Very Low Frequency Heart Rate Variability Predicts the Development of Post-Stroke Infections

Ambulatory electrocardiographic longitudinal monitoring in a canine model for Duchenne muscular dystrophy identifies decreased very low frequency power as a hallmark of impaired heart rate variability

Duchenne muscular dystrophy (DMD) patients exhibit a late left ventricular systolic dysfunction preceded by an occult phase, during which myocardial fibrosis progresses and some early functional impairments can be detected. These latter include electrocardiographic (ECG) and heart rate variability (HRV) abnormalities. This longitudinal study aimed at describing the sequence of ECG and HRV abnormalities, using Holter ECG in the GRMD (Golden retriever muscular dystrophy) dog model, known to develop a DMD-like disease, including cardiomyopathy. Most of the known ECG abnormalities described in DMD patients were also found in GRMD dogs, including increased heart rate, prolonged QT and shortened PR intervals, ventricular arrhythmias, and several of them could be detected months before the decrease of fractional shortening. The HRV was impaired like in DMD patients, one of the earliest evidenced abnormalities being a decrease in the very low frequency (VLF) component of the power spectrum. This decrease was correlated with the further reduction of fractional shortening. Such decreased VLF probably reflects impaired autonomic function and abnormal vasomotor tone. This study provides new insights into the knowledge of the GRMD dog model and DMD cardiomyopathy and emphasizes the interest to monitor the VLF power in DMD patients, still unexplored in this disease, whilst it is highly predictive of deleterious clinical events in many other pathological conditions.

Machine learning using multimodal and autonomic nervous system parameters predicts clinically apparent stroke-associated pneumonia in a development and testing study

BACKGROUND

Stroke-associated pneumonia (SAP) is a preventable determinant for poor outcome after stroke. Machine learning (ML) using large-scale clinical data warehouses may be able to predict SAP and identify patients for targeted interventions. The aim of this study was to develop a prediction model for identifying clinically apparent SAP using automated ML.

METHODS

The ML model used clinical and laboratory parameters along with heart rate (HR), heart rate variability (HRV), and blood pressure (BP) values obtained during the first 48 h after stroke unit admission. A logistic regression classifier was developed and internally validated with a nested-cross-validation (nCV) approach. For every shuffle, the model was first trained and validated with a fixed threshold for 0.9 sensitivity, then finally tested on the out-of-sample data and benchmarked against a widely validated clinical score (A2DS2).

RESULTS

We identified 2390 eligible patients admitted to two-stroke units at Charité between October 2020 and June 2023, of whom 1755 had all parameters available. SAP was diagnosed in 96/1755 (5.5%). Circadian profiles in HR, HRV, and BP metrics during the first 48 h after admission exhibited distinct differences between patients with SAP diagnosis vs. those without. CRP, mRS at admission, leukocyte count, high-frequency power in HRV, stroke severity at admission, sex, and diastolic BP were identified as the most informative ML features. We obtained an AUC of 0.91 (CI 0.88-0.95) for the ML model on the out-of-sample data in comparison to an AUC of 0.84 (CI 0.76-0.91) for the previously established A2DS2 score (p < 0.001). The ML model provided a sensitivity of 0.87 (CI 0.75-0.97) with a corresponding specificity of 0.82 (CI 0.78-0.85) which outperformed the A2DS2 score for multiple cutoffs.

CONCLUSIONS

Automated, data warehouse-based prediction of clinically apparent SAP in the stroke unit setting is feasible, benefits from the inclusion of vital signs, and could be useful for identifying high-risk patients or prophylactic pneumonia management in clinical routine.

Brain connectivity networks underlying resting heart rate variability in acute ischemic stroke

Acute strokes can affect heart rate variability (HRV), the mechanisms how are not well understood. We included 42 acute stroke patients (2-7 days after ischemic stroke, mean age 66 years, 16 women). For analysis of HRV, 20 matched controls (mean age 60.7, 10 women) were recruited. HRV was assessed at rest, in a supine position and individual breathing rhythmus for 5 min. The coefficient of variation (VC), the root mean square of successive differences (RMSSD), the powers of low (LF, 0.04-0.14 Hz) and high (HF, 0.15-0.50 Hz) frequency bands were extracted. HRV parameters were z-transformed related to age- and sex-matched normal subjects. Z-values < -1 indicate reduced HRV. Acute stroke lesions were marked on diffusion-weighted images employing MRIcroN and co-registered to a T1-weighted structural volume-dataset. Using independent component analysis (ICA), stroke lesions were related to HRV. Subsequently, we used the ICA-derived lesion pattern as a seed and estimated the connectivity between these brain regions and seven common functional networks, which were obtained from 50 age-matched healthy subjects (mean age 68.9, 27 women). Especially, LF and VC were frequently reduced in patients. ICA revealed one covarying lesion pattern for LF and one similar for VC, predominantly affecting the right hemisphere. Activity in brain areas corresponding to these lesions mainly impact on limbic (r = 0.55 ± 0.08) and salience ventral attention networks (0.61 ± 0.10) in the group with reduced LF power (z-score < -1), but on control and default mode networks in the group with physiological LF power (z-score > -1). No different connectivity could be found for the respective VC groups. Our results suggest that HRV alteration after acute stroke might be due to affecting resting-state brain networks.

Evaluation of skin sympathetic nervous activity for classification of intracerebral hemorrhage and outcome prediction

Classification and outcome prediction of intracerebral hemorrhage (ICH) is critical for improving the survival rate of patients. Early or delayed neurological deterioration is common in ICH patients, which may lead to changes in the autonomic nervous system (ANS). Therefore, we proposed a new framework for ICH classification and outcome prediction based on skin sympathetic nervous activity (SKNA) signals. A customized measurement device presented in our previous papers was used to collect data. 117 subjects (50 healthy control subjects and 67 ICH patients) were recruited for this study to obtain their 5-min electrocardiogram (ECG) and SKNA signals. We extracted the signal's time-domain, frequency-domain, and nonlinear features and analyzed their differences between healthy control subjects and ICH patients. Subsequently, we established the ICH classification and outcome evaluation model based on the eXtreme Gradient Boosting (XGBoost). In addition, heart rate variability (HRV) as an ANS assessment method was also included as a comparison method in this study. The results showed significant differences in most features of the SKNA signal between healthy control subjects and ICH patients. The ICH patients with good outcomes have a higher change rate and complexity of SKNA signal than those with bad outcomes. In addition, the accuracy of the model for ICH classification and outcome prediction based on the SKNA signal was more than 91% and 83%, respectively. The ICH classification and outcome prediction based on the SKNA signal proved to be a feasible method in this study. Furthermore, the features of change rate and complexity, such as entropy measures, can be used to characterize the difference in SKNA signals of different groups. The method can potentially provide a new tool for rapid classification and outcome prediction of ICH patients. Index Terms-intracerebral hemorrhage (ICH), skin sympathetic nervous activity (SKNA), classification, outcome prediction, cardiovascular and cerebrovascular diseases.

Heart rate variability as a marker and predictor of inflammation, nosocomial infection, and sepsis - A systematic review

PURPOSE

The autonomic nervous system interacts with the immune system via the inflammatory response. Heart rate variability (HRV), a marker of autonomic activity, is associated with inflammation, and nosocomial infections/sepsis, and has clinical implications for the monitoring of at-risk patients. Due to the vagal tone's influence on anti-inflammatory immune response, this association may predominately be reflected by vagally-mediated HRV indices. However, HRV's predictive significance on inflammation/infection remains unclear.

METHODS

843 studies examining the associations/prognostic value of HRV indices on inflammation, and nosocomial infection/sepsis were screened in this systematic review. According to inclusion and exclusion criteria, 68 associative studies and 14 prediction studies were included.

RESULTS

HRV and pro-inflammatory state were consistently associated in healthy subjects and patient groups. Pro-inflammatory state was related to reduced total power HRV including vagally- and non-vagally-mediated HRV indices. Similar, compared to controls, HRV reductions were observed during nosocomial infections/sepsis. Only limited evidence supports the predictive value of HRV in the development of nosocomial infections/sepsis. Reduced very low frequency power HRV showed the highest predictive value in adults, even with different clinical conditions. In neonates, an increased heart rate characteristic score, combining reduced total power HRV, decreased complexity, and vagally-dominated asymmetry, predicted sepsis.

CONCLUSIONS

Pro-inflammatory state is related to an overall reduction in HRV rather than a singular reduction in vagally-mediated HRV indices, reflecting the complex autonomic-regulatory changes occurring during inflammation. The potential benefit of using continuous HRV monitoring for detecting nosocomial infection-related states, and the implications for clinical outcome, need further clarification.

Exploring the Utility of Autonomic Nervous System Evaluation for Stroke Prognosis

Stroke is a major cause of functional disability and is increasing in frequency. Therefore, stroke prognosis must be both accurate and timely. Among other biomarkers, heart rate variability (HRV) is investigated in terms of prognostic accuracy within stroke patients. The literature research of two databases (MEDLINE and Scopus) is performed to trace all relevant studies published within the last decade addressing the potential utility of HRV for stroke prognosis. Only the full-text articles published in English are included. In total, forty-five articles have been traced and are included in the present review. The prognostic value of biomarkers of autonomic dysfunction (AD) in terms of mortality, neurological deterioration, and functional outcome appears to be within the range of known clinical variables, highlighting their utility as prognostic tools. Moreover, they may provide additional information regarding poststroke infections, depression, and cardiac adverse events. AD biomarkers have demonstrated their utility not only in the setting of acute ischemic stroke but also in transient ischemic attack, intracerebral hemorrhage, and traumatic brain injury, thus representing a promising prognostic tool whose clinical application may greatly facilitate individualized stroke care.

Association between vitamin B12 status and heart rate variability in patients with ischemic stroke

Autonomic dysfunction is common in patients with ischemic stroke. An ischemic stroke may induce abnormalities in autonomic tone, resulting in poor heart rate regulation and an increased risk of severe cardiac arrest and sudden death. Heart rate variability (HRV) is a reliable index for evaluating autonomic dysfunction. Vitamin B12 deficiency is frequent among older adults and is a known risk factor for ischemic stroke. As vitamin B12 deficiency affects the peripheral nerves and the central nervous system, it can lead to autonomic dysfunction. However, no study has been published on the correlation between HRV and vitamin B12 status in patients with ischemic stroke. This study aimed to investigate the relationship between HRV and vitamin B12 status and to determine whether the serum vitamin B12 level can be a predictor of HRV parameters. This retrospective study enrolled patients with ischemic stroke between January 2015 and December 2022. The patients underwent serum vitamin B12 level measurements and 24-h Holter monitoring. Pearson correlation analysis was used to investigate the correlation between serum vitamin B12 levels and HRV parameters. The impact of serum vitamin B12 status on HRV parameters was determined using multiple linear regression analysis. A total of 87 patients with ischemic stroke were included in this study. HRV parameters were significantly correlated with serum vitamin B12 status in the frequency domain. In multiple linear regression analysis, the serum vitamin B12 status was a significant predictor of HRV parameters. HRV parameters may be correlated with serum vitamin B12 status in patients with ischemic stroke. Therefore, the serum vitamin B12 status may be a significant predictor of autonomic dysfunction. Our results may provide objective evidence for the impact of serum vitamin B12 status on autonomic dysfunction in patients with ischemic stroke.

Heart rate variability as a predictor of stroke course, functional outcome, and medical complications: A systematic review

Background: Heart rate variability (HRV) is a non-invasive marker of autonomic nervous system function that is based on the analysis of length differences between subsequent RR intervals of the electrocardiogram. The aim of this systematic review was to assess the current knowledge gap in the utility of HRV parameters and their value as predictors of the acute stroke course. Methods: A systematic review was performed in accordance with the PRISMA guidelines. Relevant articles published between 1 January 2016 and 1 November 2022 available in the PubMed, Web of Science, Scopus, and Cochrane Library databases were obtained using a systematic search strategy. The following keywords were used to screen the publications: "heart rate variability" AND/OR "HRV" AND "stroke." The eligibility criteria that clearly identified and described outcomes and outlined restrictions on HRV measurement were pre-established by the authors. Articles assessing the relationship between HRV measured in the acute phase of stroke and at least one stroke outcome were considered. The observation period did not exceed 12 months. Studies that included patients with medical conditions influencing HRV with no established stroke etiology and non-human subjects were excluded from the analysis. To minimize the risk of bias, disagreements throughout the search and analysis were resolved by two independent supervisors. Results: Of the 1,305 records obtained from the systematic search based on keywords, 36 were included in the final review. These publications provided insight into the usability of linear and non-linear HRV analysis in predicting the course, complications, and mortality of stroke. Furthermore, some modern techniques, such as HRV biofeedback, for the improvement of cognition performance after a stroke are discussed. Discussion: The present study showed that HRV could be considered a promising biomarker of a stroke outcome and its complications. However, further research is needed to establish a methodology for appropriate quantification and interpretation of HRV-derived parameters.

Brain to periphery in acute ischemic stroke: Mechanisms and clinical significance

The social and public health burdens of ischemic stroke have been increasing worldwide. In addition to focal brain damage, acute ischemic stroke (AIS) provokes systemic abnormalities across peripheral organs. AIS profoundly alters the autonomic nervous system, hypothalamic-pituitary-adrenal axis, and immune system, which further yield deleterious organ-specific consequences. Poststroke systemic pathological alterations in turn considerably contribute to the progression of ischemic brain injury, which accounts for the substantial impact of systemic complications on stroke outcomes. This review provides a comprehensive and updated pathophysiological model elucidating the systemic effects of AIS. To address their clinical significance and inform stroke management, we also outline the resulting systemic complications at particular stages of AIS and highlight the mechanisms. Future therapeutic strategies should attempt to integrate the treatment of primary brain lesions with interventions for secondary systemic complications, and should be tailored to patient individualized characteristics to optimize stroke outcomes.

Getting to the heart of food craving with resting heart rate variability in adolescents

BACKGROUND

There is an epidemic of obesity in children and adolescents. Research into the self-regulatory factors that drive eating behavior is of critical importance. Food craving contributes to overeating and difficulty with weight loss and is strongly correlated with self-regulation. High-frequency heart rate variability (HF HRV) reflects parasympathetic activity and is positively associated with self-regulation. Few studies of HF HRV and food craving have been conducted in adolescents. The current study examined the association between HF HRV and food craving in a large-scale sample of healthy adolescents.

METHOD

Electrocardiogram (ECG) was recorded in 134 healthy adolescents aged 10-17 during a 7-min resting state. Participants also completed the Food Craving Questionnaire-Trait (FCQ-T). The relative power of HF HRV was calculated. Association between HF HRV and food craving was examined in the context of sex and age. Next, the relative significance of all food craving subscales was considered in relation to HF HRV.

RESULTS

HF HRV was inversely correlated with food craving, taking into account sex and age. Considering all the subscales of FCQ-T in relation to HF HRV, the "lack of control over eating" subscale accounted for the most significant variance.

CONCLUSION

This was the first study to evaluate resting HRV and eating behaviors in a large-scale adolescent sample. HF HRV was negatively associated with food craving, with lower HF HRV correlating with higher food craving, especially in the context of diminished control over eating. HF HRV could be a potential biomarker for food craving and food-related self-regulation capacity, and therefore may aid weight management interventions.

The effect of remote ischemic postconditioning on autonomic function in patients with acute ischemic stroke: A Randomized Controlled Trail

OBJECTIVE

The evidence for the effect of remote ischemic postconditioning(RIpostC) on autonomic function in patients with acute ischemic stroke(AIS) is lacking and the neural mechanism underlying the protection of RIpostC remains speculative. This trial was aimed to evaluated the efficiency of RIpostC on autonomic function in AIS patients.

DESIGN

One hundred and six AIS patients were included in this prospective, randomized, placebo-controlled trial. Patients in intervention group (n = 57) received 4 cycles of alternating inflation (cuff inflation to 200 mmHg) and deflation for 5 min on healthy upper arm once a day for 30 days. The control group underwent a sham inflation and deflation cycles. Autonomic function was evaluated by heart rate variability (HRV).

RESULTS

All HRV parameters except for the ratio of low frequency to high frequency (P = 0.101) increased significantly with time (P < 0.001) in the two groups. The value of standard deviation of all normal R-R intervals(SDNN) and high frequency at day7 and day30 and the value of the percent of difference between adjacent normal R-R intervals (pNN50) at day 30 in RIpostC group was significantly higher than that of the sham-RIpostC group(P < 0.05). A significant time-by-group interaction was observed in SDNN、pNN50、and high frequency over time between two groups (P < 0.05).

CONCLUSIONS

30-day RIpostC could improve autonomic function in AIS patients through the enhancement of the total autonomic nerve activity and vagus nerve activity. The mechanism of RIpostC mediating autonomic function needs to be further investigated.

The Association of Autonomic Nervous System Function With Ischemic Stroke, and Treatment Strategies

Acute ischemic stroke, especially minor stroke, and transient ischemic attack have high risks of recurrence and exacerbation into severe ischemic strokes. It remains challenging to perform risk stratification and screen high-risk groups for initiation of early treatment in these patients. Moreover, with the growing population of patients with chronic small vessel disease, the mechanisms and clinical implications require further investigation. Traditional tools such as the ABCD2 score (age, blood pressure, clinical features, duration of symptoms, diabetes) have only moderate predictive value in patients with transient ischemic attack or minor stroke. By contrast, measurement of changes in heart rate variability (HRV) is an important and novel tool for risk stratification and outcome prediction in patients with cardiovascular diseases, as it reflects the overall level of autonomic nervous system dysfunction. Thus, abnormal HRV may be useful for prognosis and improve stratification of stroke patients with diverse risks. HRV may also partially explain autonomic nervous dysfunction and other manifestations during the process of chronic cerebral small vessel disease. In summary, measurement of HRV may contribute to early initiation of interventions in acute or chronic stroke patients using novel treatments involving rebalancing of autonomic nervous system function.

Baroreflex sensitivity is associated with post-stroke infections. An open, prospective study

BACKGROUND AND PURPOSE

Autonomic nervous system (ANS) seems to play an important role in the post-stroke immunosuppression syndrome with increased susceptibility to infections. The aim of this study was to investigate if ANS activity measured at admission is associated with post-stroke infections.

METHODS

We prospectively analyzed patients with acute ischemic stroke. ANS was measured using the cross-correlational baroreflex sensitivity (BRS) at admission. The occurrence and cause of in-hospital infections was assessed based on the clinical and laboratory examination. Demographic and clinical variables including initial stroke severity, dysphagia, procedures as nasogastric tubes, central venous and urinary catheters and mechanical ventilation were included in the analysis.

RESULTS

We included 161 patients with ischemic stroke, of those 49 (30.4%) developed a nosocomial infection during the first 7 days of hospital stay. Patients with infections had significantly lower BRS (median 3 vs 5 ms/mmHg, p < .001) higher initial NIHSS (median 15 vs 5, p < .001), had more often non-lacunar etiology and underwent more invasive procedures. In the multivariable regression model decreased BRS (adjusted OR 1.21, 95% CI 1.03-1.41, p = .02), admission NIHSS (adjusted OR 1.10, 95% CI 1.02-1.19, p = .02) and invasive procedures (adjusted OR 1.46, 95% CI 1.03-2.06, p = .03) were independently associated with infection after ischemic stroke.

CONCLUSIONS

Decreased BRS was independently associated with infections after ischemic stroke. Autonomic shift may play an important role in increased susceptibility to infections after stroke. The possible diagnostic and therapeutic relevance of this finding deserves further research.