Admission Heart Rate Variability Is Associated With Poststroke Depression in Patients With Acute Mild-Moderate Ischemic Stroke

Preclinical evaluation of ZL006-05, a new antistroke drug with fast-onset antidepressant and anxiolytic effects

BACKGROUND

Poststroke depression and anxiety, independent predictor of poor functional outcomes, are common in the acute phase of stroke. Up to now, there is no fast-onset antidepressive and anxiolytic agents suitable for the management of acute stroke. ZL006-05, a dual-target analgesic we developed, dissociates nitric oxide synthase from postsynaptic density-95 while potentiates α2-containing γ-aminobutyric acid type A receptor. This study aims to determine whether ZL006-05 can be used as an antistroke agent with fast-onset antidepressant and anxiolytic effects.

METHODS

Photothrombotic stroke and transient middle cerebral artery occlusion were induced in rats and mice. Infarct size was measured by TTC(2,3,5-Triphenyltetrazolium chloride) staining or Nissl staining. Neurological defects were assessed by four-point scale neurological score or modified Neurological Severity Scores. Grid-walking, cylinder and modified adhesive removal tasks were conducted to assess sensorimotor functions. Spatial learning was assessed using Morris water maze task. Depression and anxiety were induced by unpredictable chronic mild stress. Depressive behaviours were assessed by tail suspension, forced swim and sucrose preference tests. Anxiety behaviours were assessed by novelty-suppressed feeding and elevated plus maze tests. Pharmacokinetics, toxicokinetics and long-term toxicity studies were performed in rats.

RESULTS

Administration of ZL006-05 in the acute phase of stroke attenuated transient and permanent ischaemic injury and ameliorated long-term functional impairments significantly, with a treatment window of 12 hours after ischemia, and reduced plasminogen activato-induced haemorrhagic transformation. ZL006-05 produced fast-onset antidepressant and anxiolytic effects with onset latency of 1 hour in the normal and CMS mice, had antidepressant and anxiolytic effects in stroke mice. ZL006-05 crossed the blood-brain barrier and distributed into the brain rapidly, and had a high safety profile in toxicokinetics and long-term toxicological studies.

CONCLUSION

ZL006-05 is a new neuroprotectant with fast-onset antidepressant and anxiolytic effects and has translational properties in terms of efficacy, safety and targeting of clinical issues.

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.

Machine learning algorithms assisted identification of post-stroke depression associated biological features

Objectives

Post-stroke depression (PSD) is a common and serious psychiatric complication which hinders functional recovery and social participation of stroke patients. Stroke is characterized by dynamic changes in metabolism and hemodynamics, however, there is still a lack of metabolism-associated effective and reliable diagnostic markers and therapeutic targets for PSD. Our study was dedicated to the discovery of metabolism related diagnostic and therapeutic biomarkers for PSD.

Methods

Expression profiles of GSE140275, GSE122709, and GSE180470 were obtained from GEO database. Differentially expressed genes (DEGs) were detected in GSE140275 and GSE122709. Functional enrichment analysis was performed for DEGs in GSE140275. Weighted gene co-expression network analysis (WGCNA) was constructed in GSE122709 to identify key module genes. Moreover, correlation analysis was performed to obtain metabolism related genes. Interaction analysis of key module genes, metabolism related genes, and DEGs in GSE122709 was performed to obtain candidate hub genes. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. Expression of signature genes was validated in GSE140275, GSE122709, and GSE180470. Gene set enrichment analysis (GSEA) was applied on signature genes. Based on signature genes, a nomogram model was constructed in our PSD cohort (27 PSD patients vs. 54 controls). ROC curves were performed for the estimation of its diagnostic value. Finally, correlation analysis between expression of signature genes and several clinical traits was performed.

Results

Functional enrichment analysis indicated that DEGs in GSE140275 enriched in metabolism pathway. A total of 8,188 metabolism associated genes were identified by correlation analysis. WGCNA analysis was constructed to obtain 3,471 key module genes. A total of 557 candidate hub genes were identified by interaction analysis. Furthermore, two signature genes (SDHD and FERMT3) were selected using LASSO and random forest analysis. GSEA analysis found that two signature genes had major roles in depression. Subsequently, PSD cohort was collected for constructing a PSD diagnosis. Nomogram model showed good reliability and validity. AUC values of receiver operating characteristic (ROC) curve of SDHD and FERMT3 were 0.896 and 0.964. ROC curves showed that two signature genes played a significant role in diagnosis of PSD. Correlation analysis found that SDHD (r = 0.653, P < 0.001) and FERM3 (r = 0.728, P < 0.001) were positively related to the Hamilton Depression Rating Scale 17-item (HAMD) score.

Conclusion

A total of 557 metabolism associated candidate hub genes were obtained by interaction with DEGs in GSE122709, key modules genes, and metabolism related genes. Based on machine learning algorithms, two signature genes (SDHD and FERMT3) were identified, they were proved to be valuable therapeutic and diagnostic biomarkers for PSD. Early diagnosis and prevention of PSD were made possible by our findings.

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.

Effect of mean heart rate on 30-day mortality in ischemic stroke with atrial fibrillation: Data from the MIMIC-IV database

Background

The relationship of mean heart rate (MHR) with 30-day mortality in ischemic stroke patients with atrial fibrillation in the intensive care unit (ICU) remains unknown. This study aimed to investigate the association between MHR within 24 h of admission to the ICU and 30-day mortality among patients with atrial fibrillation and ischemic stroke.

Methods

This retrospective cohort study used data on US adults from the Medical Information Mart for Intensive Care-IV (MIMIC-IV, version 1.0) database. Patients with ischemic stroke who had atrial fibrillation for and first time in ICU admission were identified from the MIMIC-IV database. We used multivariable Cox regression models, a restricted cubic spline model, and a two-piecewise Cox regression model to show the effect of the MHR within 24 h of ICU admission on 30-day mortality.

Results

A total of 1403 patients with ischemic stroke and atrial fibrillation (mean [SD] age, 75.9 [11.4] years; mean [SD] heart rate, 83.8[16.1] bpm; 743 [53.0%] females) were included. A total of 212 (15.1%) patients died within 30 days after ICU admission. When MHR was assessed in tertials according to the 25th and 50th percentiles, the risk of 30-day mortality was higher in participants in group 1 (< 72 bpm; adjusted hazard ratio, 1.23; 95% CI, 0.79–1.91) and group 3 (≥82 bpm; adjusted hazard ratio, 1.77; 95% CI, 1.23–2.57) compared with those in group 2 (72–82 bpm). Consistently in the threshold analysis, for every 1-bpm increase in MHR, there was a 2.4% increase in 30-day mortality (adjusted HR, 1.024; 95% CI, 1.01–1.039) in those with MHR above 80 bpm. Based on these results, there was a J-shaped association between MHR and 30-day mortality in ischemic stroke patients with atrial fibrillation admitted to the ICU, with an inflection point at 80 bpm of MHR.

Conclusion

In this retrospective cohort study, MHR within 24 h of admission was associated with 30-day mortality (nonlinear, J-shaped association) in patients with ischemic stroke and atrial fibrillation in the ICU, with an inflection point at about 80 bpm and a minimal risk observed at 72 to 81 bpm of MHR. This association was worthy of further investigation. If further confirmed, this association may provide a theoretical basis for formulating the target strategy of heart rate therapy for these patients.

Potential markers for predicting delayed encephalopathy in patients with acute carbon monoxide poisoning

BACKGROUND

Acute carbon monoxide poisoning (ACOP) commonly results in delayed neuropsychiatric sequelae (DNS). Currently, there are no reliable predictors. The aim of this article is to establish a practical model for predicting the development of delayed encephalopathy clinically.

METHODS

Retrospective analysis of clinical data were performed at a single institution for the past 6 years. 107 patients with ACOP were recruited, of who 67 developed DNS and 40 did not. Clinical characteristics of the patients were analyzed between the two groups. The risk factors associated with DNS development were screened to identify the potential markers for predicting DNS. A predictive model was then built, and the receiver operating characteristic (ROC) curve analysis was used to assess its predictive ability.

RESULTS

There were significant differences in 13 clinical features between the two groups. Four potential markers were identified. They were age, source of CO, Glasgow Coma Scale score and the initiation of HBOT. The potential predictive model showed an area under the curve (AUC) of 0.93 in the training set and 0.97 in the testing set.

CONCLUSIONS

Our model could calculate the probability of DNS after acute CO poisoning.