Alleviating sleep disturbances and modulating neuronal activity after ischemia: Evidence for the benefits of zolpidem in stroke recovery

The Role of Mature Brain-Derived Neurotrophic Factor and Its Precursor in Predicting Early-Onset Insomnia in Stroke Patients Experiencing Early Neurological Deterioration

Background

The investigation and management of early-onset insomnia (EOI) in patients undergoing early neurological deterioration (END) appear to be insufficiently prioritized in clinical practice. Brain-derived neurotrophic factor (mBDNF) and its precursor, proBDNF, play essential roles in neuroplasticity and may be involved in the pathophysiological mechanisms underlying EOI. This study aimed to investigate the associations of serum mBDNF, proBDNF, and the mBDNF/proBDNF ratio with EOI in stroke patients experiencing END.

Methods

In a prospective cohort study from October 2021 to December 2023, 232 stroke patients with END and 56 healthy controls (HCs) were enrolled. Serum levels of mBDNF and proBDNF were quantified using enzyme-linked immunosorbent assays. EOI was diagnosed according to the International Classification of Sleep Disorders, Third Edition (ICSD-3). Patients with END were categorized into subgroups based on the presence or absence EOI.

Results

Serum levels of mBDNF, proBDNF, and the mBDNF/proBDNF ratio were significantly lower in END patients compared to those in HCs (all p < 0.05). Among the 232 END patients, 82 (35.3%) developed EOI. Those with EOI had significantly lower levels of mBDNF and the mBDNF/proBDNF ratio compared to those without EOI (all p < 0.001). Multivariate logistic regression analysis revealed that male gender (p = 0.026), Hamilton Depression Rating Scale (HAMD) scores (p < 0.001), mBDNF (p = 0.009), and the mBDNF/proBDNF ratio (p < 0.001) were independent predictors of EOI in END patients. The areas under the curve (AUC) for mBDNF and the mBDNF/proBDNF ratio were 0.686 and 0.778, respectively.

Conclusion

Our study identified a correlation between reduced mBDNF levels and a decreased mBDNF/proBDNF ratio with the development of EOI in END patients. In addition, the mBDNF/proBDNF ratio may provide greater insight as a promising biomarker for EOI than mBDNF or proBDNF alone.

Development and validation of a nomogram for sleep disorders among stroke patients

BACKGROUND

Precisely identifying high-risk sleep disorder patients and implementing suitable measures are important for decreasing the incidence of sleep disorders. In this study, a nomogram method was adopted to construct a tool to predict sleep disorders in stroke based on four factors: individual characteristics, treatment-related factors, psychological factors, and family-related factors.

METHODS

A total of 450 stroke patients were continuously diagnosed at the Affiliated Hospital of Nantong University, and the data on participants were randomly distributed into a training set (n = 315) and a validation set (n = 135). Within the training set, using LASSO regression and random forest methods, five optimal predictors of sleep disorders were identified. Five optimal predictors were used to develop a model. The calibration, discrimination, generalization, and clinical applicability of the model were evaluated using calibration curves, receiver operating characteristic (ROC) curves, internal validation, and decision curve analysis (DCA).

RESULTS

We found that the place of residence, average daily infusion time, the Hospital Anxiety and Depression Scale (HADS), the Type D Personality Scale-14 (DS14), and the Fatigue Severity Scale (FSS) were crucial factors associated with sleep disorders. The validation data showed an area under the curve (AUC) of 0.903 compared to 0.899 in the training set. There was an approach to the diagonal in the calibration curve of this model, and the results of DCA noted that it is clinically beneficial across a range of thresholds from 5 % to 99 %.

CONCLUSION

A model was developed to predict sleep disorders among stroke patients to help hospital staff evaluate the risk among patients and screen high-risk patients.

Deciphering Post-Stroke Sleep Disorders: Unveiling Neurological Mechanisms in the Realm of Brain Science

Sleep disorders are the most widespread mental disorders after stroke and hurt survivors' functional prognosis, response to restoration, and quality of life. This review will address an overview of the progress of research on the biological mechanisms associated with stroke-complicating sleep disorders. Extensive research has investigated the negative impact of stroke on sleep. However, a bidirectional association between sleep disorders and stroke exists; while stroke elevates the risk of sleep disorders, these disorders also independently contribute as a risk factor for stroke. This review aims to elucidate the mechanisms of stroke-induced sleep disorders. Possible influences were examined, including functional changes in brain regions, cerebrovascular hemodynamics, neurological deficits, sleep ion regulation, neurotransmitters, and inflammation. The results provide valuable insights into the mechanisms of stroke complicating sleep disorders.