrespective of the side of the ischemia, patients showed an increased beat-to-beat HRV after ECP. Additionally, sympathetic and parasympathetic cardiac modulations were increased after ECP in patients after right-sided subacute stroke.

Automated diagnosis of coronary artery disease (CAD) patients using optimized SVM

BACKGROUND AND OBJECTIVE

Currently Coronary Artery Disease (CAD) is one of the most prevalent diseases, and also can lead to death, disability and economic loss in patients who suffer from cardiovascular disease. Diagnostic procedures of this disease by medical teams are typically invasive, although they do not satisfy the required accuracy.

METHODS

In this study, we have proposed a methodology for the automatic diagnosis of normal and Coronary Artery Disease conditions using Heart Rate Variability (HRV) signal extracted from electrocardiogram (ECG). The features are extracted from HRV signal in time, frequency and nonlinear domains. The Principal Component Analysis (PCA) is applied to reduce the dimension of the extracted features in order to reduce computational complexity and to reveal the hidden information underlaid in the data. Finally, Support Vector Machine (SVM) classifier has been utilized to classify two classes of data using the extracted distinguishing features. In this paper, parameters of the SVM have been optimized in order to improve the accuracy.

RESULTS

Provided reports in this paper indicate that the detection of CAD class from normal class using the proposed algorithm was performed with accuracy of 99.2%, sensitivity of 98.43%, and specificity of 100%.

CONCLUSIONS

This study has shown that methods which are based on the feature extraction of the biomedical signals are an appropriate approach to predict the health situation of the patients.

Prediction of in-hospital stroke mortality in critical care unit

BACKGROUND

Critical stroke causes high morbidity and mortality. We examined if variables in the early stage of critical stroke could predict in-hospital mortality.

METHODS

We recruited 611 ischemic and 805 hemorrhagic stroke patients who were admitted within 24 h after the symptom onset. Data were analyzed with independent t test and Chi square test, and then with multivariate logistic regression analysis.

RESULTS

In ischemic stroke, National Institutes of Health Stroke Scale (NIHSS) score (OR 1.08; 95 % CI 1.06-1.11; P < 0.01), white blood cell count (OR 1.11; 95 % CI 1.05-1.18; P < 0.01), systolic blood pressure (BP) (OR 0.49; 95 % CI 0.26-0.90; P = 0.02) and age (OR 1.03; 95 % CI 1.00-1.05; P = 0.03) were associated with in-hospital mortality. In hemorrhagic stroke, NIHSS score (OR 1.12; 95 % CI 1.09-1.14; P < 0.01), systolic BP (OR 0.25; 95 % CI 0.15-0.41; P < 0.01), heart disease (OR 1.94; 95 % CI 1.11-3.39; P = 0.02) and creatinine (OR 1.16; 95 % CI 1.01-1.34; P = 0.04) were related to in-hospital mortality. Nomograms using these significant predictors were constructed for easy and quick evaluation of in-hospital mortality.

CONCLUSION

Variables in acute stroke can predict in-hospital mortality and help decision-making in clinical practice using nomogram.

Feasibility, Reliability and Predictive Value Of In-Ambulance Heart Rate Variability Registration

Background

Heart rate variability (HRV) is a parameter of autonomic nervous system function. A decrease of HRV has been associated with disease severity, risk of complications and prognosis in several conditions.

Objective

We aim to investigate the feasibility and the reliability of in-ambulance HRV registration during emergency interventions, and to evaluate the association between prehospital HRV parameters, patient characteristics, vital parameters and short-term outcome.

Methods

We conducted a prospective study using a non-invasive 2-lead ECG registration device in 55 patients transported by the paramedic intervention team of the Universitair Ziekenhuis Brussel. HRV assessment included time domain parameters, frequency domain parameters, nonlinear analysis, and time-frequency analysis. The correlation between HRV parameters and patient and outcome characteristics was analyzed and compared to controls.

Results

Artifact and ectopic detection rates were higher in patients during ambulance transportation compared to controls in resting conditions, yet technical reasons precluding in-ambulance HRV analysis occurred in only 9.6% of cases. HRV acquisition was possible without safety issues or interference with routine emergency care. Reliability of the results was considered sufficient for Sample entropy (SampEn), good for the ratio of low frequency and high frequency components (LF/HF ratio) in the frequency and the time frequency domain, and excellent for the triangular interpolation of the NN interval histogram (TINN), and for the short-term scaling exponent of the detrended fluctuation analysis (DFA α1). HRV indices were significantly reduced inpatients with unfavorable outcome compared to patients with favorable outcome and controls. Multivariate analysis identified lower DFA α1 as an independent predictor of unfavorable outcome (OR, 0.155; 95% CI 0.024–0.966; p = 0.049).

Conclusion

In-ambulance HRV registration is technically and operationally feasible and produces reliable results for parameters in the time, frequency, nonlinear and time frequency domain. Especially non-linear HRV analysis during emergency ambulance transportation may be a promising approach to predict patient outcome.

Heart rate variability and baroreceptor sensitivity in acute stroke: a systematic review

BACKGROUND

Autonomic nervous system dysfunction is common after acute stroke and is associated with elevated risk of cardiac arrhythmia and mortality. Heart rate variability and baroreceptor sensitivity have been investigated as parameters of autonomic nervous system dysfunction for the prediction of stroke outcome.

SUMMARY

We performed a systematic literature review on heart rate variability and baroreceptor sensitivity as parameters for autonomic nervous function in acute stroke. Twenty-two studies were included. Associations between heart rate variability or baroreceptor sensitivity and stroke severity, early and late complications, dependency and mortality were reported. However, interpretability of most studies and extrapolation to general stroke population are limited due to many confounding factors such as varying methodology, small sample sizes, survival selection, and exclusion of patients with frequently occurring comorbidities in stroke. Key issues, such as the effect of thrombolytic therapy on autonomic function, autonomic nervous system dysfunction in the hyperacute phase of stroke, and correlation with the risk of recurrent stroke have not been investigated. Also, nonlinear techniques have remained largely unexplored in this domain, in spite of their advantage to provide more solid evaluation in the occurrence of arrhythmia.

KEY MESSAGES

Cardiac autonomic dysfunction, represented by reduced heart rate variability or impaired baroreceptor sensitivity, is associated with stroke severity, early and late complications, dependency, and mortality. Large-scale prospective studies applying internationally accepted standards of measures for analysis of heart rate variability and baroreceptor sensitivity are needed in patients with acute stroke.

Mercury Exposure and Heart Rate Variability: a Systematic Review

BACKGROUND

Mercury affects the nervous system and has been implicated in altering heart rhythm and function. We sought to better define its role in modulating heart rate variability, a well-known marker of cardiac autonomic function.

DESIGN

This is a systematic review study.

METHODS

We searched PubMed, Embase, TOXLINE, and DART databases without language restriction. We report findings as a qualitative systematic review because heterogeneity in study design and assessment of exposures and outcomes across studies, as well as other methodological limitations of the literature, precluded a quantitative meta-analysis.

RESULTS

We identified 12 studies of mercury exposure and heart rate variability in human populations (ten studies involving primarily environmental methylmercury exposure and two studies involving occupational exposure to inorganic mercury) conducted in Japan, the Faroe Islands, Canada, Korea, French Polynesia, Finland, and Egypt. The association of prenatal mercury exposure with lower high-frequency band scores (thought to reflect parasympathetic activity) in several studies, in particular the inverse association of cord blood mercury levels with the coefficient of variation of the R-R intervals and with low-frequency and high-frequency bands at 14 years of age in the Faroe Islands birth cohort study, suggests that early mercury exposure could have a long-lasting effect on cardiac parasympathetic activity. Studies with later environmental exposures to mercury in children or in adults were heterogeneous and did not show consistent associations.

CONCLUSIONS

The evidence was too limited to draw firm causal inferences. Additional research is needed to elucidate the effects of mercury on cardiac autonomic function, particularly as early-life exposures might have lasting impacts on cardiac parasympathetic function.

Complexity of heart rate variability predicts outcome in intensive care unit admitted patients with acute stroke

BACKGROUND

Heart rate variability (HRV) has been proposed as a predictor of acute stroke outcome. This study aimed to evaluate the predictive value of a novel non-linear method for analysis of HRV, multiscale entropy (MSE) and outcome of patients with acute stroke who had been admitted to the intensive care unit (ICU).

METHODS

The MSE of HRV was analysed from 1 h continuous ECG signals in ICU-admitted patients with acute stroke and controls. The complexity index was defined as the area under the MSE curve (scale 1-20). A favourable outcome was defined as modified Rankin scale 0-2 at 3 months after stroke.

RESULTS

The trends of MSE curves in patients with atrial fibrillation (AF) (n=77) were apparently different from those in patients with non-AF stroke (n=150) and controls (n=60). In addition, the values of complexity index were significantly lower in the patients with non-AF stroke than in the controls (25.8±.3 vs. 32.3±4.3, p<0.001). After adjustment for clinical variables, patients without AF who had a favourable outcome were significantly related to higher complexity index values (OR=1.15, 95% CI 1.07 to 1.25, p<0.001). Importantly, the area under the receiver operating characteristic curve for predicting a favourable outcome of patients with non-AF stroke from clinical parameters was 0.858 (95% CI 0.797 to 0.919) and significantly improved to 0.903 (95% CI 0.853 to 0.954) after adding on the parameter of complexity index values (p=0.020).

CONCLUSIONS

In ICU-admitted patients with acute stroke, early assessment of the complexity of HRV by MSE can help in predicting outcomes in patients without AF.

Modulation of Cardiac Autonomic Dysfunction in Ischemic Stroke following Ayurveda (Indian System of Medicine) Treatment

Objectives. Cardiac autonomic dysfunction in stroke has implications on morbidity and mortality. Ayurveda (Indian system of medicine) describes stroke as pakshaghata. We intended to study the effect of Ayurveda therapies on the cardiac autonomic dysfunction. Methods. Fifty patients of ischemic stroke (middle cerebral artery territory) (mean age 39.26 ± 9.88 years; male 43, female 7) were recruited within one month of ictus. All patients received standard allopathic medications as advised by neurologist. In addition, patients were randomized to receive physiotherapy (Group I) or Ayurveda treatment (Group II) for 14 days. Continuous electrocardiogram and finger arterial pressure were recorded for 15 min before and after treatments and analyzed offline to obtain heart rate and blood pressure variability and baroreflex sensitivity (BRS). Results were analysed by RMANOVA. Results. Patients in Group II showed statistically significant improvement in cardiac autonomic parameters. The standard deviation of normal to normal intervals,and total and low frequency powers were significantly enhanced (F = 8.16, P = 0.007, F = 9.73, P = 0.004, F = 13.51, and P = 0.001, resp.). The BRS too increased following the treatment period (F = 10.129, P = 0.004). Conclusions. The current study is the first to report a positive modulation of cardiac autonomic activity after adjuvant Ayurveda treatment in ischemic stroke. Further long term studies are warranted.

Abnormal heart rate characteristics are associated with abnormal neuroimaging and outcomes in extremely low birth weight infants

OBJECTIVE

Brain injury in preterm infants may lead to an inflammatory response and central nervous system dysfunction reflected by abnormal heart rate characteristics (HRC). We hypothesized that a continuously monitored HRC index reflecting reduced HR variability and decelerations correlates with abnormal neuroimaging and outcomes in extremely low birth weight infants (ELBW).

STUDY DESIGN

We analyzed the average HRC index within 28 days after birth (aHRC28) and head ultrasound (HUS) in 384 ELBW infants. In 50 infants with brain magnetic resonance imaging (MRI) and 70 infants with Bayley neurodevelopmental testing at 1 year of age, we analyzed the relationship between aHRC28, MRI abnormalities and low Bayley scores.

RESULT

aHRC28 was higher in infants with severe HUS abnormalities (2.65±1.27 for Grade III-IV intraventricular hemorrhage (IVH) or cystic periventricular leukomalacia (cPVL) versus 1.72±0.95 for normal or Grade I-II IVH, P<0.001). Higher aHRC28 was also associated with white matter damage on MRI and death or Bayley motor or mental developmental index <70. Associations persisted after adjusting for gestational age, birth weight and septicemia. For every one point increase in aHRC28, the odds ratio of death or Bayley score <70 was 2.45 (95% CI 1.46, 4.05, P<0.001).

CONCLUSION

A continuously monitored HRC index provides an objective, noninvasive measure associated with abnormal brain imaging and adverse neurologic outcomes in ELBW infants.

Linear and nonlinear analysis of normal and CAD-affected heart rate signals

Coronary artery disease (CAD) is one of the dangerous cardiac disease, often may lead to sudden cardiac death. It is difficult to diagnose CAD by manual inspection of electrocardiogram (ECG) signals. To automate this detection task, in this study, we extracted the heart rate (HR) from the ECG signals and used them as base signal for further analysis. We then analyzed the HR signals of both normal and CAD subjects using (i) time domain, (ii) frequency domain and (iii) nonlinear techniques. The following are the nonlinear methods that were used in this work: Poincare plots, Recurrence Quantification Analysis (RQA) parameters, Shannon entropy, Approximate Entropy (ApEn), Sample Entropy (SampEn), Higher Order Spectra (HOS) methods, Detrended Fluctuation Analysis (DFA), Empirical Mode Decomposition (EMD), Cumulants, and Correlation Dimension. As a result of the analysis, we present unique recurrence, Poincare and HOS plots for normal and CAD subjects. We have also observed significant variations in the range of these features with respect to normal and CAD classes, and have presented the same in this paper. We found that the RQA parameters were higher for CAD subjects indicating more rhythm. Since the activity of CAD subjects is less, similar signal patterns repeat more frequently compared to the normal subjects. The entropy based parameters, ApEn and SampEn, are lower for CAD subjects indicating lower entropy (less activity due to impairment) for CAD. Almost all HOS parameters showed higher values for the CAD group, indicating the presence of higher frequency content in the CAD signals. Thus, our study provides a deep insight into how such nonlinear features could be exploited to effectively and reliably detect the presence of CAD.

Acute ischaemic stroke prediction from physiological time series patterns

BACKGROUND

Stroke is one of the major diseases with human mortality. Recent clinical research has indicated that early changes in common physiological variables represent a potential therapeutic target, thus the manipulation of these variables may eventually yield an effective way to optimise stroke recovery.

AIMS

We examined correlations between physiological parameters of patients during the first 48 hours after a stroke, and their stroke outcomes after three months. We wanted to discover physiological determinants that could be used to improve health outcomes by supporting the medical decisions that need to be made early on a patient's stroke experience.

METHOD

We applied regression-based machine learning techniques to build a prediction algorithm that can forecast threemonth outcomes from initial physiological time series data during the first 48 hours after stroke. In our method, not only did we use statistical characteristics as traditional prediction features, but we also adopted trend patterns of time series data as new key features.

RESULTS

We tested our prediction method on a real physiological data set of stroke patients. The experiment results revealed an average high precision rate: 90%. We also tested prediction methods only considering statistical characteristics of physiological data, and concluded an average precision rate: 71%.

CONCLUSION

We demonstrated that using trend pattern features in prediction methods improved the accuracy of stroke outcome prediction. Therefore, trend patterns of physiological time series data have an important role in the early treatment of patients with acute ischaemic stroke.

Heart rate variability

Heart rate variability (HRV) provides indirect insight into autonomic nervous system tone, and has a well-established role as a marker of cardiovascular risk. Recent decades brought an increasing interest in HRV assessment as a diagnostic tool in detection of autonomic impairment, and prediction of prognosis in several neurological disorders. Both bedside analysis of simple markers of HRV, as well as more sophisticated HRV analyses including time, frequency domain and nonlinear analysis have been proven to detect early autonomic involvement in several neurological disorders. Furthermore, altered HRV parameters were shown to be related with cardiovascular risk, including sudden cardiac risk, in patients with neurological diseases. This chapter aims to review clinical and prognostic application of HRV analysis in diabetes, stroke, multiple sclerosis, muscular dystrophies, Parkinson's disease and epilepsy.

I. THAJUDINAHAMED. NOVEL CLASSIFICATION OF CORONARY ARTERY DISEASE USING HEART RATE VARIABILITY ANALYSIS

Coronary artery disease (CAD) is a leading cause of death worldwide. Heart rate variability (HRV) has been proven to be a non-invasive marker of the autonomic modulation of the heart. Nonlinear analyses of HRV signals have shown that the HRV is reduced significantly in patients with CAD. Therefore, in this work, we extracted nonlinear features from the HRV signals using the following techniques: recurrence plots (RP), Poincare plots, and detrended fluctuation analysis (DFA). We also extracted three types of entropy, namely, Shannon entropy (ShanEn), approximation entropy (ApEn), and sample entropy (SampEn). These features were subjected to principal component analysis (PCA). The significant principal components were evaluated using eight classification techniques, and the performances of these techniques were evaluated to determine which presented the highest accuracy in classifying normal and CAD classes. We observed that the multilayer perceptron (MLP) method resulted in the highest classification accuracy (89.5%) using our proposed technique.

Watching neutral and threatening movies: subjective experience and autonomic responses in subjects with different hypnotizability levels

Subjects with high hypnotizability scores (Highs) have been considered more prone to experience negative affect and more vulnerable to its autonomic effects with respect to low hypnotizable individuals (Lows). The aim of the study was to analyze the subjective experience, tonic skin conductance (SC), respiratory frequency (RF), heart rate (HR) and heart rate variability (HRV) of healthy Highs and Lows during a long-lasting, emotionally neutral task (Session R, 46 subjects) and a moderately threatening one (Session T, 35 subjects). At the end of the relaxing Session R, all participants reported an increased relaxation. At the end of the threatening Session T, only 20 subjects reported a decreased relaxation (effective T: eT subsample). Highs and Lows of this subsample reported a similarly reduced relaxation and showed a similarly increased skin conductance. HR and HRV did not differ between the two sessions and between Highs and Lows. Among the subjects not reporting decreased relaxation at the end of Session T (ineffective T: iT subsample, n=15), relaxation was deeper and associated with lower skin conductance in Highs, although HR and HRV did not differ between Highs and Lows. All together, the results do not support the hypothesis of higher proneness of Highs to experience negative affect and to exhibit the autonomic correlates of negative emotion.

Depressed sympathovagal balance predicts mortality in patients with subarachnoid hemorrhage

OBJECTIVES

The objective of this study is to investigate the role of sympathovagal balance in predicting inhospital mortality by assessing power spectral analysis of heart rate variability (HRV) among patients with nontraumatic subarachnoid hemorrhage (SAH) in an emergency department (ED).

METHODS

A cohort of 132 adult patients with spontaneous SAH in an ED was prospectively enrolled. A continuous 10-minute electrocardiography for off-line power spectral analysis of the HRV was recorded. Using the inhospital mortality, the patients were classified into 2 groups: nonsurvivors (n=38) and survivors (n=94). The HRV measures were compared between these 2 groups of patients.

RESULTS

Having compared the various measurements, the very low-frequency component, low-frequency component, normalized low-frequency component (LF%), and low-/high-frequency component ratio (LF/HF) were significantly lower, whereas the normalized high-frequency component was significantly higher among the nonsurvivors than among the survivors. A multiple logistic regression model identified LF/HF (odds ratio, 2.16; 95% confidence interval [CI], 1.18-3.97; P=.013) and LF% (odds ratio, 0.78; 95% CI, 0.69-0.88; P<.001) as independent variables that were able to predict inhospital mortality for patients with SAH in an ED. The receiver operating characteristic area for LF/HF in predicting inhospital mortality was 0.957 (95% CI, 0.914-1.000; P<.001), and the best cutoff points was 0.8 (sensitivity, 92.1%; specificity, 90.4%).

CONCLUSIONS

Power spectral analysis of the HRV is able to predict inhospital mortality for patients after SAH in an ED. A tilt in the sympathovagal balance toward depressed sympathovagal balance, as indicated by HRV analysis, might contribute to the poor outcome among these patients.

Heart rate variability predicts ESRD and CKD-related hospitalization

Autonomic imbalance, a feature of both diabetes and hypertension, may contribute to adverse cardiovascular outcomes. In animal models, sympathetic nerve activity contributes to renal damage but the extent to which autonomic dysfunction precedes the development of CKD and ESRD in humans is unknown. We measured resting heart rate and heart rate variability in 13,241 adults (45- to 64-years old) followed for a median of 16 years in the Atherosclerosis Risk in Communities (ARIC) Study. We examined heart rate parameters by quartiles, defining those in the lowest quartile (by time and frequency domain measures separately) as the risk group of interest. We identified 199 cases of incident ESRD and 541 patients with CKD-related hospitalizations; higher resting heart rate and lower heart rate variability associated with both outcomes. The fully adjusted hazard ratios for ESRD were 1.98 (95% confidence interval [CI] 1.45 to 2.70) among those in the highest heart rate quartile and 1.56 (95% CI 1.14 to 2.14) for high-frequency power. Other time and frequency domain measures were similarly and significantly associated with ESRD and CKD-related hospitalizations. These results suggest that autonomic dysfunction may be an important risk factor for ESRD and CKD-related hospitalizations and call for further studies to define the mechanisms that underlie these associations.

Prognostic value of QT parameters in patients with acute hemorrhagic stroke: a prospective evaluation with respect to mortality and post-hospitalization bed confinement

BACKGROUND

This prospective study was performed to evaluate the prognostic prediction value of QT parameters and clinical characteristics exhibited by patients with acute hemorrhagic stroke at the time of presenting to the emergency department (ED).

METHODS

One hundred and sixty-six patients admitted to the ED of Taipei Veterans General Hospital from January 2006 to October 2006 because of acute hemorrhagic stroke were enrolled. Glasgow Coma Scale (GCS) scores between 3 and 8 were taken to indicate severe neurologic deficits. QT parameters (QT max, QT min, QT dispersion, QTc max, QTc min, QTc dispersion) and other pertinent clinical variables were determined on admission. Logistic regression model was applied to evaluate prognostic prediction values.

RESULTS

Mortality was higher among stroke patients with low GCS scores (p < 0.01). Leukocyte counts and systolic blood pressures were significantly higher among non-surviving patients (p = 0.04). No association was found between QT parameters and mortality (all p > 0.05). Among survivors, post-hospitalization bed confinement was required for those significantly older (p = 0.01) and those with higher QT max and QTc max values in multivariate analyses (p = 0.04 and p < 0.01, respectively).

CONCLUSION

Low GCS scores, increased leukocyte counts, and elevated systolic blood pressures predict increased mortality for subjects with acute hemorrhagic stroke. Advanced age and prolongations in QTc and QT max at the time of stroke predicted poor functional recovery for these subjects.

Spinocerebellar ataxias type 1, 2 and 3: a study of heart rate variability

OBJECTIVE

To detect cardiac autonomic dysfunction, using analysis of heart rate variability in genetically defined spinocerebellar ataxias (SCA).

MATERIALS AND METHODS

Consecutive RR intervals were analyzed for time- and frequency-domain parameters in 22 genotypically proven SCA patients (SCA1 = 11, SCA2 = 6 and SCA3 = 5) and compared with that of age- and gender-matched controls.

RESULTS

Reduction in the standard deviation of RR interval (RR_SD) was seen in 72.7% of SCA patients. There was a reduction in both the parasympathetic and sympathetic parameters in SCA without any change in the ratio of low- to high-frequency power. In SCA1, there was a significant negative correlation between RR_SD and duration of illness but not with the CAG repeat lengths of the abnormal allele. Small sample size of SCA2 and SCA3 precluded similar comparison.

CONCLUSIONS

Cardiac autonomic dysfunction, predominantly parasympathetic, was seen in SCA, and the severity correlated with the duration of illness in SCA1.