Related risk factors associated with post-stroke fatigue: a systematic review and meta-analysis

Changes in fatigue after first-ever ischemic stroke and their associations with changes in physical fitness, body composition, and physical activity

OBJECTIVES

The objectives of the present study were 1) to describe changes in fatigue from 3 to 12 months post-stroke and compare different patterns of fatigue changes with respect to concurrent changes in physical fitness, body composition, and activity levels, and 2) to explore whether changes in fatigue are associated with changes in physical fitness, body composition, and physical activity levels in patients recovering from first-ever ischemic stroke.

MATERIALS AND METHODS

In this longitudinal observational study, we assessed 72 patients (mean age 62 years, 36 % females) at 3 and 12 months after first-ever ischemic stroke. Fatigue was measured with the 7-item Fatigue Severity Scale. Physical fitness, body composition and physical activity were assessed using cardiopulmonary exercise testing, physical function tests, Dual-energy X-ray Absorptiometry, and accelerometers.

RESULTS

Fatigue levels was stable between 3 and 12 months post-stroke in 44 (61 %) patients, decreased in 14 (19 %), and increased in another 14 (19 %). Patients with increased fatigue levels showed a greater decrease in cardiorespiratory fitness, as measured directly by peak oxygen uptake, compared to those with decreased fatigue. Robust regression analysis, adjusted for age and sex, indicated that each kilogram of lean body mass gained from 3 to 12 months post-stroke was significantly associated with a 0.3-point reduction in fatigue during the same timeframe (B= -0.32; 95 %CI [-0.51, -0.12]).

CONCLUSION

There was considerable individual variation in changes to fatigue, physical fitness, body composition, and physical activity levels between 3 and 12 months following a first-ever ischemic stroke. Increased fatigue was linked to a greater concurrent decline in cardiorespiratory fitness, while lean body mass was associated with decreases in fatigue.

The association of post-COVID-19 fatigue in the acute phase with neuropsychiatric and neurocognitive symptoms trajectory over time and long-term health-related quality of life among Chinese adults

BACKGROUND

Post-viral fatigue is a common and debilitating neurological sequela of COVID-19, often accompanied with multidimensional neuropsychiatric symptoms (post-viral fatigue, sleep disturbance, anxiety, depression, and post-traumatic stress disorder) and neurocognitive impairment. We sought to characterize the trajectory of these neurological symptoms and investigate the relationship between acute-phase fatigue (< 1 month) and the chronicity of neuropsychiatric and neurocognitive symptoms, as well as long-term health-related quality of life (HRQoL) at 3 months post-infection.

METHODS

A prospective, multi-center, longitudinal study was conducted from January to February 2023 within a cohort of individuals with a mild SARS-COV-2 infection and contemporaneous healthy controls (HCs). Comprehensive neuropsychiatric and neurocognitive assessments were collected for COVID-19 survivors during both acute and chronic phase post-infection, with the EQ-5D-5L (a standardized instrument for assessing HRQoL) evaluated at the chronic phase. Healthy controls underwent the same protocol for recruitment to the study. Linear mixed models were used to access the impact of acute-phase fatigue on different neuropsychiatric and neurocognitive scales over time.

RESULTS

Three hundred thirty-five COVID-19 survivors and 79 HCs were included in the study. COVID-19 survivors exhibited poorer performance in various neuropsychiatric domains during the acute phase, with the exception of cognitive impairment. A significant amelioration of emotional symptoms, including anxiety and depression, was observed from the acute to chronic phase among COVID-19 survivors, reaching levels comparable to those of HCs. However, at 3 months post-infection, survivors continued to report higher levels of fatigue and poorer sleep quality compared to HCs, although the differences had diminished from the acute phase. The impact of the pandemic event persisted, and no significant changes in cognitive performance were observed. Acute-phase fatigue was associated with poorer sleep and worse emotional problems during the recovery process (from the acute to the chronic phase), and further exacerbated overall HRQoL at 3 months post-infection (EQ index score, p = 0.001, Cohen's d = -0.33; EQ-VAS, p = 0.007, Cohen's d = -0.19).

CONCLUSIONS

Our findings provide novel evidence on the distinct temporal trajectories for post-acute COVID-19 sequelae in a longitudinal study, highlighting the negative impact of acute-phase fatigue on the process of neuropsychiatric recovery and long-term HRQoL.

Prevalence, Trajectory, and Predictors of Poststroke Fatigue in Older Adults

OBJECTIVE

To explore the prevalence, trajectories, and predictors of poststroke fatigue in older adults after a first ischemic stroke.

DESIGN

A longitudinal observational cohort study.

SETTING

Two hospitals.

PARTICIPANTS

A total of 381 patients aged ≥65 years with their first ischemic stroke were included. The mean (standard deviation) age was 71.1 (4.27) years, with 96 patients (25.2%) being women and 285 (74.8%) being men.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Patients were assessed using the Fatigue Severity Scale at admission, 3 months, and 12 months. Growth mixture models were used to identify distinct fatigue trajectories, and baseline variables were analyzed to determine their association with these trajectories.

RESULTS

The prevalence of clinical fatigue was 39.11%, 33.33%, and 22.31% at admission, 3 months, and 12 months, respectively. Five distinct fatigue trajectories were identified: persistently low fatigue (class 1, 49.1%), persistently high fatigue (class 2, 21.5%), initial high but early decreasing fatigue (class 3, 15.0%), initial high but late decreasing fatigue (class 4, 8.7%), and increasing-then-decreasing fatigue (class 5, 5.8%). Multinomial logistic regression analysis revealed that several factors were significantly associated with high and persistent fatigue (class 2), including older age, lower social support, decreased physical activity, higher depression and anxiety scores, cognitive impairment, and greater stroke severity.

CONCLUSIONS

These findings indicate significant variability in the progression of fatigue among stroke survivors. Further research is necessary to determine the outcomes linked to these fatigue trajectory subgroups and to identify the most effective treatment strategies tailored to each specific subgroup.

Daily Bidirectional Associations Between Sleep and Fatigue, Depression, and Anxiety in Stroke Survivors: A 7-Day Intensive Longitudinal Study

OBJECTIVE

To examine the bidirectional relationship between sleep quality and mood states including fatigue, depression, and anxiety in stroke survivors.

DESIGN

A prospective observational study using ecological momentary assessment (EMA) surveys conducted 3 times daily over a 7-day period.

SETTING

A tertiary-level, class A hospital.

PARTICIPANTS

Thirty-four stroke survivors (N=34).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

EMA measures of mood symptoms (fatigue, depression, anxiety) and sleep, including subjective and objective total sleep time (TST), sleep onset latency (SOL), total wake after sleep onset (WASO), number of awakenings (NWK), sleep efficiency (SE), and sleep quality.

RESULTS

Multilevel models revealed that more frequent NWK and increased TST were associated with greater fatigue, whereas higher SE was linked to lower depression levels. EMA analyses showed that greater daytime fatigue and evening anxiety were unexpectedly associated with improved same-night sleep quality, whereas better sleep quality was linked to increased next-day fatigue. No significant associations were found between sleep quality and next-day depression or anxiety. Fatigue and anxiety peaked in the morning and decreased significantly by evening, whereas depression showed reductions in the afternoon and evening compared with morning levels. However, no significant interaction was observed between sleep quality and time of day in their effects on mood.

CONCLUSIONS

This study provides preliminary evidence of the intricate and dynamic relationship between sleep and mood in stroke survivors, highlighting the bidirectional associations and time of day effects. These findings emphasize the need for targeted, personalized, and multifaceted interventions to improve both sleep and mood in stroke patients. Further research is necessary to validate these observations and explore mechanisms underlying these associations.

Post-stroke fatigue: The role of comorbidities and its impact on quality of life

BACKGROUND

Post-stroke fatigue (PSF) is a common complication following stroke that affects approximately 50% of stroke survivors.

PURPOSE

The purpose of this study was to investigate the role of comorbidities in PSF and the impact of PSF on Quality of Life (QoL). To achieve this, residual stroke symptoms have also been considered.

METHODS

The participants were stroke survivors living in a Swedish municipality. Self-reported data were collected via the Fatigue Assessment Scale (FAS), the Riksstroke questionnaire, and the Short Form Health Survey 36 (SF-36). Linear multiple regression and Spearman's correlation coefficient were used to analyze the data.

RESULTS

A total of 142 participants (83 men) with a mean age of 74.8 (SD 9.7) years were included in the study. Fatigue levels were classified as normal (FAS 10-21) for 70 (49.3%) individuals, mild-to-moderate (FAS 22-34) for 56 (39.4%) individuals, and severe (FAS 35-50) for 16 (11.3%) individuals. The mean FAS score was 23.3 (SD 8.2). Multiple regression analysis indicated that the presence of vertigo (β = 0.24, p = 0.004), chronic pulmonary disorders (β = 0.29, p = 0.003), and hemiparesis (β = 0.18, p = 0.05) were associated with more severe PSF. The model explained 19.2% of the variance in PSF. A higher level of PSF was associated with worse QoL in all eight SF-36 domains (r = -0.38 to -0.67).

CONCLUSIONS

Vertigo, chronic pulmonary disorders, and hemiparesis were significantly associated with more severe PSF. Additionally, higher levels of fatigue were associated with a worse QoL. These findings confirm that PSF is a multifaceted phenomenon, underscoring the importance of addressing PSF in rehabilitation to improve outcomes for stroke survivors.

Machine Learning-Based Model for Prediction of Early Post-Stroke Fatigue in Patients With Stroke: A Longitudinal Study

BackgroundPost-stroke fatigue, as one of the long-lasting physical and mental symptoms accompanying stroke survivors, will seriously affect the daily living ability and quality of life of stroke patients.ObjectiveThe aim of this study was to develop machine learning (ML) algorithms to predict early post-stroke fatigue among patients with stroke.MethodsA longitudinal study of 702 patients with stroke followed for 3 months. Twenty-three clinical features were obtained from medical records and questionnaires before discharge. Early post-stroke fatigue was assessed using the Fatigue Severity Scale. The dataset was randomly divided into a training group (70%) and an internal validation group (30%), applied oversampling, 10-fold cross-validation, and grid search to optimize the hyperparameter. Feature selection using the Least Absolute Shrinkage and Selection Operator (LASSO) regression. Sixteen ML algorithms were performed to predict early post-stroke fatigue in this study. Accuracy, precision, recall, F1 score, area under the receiver operating characteristic curve (AUC), and brier score were used to evaluate the models performance.ResultsAmong the 16 ML algorithms, the Bagging model was the optimal model for predicting early post-stroke fatigue in patients with stroke (AUC = 0.8479, accuracy = 0.7518, precision = 0.5741, recall = 0.7209, F1 score = 0.6392, brier score = 0.1490). The feature selection based on LASSO revealed that risk factors for early post-stroke fatigue in patients with stroke included anxiety, sleep, social support, family care, pain, depression, neural-functional defect, quit/no drinking, balance function, type of stroke, sex, heart disease, smoking, and hemiplegia.ConclusionsIn this study, the Bagging model proved to be effective in predicting early post-stroke fatigue.

Influencing factors and predictive models of early post-stroke depression in patients with acute ischemic stroke

BACKGROUND

Post-stroke depression (PSD) refers to a depressive state that appears after stroke onset and is one of the most common complications in ischemic stroke patients. The occurrence of PSD exacerbates the risk of disability and increases the mortality of patients. Current diagnosis of PSD is severely underdiagnosed.

METHODS

Patients hospitalized for acute ischemic stroke between December 2019 and November 2022 in the Department of Neurology of Sinopharm Gezhouba Central Hospital were retrospectively collected. Patients' basic clinical information, test data and related questionnaire scores were collected. They were divided into PSD group and NPSD group. Multivariate regression was used to analyze the risk factors of post-stroke depression and establish a risk prediction model to draw nomograms. Receiver Operating Characteristic Curve (ROC), Calibration curve and Decision Curve Analysis (DCA) decision curve were drawn using R language to assess the clinical efficacy and clinical utility of the model.

RESULTS

Post-stroke depression in Acute Ischemic Stroke (AIS) patients was associated with single factors such as hypertension, living alone, education level, homocysteine level, National Institute of Health Stroke Scale (NIHSS) score, lymphocyte count, neutrophil count (P < 0.05). Among them, living alone, CRP level, hypertension, homocysteine level, education level, systemic immune inflammation index (SII), and NIHSS score were independent risk factors for post-stroke depression in AIS patients (P < 0.05). The seven selected variables were used to construct a risk prediction model, nomograms were drawn, and ROC curves were used to assess model discrimination, AUROC = 0.881. Calibration curve is used to evaluate the consistency of the model, DCA decision curve is used to evaluate the practicability of the model, and this model has good discrimination ability, calibration and clinical practicability.

CONCLUSION

The probability of PSD in AIS patients in this study was 26.51%. Independent risk factors for developing PSD, including CRP level, living alone, history of hypertension, homocysteine level, education level, SII, NIHSS score to establish risk prediction model and draw nomograms. The model was demonstrated to have good discrimination, calibration and clinical utility by internal validation.

Prevalence of fatigue and perceived fatigability in older adults: a systematic review and meta-analysis

Fatigue is a common health complaint in older adults, but its prevalence varies widely among studies due to differences in populations and assessment tools. The objective of this review is to systematically evaluate the prevalence of fatigue and perceived fatigability in older adults with PRISMA 2020. Four databases-PubMed, Embase, Web of Science (WoS), and Cochrane Library-were systematically searched as of December 27, 2023. Cochrane Q tests and the I2 statistic were used using Stata16.0 to assess between-study heterogeneity. A total of 21 studies involving 17843 participants were included in this study. The prevalence of fatigue in older adults was 42.6%, and the prevalence of perceived physical fatigability and mental fatigability was 58.2% and 24.0%. Meta-analysis showed that the prevalence of perceived physical fatigability among older adults was very high. This prevalence varied with regional economic development level, age of the subjects, sample size, and representativeness of the subjects. Fatigue is a health dilemma faced by most older adults. To improve quality of life, early and regular fatigue assessment should be part of routine health screening for older adults.

Post-stroke fatigue - a multidimensional problem or a cluster of disorders? A case for phenotyping post-stroke fatigue

Post-stroke fatigue is a chronic problem with significant impact on morbidity and mortality, which urgently needs effective treatments. The last decade has seen a considerable increase in interest in understanding the pathophysiology of fatigue and developing treatments. In this review, following a summary of theoretical frameworks to understand chronic fatigue, I make a case for why phenotyping fatigue is a necessary step to fully understand pathophysiology, which in turn is essential for the development of robust treatments. I then appraise current post-stroke fatigue literature with the view of identifying post-stroke fatigue phenotypes.

Post-stroke fatigue and its correlation with family functioning in patients who have experienced a first episode of stroke

Objective

This study aimed to analyse the relevant factors that may affect post-stroke fatigue (PSF) in patients with stroke and further explore the correlation between family functioning and PSF.

Methods

Patients who had experienced a first episode of stroke and were admitted to the Department of Neurology of the First Affiliated Hospital of Wenzhou Medical University were rigorously screened. The general data and family functioning of the patients on admission were collected, and their family adaptation, partnership, growth, affection and resolve scores and their PSF on the 5th day of admission were collected using the fatigue severity scale (FSS). Multiple linear regression analysis was then utilized to explore the factors affecting PSF in patients with stroke.

Results

A total of 220 questionnaires were distributed, and 220 were returned, with 212 valid questionnaires and a valid return rate of 96.4%. These 212 patients had a family functioning score of 6.58 ± 2.00 and an FSS score of 36.62 ± 10.96. Spearman's correlation analysis showed negative correlations between the FSS scores and the adaptation, partnership, growth, affection, resolve and family functioning scores (r = -0.380, -0.505, -0.470, -0.303, -0.281 and -0.712, respectively; p < 0.001). Furthermore, multiple linear regression analysis showed that family functioning (β' = -0.516), marital status (β' = -0.244), household income (β' = -0.185), literacy (β' = -0.181) and activities of daily living (β' = -0.084) were influential factors for PSF in patients with stroke (p < 0.05).

Conclusion

There is a significant negative correlation between family functioning and PSF, suggesting that better family functioning may help mitigate the severity of post-stroke fatigue. Healthcare providers should identify interventions to help patients and families address fatigue, boost disease recovery, promote patients' physical and mental health and improve their quality of life.

Post-stroke fatigue severity is associated with executive dysfunction in chronic stroke

Following stroke, fatigue is highly prevalent and managing fatigue is consistently rated a key unmet need by stroke survivors and professionals. Domain-specific cognitive impairments have been associated with greater fatigue severity in earlier stages of stroke recovery, but it is unclear whether these associations hold in chronic (>2 years) stroke. The present cross-sectional observational study evaluates the relationship between domain-specific cognitive functioning and the severity of self-reported fatigue among chronic stroke survivors. Participants (N = 105; mean age = 72.92, 41.90% female; mean years post-stroke = 4.57) were assessed in domains of attention (Hearts Cancellation test), language (Boston Naming Test), episodic memory (Logical Memory Test), working memory (Digit Span Backwards task), and executive functioning (set-shifting: Trail Making Test, Part B), as part of the OX-CHRONIC study, a longitudinal stroke cohort. Fatigue was assessed using the Fatigue Severity Scale. In a multiple linear regression analysis inclusive of above cognitive domains, only poorer executive functioning was associated with increased fatigue severity. This provides insight into the cognitive impairment profile of post-stroke fatigue long-term after stroke, with executive functioning deficits as the key hallmark.

Exploring post-stroke fatigue from the perspective of stroke survivors: what strategies help? A qualitative study

PURPOSE

Post-stroke fatigue is a research priority for stroke survivors and health professionals but there is limited evidence to guide management. We aimed to explore (1) the experience of post-stroke fatigue from the perspective of stroke survivors and their caregivers and (2) fatigue management strategies that are used.

MATERIALS AND METHODS

This was a qualitative study using semi-structured interviews. People with self-reported post-stroke fatigue and caregivers were recruited using maximum variation sampling. Analysis was done via the framework approach.

RESULTS

We recruited 17 stroke survivors, nine male (53%), most under 65 years (n = 12, 76%), and greater than 1-year post-stroke (n = 16, 94%, range 10-months to 22-years). One-third of participants self-reported having aphasia (n = 5, 36%). We also recruited eight caregivers, most of whom were female (n = 7, 88%). We identified four themes: (1) fatigue is unexpected after stroke and symptoms vary; (2) the individual experience of fatigue is complex, influenced by multifactorial and biopsychosocial factors; (3) learning to adapt and accept fatigue; and (4) Strategies to manage fatigue and personal approaches to rest.

CONCLUSIONS

Post-stroke fatigue experience varies presenting cognitively, physically, and psychologically according to a complex interplay of biopsychosocial factors and personal triggers. Self-management strategies are individualised and include organisation, medications, lifestyle modifications, and peer support.

Evidence of aberrant anti-epstein-barr virus antibody response, though no viral reactivation, in people with post-stroke fatigue

BACKGROUND

Fatigue is a common complication of stroke that has a significant impact on quality of life. The biological mechanisms that underly post-stroke fatigue are currently unclear, however, reactivation of latent viruses and their impact on systemic immune function have been increasingly reported in other conditions where fatigue is a predominant symptom. Epstein-Barr virus (EBV) in particular has been associated with fatigue, including in long-COVID and myalgic encephalomyelitis/chronic fatigue syndrome, but has not yet been explored within the context of stroke.

AIMS

We performed an exploratory analysis to determine if there is evidence of a relationship between EBV reactivation and post-stroke fatigue.

METHODS

In a chronic ischemic stroke cohort (> 5 months post-stroke), we assayed circulating EBV by qPCR and measured the titres of anti-EBV antibodies by ELISA in patients with high fatigue (FACIT-F < 40) and low fatigue (FACIT-F > 41). Statistical analysis between two-groups were performed by t-test when normally distributed according to the Shapiro-Wilk test, by Mann-Whitney test when the data was not normally distributed, and by Fisher's exact test for categorical data.

RESULTS

We observed a similar incidence of viral reactivation between people with low versus high levels of post-stroke fatigue (5 of 22 participants (24%) versus 6 of 22 participants (27%)). Although the amount of circulating EBV was similar, we observed an altered circulating anti-EBV antibody profile in participants with high fatigue, with reduced IgM against the Viral Capsid Antigen (2.244 ± 0.926 vs. 3.334 ± 2.68; P = 0.031). Total IgM levels were not different between groups indicating this effect was specific to anti-EBV antibodies (3.23 × 105 ± 4.44 × 104 high fatigue versus 4.60 × 105 ± 9.28 × 104 low fatigue; P = 0.288).

CONCLUSIONS

These data indicate that EBV is not more prone to reactivation during chronic stroke recovery in those with post-stroke fatigue. However, the dysregulated antibody response to EBV may be suggestive of viral reactivation at an earlier stage after stroke.

Identification of core genes shared by ischemic stroke and myocardial infarction using an integrated approach

BACKGROUND

Both ischemic stroke (IS) and myocardial infarction (MI) are caused by vascular occlusion that results in ischemia. While there may be similarities in their mechanisms, the potential relationship between these 2 diseases has not been comprehensively analyzed. Therefore, this study explored the commonalities in the pathogenesis of IS and MI.

METHODS

Datasets for IS (GSE58294, GSE16561) and MI (GSE60993, GSE61144) were downloaded from the Gene Expression Omnibus database. Transcriptome data from each of the 4 datasets were analyzed using bioinformatics, and the differentially expressed genes (DEGs) shared between IS and MI were identified and subsequently visualized using a Venn diagram. A protein-protein interaction (PPI) network was constructed using the Interacting Gene Retrieval Tool database, and identification of key core genes was performed using CytoHubba. Gene Ontology (GO) term annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the shared DEGs were conducted using prediction and network analysis methods, and the functions of the hub genes were determined using Metascape.

RESULTS

The analysis revealed 116 and 1321 DEGs in the IS and MI datasets, respectively. Of the 75 DEGs shared between IS and MI, 56 were upregulated and 19 were downregulated. Furthermore, 15 core genes - S100a12, Hp, Clec4d, Cd163, Mmp9, Ormdl3, Il2rb, Orm1, Irak3, Tlr5, Lrg1, Clec4e, Clec5a, Mcemp1, and Ly96 - were identified. GO enrichment analysis of the DEGs showed that they were mainly involved in the biological functions of neutrophil degranulation, neutrophil activation during immune response, and cytokine secretion. KEGG analysis showed enrichment in pathways pertaining to Salmonella infection, Legionellosis, and inflammatory bowel disease. Finally, the core gene-transcription factor, gene-microRNA, and small-molecule relationships were predicted.

CONCLUSION

These core genes may provide a novel theoretical basis for the diagnosis and treatment of IS and MI.

The oxytocin receptor is essential for the protective effect of pair housing on post-stroke depression in mice

The beneficial effect of social interaction in mitigating the incidence of post-stroke depression (PSD) and ameliorating depressive symptoms has been consistently demonstrated through preclinical and clinical studies. However, the underlying relationship with oxytocin requires further investigation. In light of this, the present study aimed to explore the protective effect of pair housing on the development of PSD and the potential relationship with oxytocin receptors. The PSD model was induced by middle cerebral artery occlusion (MCAO) for 50 min, followed by 4-week isolated housing and restrained stress. Subsequently, each mouse in the pair-housing group (PH) was pair-housed with an isosexual healthy partner. Another group was continuously administrated fluoxetine (10 mg/Kg, i.p, once a day) for 3 weeks. To elucidate the potential role of oxytocin, we subjected pair-housed PSD mice to treatment with an oxytocin receptor (OXTR) antagonist (L368,889) (5 mg/Kg, i.p, once a day) for 3 weeks. At 31 to 32 days after MCAO, anxiety- and depressive-like behaviors were assessed using sucrose consumption, forced swim test, and tail-suspension test. The results showed that pair housing significantly improved post-stroke depression to an extent comparable to that of fluoxetine treatment. Furthermore, pair housing significantly decreased corticosterone in serum, increasing OXT mRNA expression in the hypothalamus. Treatment with L368,889 essentially reversed the effect of pair housing, with no discernible sex differences apart from changes in body weight. Pair housing increased hippocampal serotonin (5-HT), but treatment with L368,889 had no significant impact. Additionally, pair housing effectively reduced the number of reactive astrocytes and increased Nissl's body in the cortex and hippocampal CA3 regions. Correspondingly, treatment with L368,889 significantly reversed the changes in the Nissl's body and reactive astrocytes. Moreover, pair housing downregulated mRNA levels of TNF-α, IL-1β, and IL-6 in the cortex caused by PSD, which was also reversed by treatment with L368,889. In conclusion, pair housing protects against the development of PSD depending on OXT and OXTR in the brain, with no significant divergence based on sex. These findings provide valuable insights into the potential of social interaction and oxytocin as therapeutic targets for PSD. Further research into the underlying mechanisms of these effects may contribute to the development of novel treatments for PSD.

Association between sleep-disordered breathing and post-stroke fatigue in patients with ischemic stroke

OBJECTIVES

Post-stroke fatigue (PSF) is common and often disabling. Sleep-disordered breathing (SDB) is highly prevalent among stroke survivors and can cause fatigue. We explored the relationship between SDB and PSF over time.

MATERIALS AND METHODS

Ischemic stroke (IS) patients within the BASIC project were offered SDB screening with a well-validated cardiopulmonary sleep apnea test at 0, 3-, 6-, and 12-months post-stroke. The primary exposure was the respiratory event index (REI; sum of apneas plus hypopneas per hour). The primary outcome was PSF, measured by the SF-36 vitality scale. Associations between REI and PSF were evaluated using linear regression including time-by-REI interactions, allowing the effect of REI to vary over time.

RESULTS

Of the 411 IS patients who completed at least one outcome interview, 44 % were female, 61 % Mexican American (MA), 26 % non-Hispanic white, with a mean age of 64 (SD 10). Averaged across timepoints, REI was not associated with PSF. In a time-varying model, higher REI was associated with greater PSF at 3-months (β = 1.75, CI = 0.08, 3.43), but not at 6- or 12-months. Across timepoints, female sex, depressive symptoms, and comorbidity burden were associated with greater PSF, whereas MA ethnicity was associated with less PSF.

CONCLUSIONS

Higher REI was associated with modestly greater PSF in the early post-stroke period, but no association was observed at 6 months and beyond. SDB may be a modest modifiable risk factor for early PSF, but its treatment is unlikely to have a substantial impact on long-term PSF. MA ethnicity seems to be protective against PSF.

Improving physical movement during stroke rehabilitation: investigating associations between sleep measured by wearable actigraphy technology, fatigue, and key biomarkers

BACKGROUND

Sleep disturbance and fatigue are common in individuals undergoing inpatient rehabilitation following stroke. Understanding the relationships between sleep, fatigue, motor performance, and key biomarkers of inflammation and neuroplasticity could provide valuable insight into stroke recovery, possibly leading to personalized rehabilitation strategies. This study aimed to investigate the influence of sleep quality on motor function following stroke utilizing wearable technology to obtain objective sleep measurements. Additionally, we aimed to determine if there were relationships between sleep, fatigue, and motor function. Lastly, the study aimed to determine if salivary biomarkers of stress, inflammation, and neuroplasticity were associated with motor function or fatigue post-stroke.

METHODS

Eighteen individuals who experienced a stroke and were undergoing inpatient rehabilitation participated in a cross-sectional observational study. Following consent, participants completed questionnaires to assess sleep patterns, fatigue, and quality of life. Objective sleep was measured throughout one night using the wearable Philips Actiwatch. Upper limb motor performance was assessed on the following day and saliva was collected for biomarker analysis. Correlation analyses were performed to assess the relationships between variables.

RESULTS

Participants reported poor sleep quality, frequent awakenings, and difficulties falling asleep following stroke. We identified a significant negative relationship between fatigue severity and both sleep quality (r=-0.539, p = 0.021) and participants experience of awakening from sleep (r=-0.656, p = 0.003). A significant positive relationship was found between grip strength on the non-hemiplegic limb and salivary gene expression of Brain-derived Neurotrophic Factor (r = 0.606, p = 0.028), as well as a significant negative relationship between grip strength on the hemiplegic side and salivary gene expression of C-reactive Protein (r=-0.556, p = 0.048).

CONCLUSION

The findings of this study emphasize the importance of considering sleep quality, fatigue, and biomarkers in stroke rehabilitation to optimize recovery and that interventions may need to be tailored to the individual. Future longitudinal studies are required to explore these relationships over time. Integrating wearable technology for sleep and biomarker analysis can enhance monitoring and prediction of outcomes following stroke, ultimately improving rehabilitation strategies and patient outcomes.

Pathophysiology, Assessment, and Management of Post-Stroke Cognitive Impairment, Depression, and Fatigue

Post-stroke cognitive impairment, depression, and fatigue are common, persistent, and disabling. This review summarizes current knowledge on the pathophysiology, assessment, and management of these debilitating neuropsychiatric sequelae of stroke. We briefly review evolving knowledge on the neural mechanisms and risk factors for each condition. We describe patient-reported outcome measures and clinician rating techniques that can be used to assist in screening and comprehensive assessment. We then discuss behavioral and pharmacologic management strategies. Heterogeneity of stroke remains a challenge in management and new research is still needed to optimize and personalize treatments for stroke survivors.

A Machine Learning Approach to Predict Post-stroke Fatigue. The Nor-COAST study

OBJECTIVE

This study aimed to predict fatigue 18 months post-stroke by utilizing comprehensive data from the acute and sub-acute phases after stroke in a machine-learning set-up.

DESIGN

A prospective multicenter cohort-study with 18-month follow-up.

SETTING

Outpatient clinics at 3 university hospitals and 2 local hospitals.

PARTICIPANTS

474 participants with the diagnosis of acute stroke (mean ± SD age; 70.5 (11.3), 59% male; N=474).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

The primary outcome, fatigue at 18 months, was assessed using the Fatigue Severity Scale (FSS-7). FSS-7≥5 was defined as fatigue. In total, 45 prediction variables were collected, at initial hospital-stay and 3-month post-stroke.

RESULTS

The best performing model, random forest, predicted 69% of all subjects with fatigue correctly with a sensitivity of 0.69 (95% CI: 0.50, 0.86), a specificity of 0.74 (95% CI: 0.66, 0.83), and an Area under the Receiver Operator Characteristic curve of 0.79 (95% CI: 0.69, 0.87) in new unseen data. The proportion of subjects predicted to suffer from fatigue, who truly suffered from fatigue at 18-months was estimated to 0.41 (95% CI: 0.26, 0.57). The proportion of subjects predicted to be free from fatigue who truly did not have fatigue at 18-months was estimated to 0.90 (95% CI: 0.83, 0.96).

CONCLUSIONS

Our findings indicate that the model has satisfactory ability to predict fatigue in the chronic phase post-stroke and may be applicable in clinical settings.

Observer-reported cognitive decline in out-of-hospital cardiac arrest survivors and its association with long-term survivor and relative outcomes

AIM

Long-term cognitive decline after out-of-hospital cardiac arrest (OHCA) is still poorly understood. This study describes long-term observer-reported cognitive decline among Danish OHCA survivors, including differences in years since the event, and investigates characteristics and self-reported outcomes associated with observer-reported cognitive decline.

METHODS

Adults who survived an OHCA from 2016 to 2019, and their relatives, completed the national DANish Cardiac Arrest Survivorship survey. Relatives completed the Informant Questionnaire on Cognitive Decline in the Elderly, Cardiac Arrest version (IQCODE-CA), the Hospital Anxiety and Depression Scale (HADS) and the World Health Organisation-Five Well-being index; and survivors completed the Two Simple Questions (everyday activities and mental recovery), the Modified Fatigue Impact Scale, HADS, and the Short World Health Organisation Disability Assessment Schedule 2.0. Potential associations between survivor characteristics and the IQCODE-CA were investigated using a multivariable logistic regression model. Self-reported outcomes among survivors and relatives, and the association with IQCODE-CA scores were investigated using separate logistic regression models.

RESULTS

Total median IQCODE-CA score was 3.04 (IQR: 3.00-3.27), with 47% having possible cognitive decline (score ≥ 3.04), consistent across time groups. Increasing age (OR 0.98, 95% CI: 0.97-0.99) and worse self-reported mental and physical outcomes for survivors and relatives, except 'everyday activities' were significantly associated with possible cognitive decline among survivors.

CONCLUSIONS

Nearly half of OHCA survivors may suffer long-term cognitive decline. Worse self-reported mental and physical outcomes among survivors and their relatives are associated with potential cognitive decline emphasising the need for post-OHCA care to include systematic neurocognitive assessment, tailored support and effective rehabilitation.

Relationship between glycated hemoglobin levels at admission and chronic post-stroke fatigue in patients with acute ischemic stroke

BACKGROUND

Chronic Post-Stroke Fatigue (PSF) is a common and persistent complications among ischemic stroke survivors. The serum glycated hemoglobin (HbA1c) level, as it is known has emerged as a critical risk factor for Acute Ischemic Stroke (AIS) and post-stroke cognitive and emotional impairment. However, no studies have been conducted on the link between HbA1c and PSF. Therefore, this study aims to estimate the relationship between HbA1c and PSF in the chronic phase.

METHODS

A longitudinal study was conducted on 559 patients diagnosed with their first AIS episode and admitted to Suining Central Hospital within three days after onset. All patients were examined for serum HbA1c, blood glucose levels and routine blood biochemical indicators at admission. The Fatigue Severity Scale (FSS) was employed to assess fatigue symptoms at six months post-stroke. Multivariate logistic regression and smooth curve fitting were used to analyze the relationship between admission HbA1c, blood glucose levels, discharge blood glucose and PSF, and the predictive value of HbA1c on PSF was assessed using a segmented linear regression model.

RESULTS

189(33.8 %)of the 559 patients included in the study, reported PSF at six-month follow-up. Compared with the non-PSF group, the PSF group displayed significantly higher levels of HbA1c (7.8 ± 3.0 vs 6.5 ± 2.0 %, P < 0.001), admission blood glucose (7.8 ± 3.8 vs 7.1 ± 3.5 mmol/L, P = 0.041), and discharge blood glucose (6.3 ± 1.6 vs 5.8 ± 1.2 mmol/L, P < 0.001). The dose-response relationship among admission HbA1c, blood glucose, discharge blood glucose and PSF showed that HbA1c level is positively and non-linearly related to the risk of PSF. A linear positive correlation is noted between PSF and discharge blood glucose levels, while no significant correlation was observed for the blood glucose levels upon admission.

CONCLUSIONS

Higher HbA1c levels at admission were independently associated with the risk of chronic PSF, the correlation between blood glucose and PSF showed significant variability, HbA1c may serve as a more stable risk factor in predicting the occurrence of chronic PSF and long-term active glycemic management may have a favorable impact on chronic PSF after AIS.

Validation of the Turkish version of the Neurological Fatigue Index for Stroke

INTRODUCTION

Post-stroke fatigue is an often overlooked problem that hinders recovery. Therefore, stroke patients should be evaluated for fatigue during the recovery period. This study aimed to adapt the Neurological Fatigue Index for Stroke (NFI-Stroke) into the Turkish language.

METHODS

This methodological study was carried out on 110 stroke patients admitted to a university hospital in Istanbul. In addition to the NFI-Stroke, Functional Independence Measure, National Institutes of Health Stroke Scale, modified-Rankin Scale, Fatigue Severity-Scale, and Stroke Self Efficacy Questionnaire were used to collect data.

RESULTS

Since the linguistic validity study of the scale has already been carried out, only psychometric properties were evaluated. The items in the scale were grouped under two factors. The Cronbach`s alpha coefficient was found to be 0.96 for the physical sub-dimension and 0.84 for the cognitive sub-dimension. Item-total correlation coefficients were found between 0.74-0.91 for the physical sub-dimension, and 0.82-0.91 for the cognitive sub-dimension. The test-retest evaluation confirmed the consistency of the responses to the scale against time. The scale was correlated with other scales used in the study as expected.

CONCLUSIONS

The NFI-Stroke will be useful in clinical practice in assessment of fatigue, which may affect the adaptation of patients to rehabilitation.

A roadmap for research in post-stroke fatigue: Consensus-based core recommendations from the third Stroke Recovery and Rehabilitation Roundtable

RATIONALE

Fatigue affects almost half of all people living with stroke. Stroke survivors rank understanding fatigue and how to reduce it as one of the highest research priorities.

METHODS

We convened an interdisciplinary, international group of clinical and pre-clinical researchers and lived experience experts. We identified four priority areas: (1) best measurement tools for research, (2) clinical identification of fatigue and potentially modifiable causes, (3) promising interventions and recommendations for future trials, and (4) possible biological mechanisms of fatigue. Cross-cutting themes were aphasia and the voice of people with lived experience. Working parties were formed and structured consensus building processes were followed.

RESULTS

We present 20 recommendations covering outcome measures for research, development, and testing of new interventions and priority areas for future research on the biology of post-stroke fatigue. We developed and recommend the use of the Stroke Fatigue Clinical Assessment Tool.

CONCLUSIONS

By synthesizing current knowledge in post-stroke fatigue across clinical and pre-clinical fields, our work provides a roadmap for future research into post-stroke fatigue.

Mechanisms of Post-Stroke Fatigue: A Follow-Up From the Third Stroke Recovery and Rehabilitation Roundtable

BACKGROUND

Post-stroke fatigue (PSF) is a significant and highly prevalent symptom, whose mechanisms are poorly understood. The third Stroke Recovery and Rehabilitation Roundtable paper on PSF focussed primarily on defining and measuring PSF while mechanisms were briefly discussed. This companion paper to the main paper is aimed at elaborating possible mechanisms of PSF.

METHODS

This paper reviews the available evidence that potentially explains the pathophysiology of PSF and draws parallels from fatigue literature in other conditions. We start by proposing a case for phenotyping PSF based on structural, functional, and behavioral characteristics of PSF. This is followed by discussion of a potentially significant role of early inflammation in the development of fatigue, specifically the impact of low-grade inflammation and its long-term systemic effects resulting in PSF. Of the many neurotransmitter systems in the brain, the dopaminergic systems have the most evidence for a role in PSF, along with a role in sensorimotor processing. Sensorimotor neural network dynamics are compromised as highlighted by evidence from both neurostimulation and neuromodulation studies. The double-edged sword effect of exercise on PSF provides further insight into how PSF might emerge and the importance of carefully titrating interventional paradigms.

CONCLUSION

The paper concludes by synthesizing the presented evidence into a unifying model of fatigue which distinguishes between factors that pre-dispose, precipitate, and perpetuate PSF. This framework will help guide new research into the biological mechanisms of PSF which is a necessary prerequisite for developing treatments to mitigate the debilitating effects of post-stroke fatigue.

[Comorbid anxiety disorders in patients with neurological pathology: current state of the problem and the role of etifoxine in treatment strategy]

The article presents theses of the resolution of the Interdisciplinary Council of Experts in Psychiatry and Neurology (Moscow, 2024) on the issue of comorbid anxiety disorders (AD) in patients with neurological pathologies. The authors highlight the high prevalence of comorbid ADs and their significant negative impact on the course of underlying diseases, such as epilepsy, pain syndromes and post-stroke conditions. Modern approaches to the diagnosis and treatment of ADs in this group of patients are discussed. Special attention is given to the role of etifoxine as an effective anxiolytic in the comprehensive therapy of ADs. Etifoxine, due to its dual mechanism of action on GABA receptors, demonstrates high efficacy in reducing anxiety and has neuroprotective, neurotrophic, neuroplastic, analgesic, and anti-inflammatory properties, making it an important tool in the treatment of comorbid ADs in patients with neurological pathologies. The article also reviews recently published data confirming its efficacy and favourable safety profile compared to traditional benzodiazepines and other anxiolytic drugs.

A roadmap for research in post-stroke fatigue: Consensus-based core recommendations from the third Stroke Recovery and Rehabilitation Roundtable

RATIONALE

Fatigue affects almost half of all people living with stroke. Stroke survivors rank understanding fatigue and how to reduce it as one of the highest research priorities.

METHODS

We convened an interdisciplinary, international group of clinical and pre-clinical researchers and lived experience experts. We identified four priority areas: (1) best measurement tools for research, (2) clinical identification of fatigue and potentially modifiable causes, (3) promising interventions and recommendations for future trials, and (4) possible biological mechanisms of fatigue. Cross-cutting themes were aphasia and the voice of people with lived experience. Working parties were formed and structured consensus building processes were followed.

RESULTS

We present 20 recommendations covering outcome measures for research, development, and testing of new interventions and priority areas for future research on the biology of post-stroke fatigue. We developed and recommend the use of the Stroke Fatigue Clinical Assessment Tool.

CONCLUSIONS

By synthesizing current knowledge in post-stroke fatigue across clinical and pre-clinical fields, our work provides a roadmap for future research into post-stroke fatigue.

Validating the Fatigue Scale for Motor and Cognitive Function (FSMC) in chronic stroke

BACKGROUND

Post-stroke fatigue can manifest as both physical and mental fatigue. The Fatigue Scale for Motor and Cognitive Functions (FSMC) evaluates fatigue on the motor and cognitive domains separately, however, the psychometric properties of this measure in stroke have not been reported.

OBJECTIVE

To determine the internal consistency, test-retest reliability, and concurrent validity of the FSMC in chronic stroke.

METHODS

Thirty-four participants with chronic stroke (55.26±12.27 years of age; 59.53±89.21 months post-stroke) completed the FSMC on two separate visits. Internal consistency and reliability of the FSMC were examined using Cronbach's alpha and two-way mixed effects intraclass correlation coefficients (ICC), respectively. Correlation between the FSMC and the Fatigue Severity Scale and Visual Analog Scale-Fatigue was used to assess concurrent validity.

RESULTS

Internal consistency was excellent (Cronbach's alpha > 0.9) and reliability was moderate to good (ICC = 0.72-0.81) for all FSMC scores. The FSMC demonstrated moderate to good concurrent validity with the Fatigue Severity Scale (ρ= 0.66-0.72) but only fair concurrent validity with the Visual Analog Scale-Fatigue (ρ= 0.37-0.44).

CONCLUSION

The FSMC is a valid and reliable measure of post-stroke fatigue and may be a useful tool to examine physical fatigue and cognitive fatigue in chronic stroke.

Post-stroke fatigue: a review of development, prevalence, predisposing factors, measurements, and treatments

Background

Post-stroke fatigue (PSF) is a ubiquitous and overwhelming symptom for most stroke survivors. However, there are no effective management strategies for PSF, which is partly due to our limited understanding.

Objective

In this paper, we review the development, prevalence, predisposing factors, measurements, and treatments of PSF.

Results

PSF is an independent symptom after stroke, with a prevalence ranging from 42 to 53%, which depends on the selection of measurement tools and stroke characteristics. It is affected by biological, physical, and psychological factors, among which inflammation may play a key role.

Conclusion

Numerous but non-specific evaluation measurement tools limit the management of PSF. In clinical practice, it may be beneficial to identify PSF by combining scales and objective indexes, such as walking tests and electromyographic examinations. There are no evidence-based interventions to improve PSF. However, increasing evidence suggests that transcranial direct-current stimulation and mindfulness-based interventions may become promising treatments. Further studies are urgently needed to better understand the etiology of PSF, thereby providing the basis for developing new measurement tools and targeted treatments.

Assessment of post-COVID-19 fatigue among female survivors 2 years after hospital discharge: a nested case-control study

BACKGROUND

Fatigue is a common symptom of long COVID syndrome. Compared to male survivors, females have a higher incidence of post-COVID fatigue. Therefore, long-term follow-up is necessary to understand which groups of females are more vulnerable to post-COVID fatigue.

METHODS

This is a nested case-control study of female COVID-19 survivors who were discharged from two designated hospitals in Wuhan, China in 2020, and received 2-year follow-up from March 1 to April 6, 2022. All patients completed the Checklist Individual Strength-subscale subjective fatigue (CIS-fatigue), a chronic obstructive pulmonary disease (COPD) assessment test (CAT), and the Hospital Anxiety and Depression Scale (HADS; including the HADS-Anxiety [HADS-A] and the HADS-Depression [HADS-D]). Individuals with CIS-fatigue scores of 27 or higher were classified as cases. The risk factors for fatigue was analysed with multivariable logistic regression analysis.

RESULTS

A total of 899 female COVID-19 survivors were enrolled for analysis, including 47 cases and 852 controls. Compared with controls, cases had higher CAT, HADS-A and HADS-D scores, and showed a higher prevalence of symptoms, including anxiety (cases vs. controls, 44.7% vs. 4.0%, p < 0.001), chest tightness (21.2% vs. 2.3%, p < 0.001), dyspnoea (19.1% vs. 0.8%, p < 0.001) and so on. In multivariable logistic regression analysis, age (OR, 1.03; 95% CI, 1.01-1.06; p = 0.02) and cerebrovascular disease (OR, 11.32; 95% CI, 2.87-43.00; p < 0.001) were risk factors for fatigue. Fatigue had a statistically significant moderate correlation with depression (r = 0.44, p < 0.001), but not with CAT ≥ 10.

CONCLUSION

Female COVID-19 patients who had cerebrovascular disease and older age have higher risk of fatigue. Patients with fatigue have higher CAT scores, and are more likely to have concurrent depression.

Post-Stroke Neuropsychiatric Complications: Types, Pathogenesis, and Therapeutic Intervention

Almost all stroke survivors suffer physical disabilities and neuropsychiatric disturbances, which can be briefly divided into post-stroke neurological diseases and post-stroke psychiatric disorders. The former type mainly includes post-stroke pain, post-stroke epilepsy, and post-stroke dementia while the latter one includes post-stroke depression, post-stroke anxiety, post-stroke apathy and post-stroke fatigue. Multiple risk factors are related to these post-stroke neuropsychiatric complications, such as age, gender, lifestyle, stroke type, medication, lesion location, and comorbidities. Recent studies have revealed several critical mechanisms underlying these complications, namely inflammatory response, dysregulation of the hypothalamic pituitary adrenal axis, cholinergic dysfunction, reduced level of 5-hydroxytryptamine, glutamate-mediated excitotoxicity and mitochondrial dysfunction. Moreover, clinical efforts have successfully given birth to many practical pharmaceutic strategies, such as anti-inflammatory medications, acetylcholinesterase inhibitors, and selective serotonin reuptake inhibitors, as well as diverse rehabilitative modalities to help patients physically and mentally. However, the efficacy of these interventions is still under debate. Further investigations into these post-stroke neuropsychiatric complications, from both basic and clinical perspectives, are urgent for the development of effective treatment strategies.

Post-Stroke Brain Health Monitoring and Optimization: A Narrative Review

Significant advancements have been made in recent years in the acute treatment and secondary prevention of stroke. However, a large proportion of stroke survivors will go on to have enduring physical, cognitive, and psychological disabilities from suboptimal post-stroke brain health. Impaired brain health following stroke thus warrants increased attention from clinicians and researchers alike. In this narrative review based on an open timeframe search of the PubMed, Scopus, and Web of Science databases, we define post-stroke brain health and appraise the body of research focused on modifiable vascular, lifestyle, and psychosocial factors for optimizing post-stroke brain health. In addition, we make clinical recommendations for the monitoring and management of post-stroke brain health at major post-stroke transition points centered on four key intertwined domains: cognition, psychosocial health, physical functioning, and global vascular health. Finally, we discuss potential future work in the field of post-stroke brain health, including the use of remote monitoring and interventions, neuromodulation, multi-morbidity interventions, enriched environments, and the need to address inequities in post-stroke brain health. As post-stroke brain health is a relatively new, rapidly evolving, and broad clinical and research field, this narrative review aims to identify and summarize the evidence base to help clinicians and researchers tailor their own approach to integrating post-stroke brain health into their practices.

Post-stroke Everything

PURPOSE OF REVIEW

This review aims at providing updates on selected post-stroke complications. We examined recent advances in diagnosing and treating the following post-stroke complications: cognitive impairment, epilepsy, depression, fatigue, tremors, dysphagia, and pain.

RECENT FINDINGS

Advances in understanding the mechanisms of post-stroke complications, in general, are needed despite advances made in understanding, treating, and preventing these complications. There are growing progresses in integrating new tools to diagnose post-stroke cognitive impairment. The potential role of acute stroke reperfusion treatment in post-stroke epilepsy and its impact on other stroke complications is getting more transparent. Post-stroke depression remains underestimated and new tools to diagnose depression after stroke are being developed. New promising pharmacological approaches to treating post-stroke pain are emerging. Tremors related to stroke are poorly understood and under-evaluated, while treatment towards post-stroke dysphagia has benefited from new non-pharmacological to pharmacological approaches.

CONCLUSIONS

An integrative approach to stroke complications and collaborations between providers across specialties are more likely to improve stroke outcomes.

Predicting the relationship between anxiety and health-related quality of life in post-stroke patients: The role of sleep duration

OBJECTIVES

Sleep and psychological disorders are common complaints in stroke survivors. The effectiveness of sleep duration in post-stroke on mental well-being and health outcomes has been reported recently. This study aimed to investigate the mediating effect of sleep duration on the relationship between anxiety and health-related quality of life in Chinese post-stroke; MATERIALS AND METHODS: We conducted a quantitative, cross-sectional study with participants recruited through a multistage, stratified, probability proportional to size sampling method. Anxiety, health-related quality of life, and sleep duration were measured by Zung Self-rating Anxiety Scale, World Health Organization Quality of Life Questionnaire, and a self-administered, structured questionnaire. A multiple linear regression analysis was conducted to identify the association between anxiety, sleep duration, and quality of life. The direct and indirect effects of sleep duration on health-related quality of life was assessed using the bootstrap method via Model 4 (parallel mediation) of SPSS PROCESS macro; RESULTS: A total of 856 post-stroke patients participated in the study, and incidence of anxiety symptom amongst post-stroke was 33.53%. Sleep duration mainly plays partial mediating roles in the relationship between mild-to-moderate anxiety and quality of life in physical, psychological, and environment domains, with sleep duration of 7-8h playing a major role; CONCLUSIONS: A significant relationship among anxiety, sleep duration, and quality of life in post-stroke was found in this study. The sleep duration partially mediated the association between anxiety and quality of life. Suitable prevention methods and early interventions for sleep duration may improve the quality of life for post-stroke anxiety.

The impact of post-stroke fatigue on work and other everyday life activities for the working age population - a registry-based cohort study

INTRODUCTION

Life after stroke is a comprehensive area that involves engagement in meaningful everyday activities, including work, and can be adversely affected by post-stroke fatigue. This study investigates post-stroke fatigue, its development over time, and its impact on return to work and other everyday life activities. In addition, we investigated whether post-stroke fatigue could predict functioning in everyday life activities one year after stroke.

MATERIAL AND METHODS

This prospective registry-based study includes 2850 working age (18 - 63 years) patients registered in the Swedish Stroke Register (Riksstroke) during year 2017 and 2018. Post-stroke fatigue and everyday activities were analyzed 3- and 12-months post-stroke.

RESULTS

The mean age of the included participants was 54 years and the majority, 65%, were men. Three months post-stroke, 43% self-reported fatigue, at 12-months the proportion increased to 48%. About 90% of the patients were independent in basic ADL at 3-month. Dependence in complex activities one year post-stroke was significantly associated with fatigue. Not experiencing fatigue one year after stroke could predict positive functioning in everyday activities, increasing the chance of returning to work (OR = 3.7) and pre-stroke life and everyday activities (OR = 5.7).

CONCLUSION

Post-stroke fatigue is a common persistent disability that negatively impacts complex activities; therefore, fatigue needs to be acknowledged and addressed long term after discharge.

Association of post-stroke fatigue with physical activity and physical fitness: A systematic review and meta-analysis

BACKGROUND

It has been hypothesized that post-stroke fatigue (PSF) is associated with reduced physical activity (PA) and impaired physical fitness (fitness). Understanding associations between PSF and PA, and/or fitness could help guide the development of targeted exercise interventions to treat PSF.

AIMS

Our systematic review and meta-analysis aimed to investigate PSF's associations with PA and fitness.

SUMMARY OF REVIEW

Following a registered protocol, we included studies with cross-sectional or prospective observational designs, published in English or a Scandinavian language, which reported an association of PSF with PA and/or fitness in adult stroke survivors. We searched MEDLINE, Embase, AMED, CINAHL, PsycINFO, ClinicalTrials.gov, and World Health Organization's International Clinical Trials Registry Platform from inception to November 30, 2022. Risk of bias was assessed using Quality in Prognosis Studies. Thirty-two unique studies (total n = 4721 participants, 55% male), and three study protocols were included. We used random-effects meta-analysis to pool data for PA and fitness outcomes, and vote-counting of direction of association to synthesize data that could not be meta-analyzed. We found moderate-certainty evidence of a weak association between higher PSF and impaired fitness (meta r = -0.24; 95% confidence interval (CI) = -0.33, -0.15; n = 905, 7 studies), and very low-certainty evidence of no association between PSF and PA (meta r = -0.09; 95% CI = -0.34, 0.161; n = 430, 3 studies). Vote-counting showed a higher proportion of studies with associations between higher PSF and impaired fitness (pˆ = 0.83; 95% CI = 0.44, 0.97; p = 0.22, n = 298, 6 studies), and with associations between higher PSF and lower PA (pˆ = 0.75; 95% CI = 0.51, 0.90; p = 0.08, n = 2566, 16 studies). Very low- to moderate-certainty evidence reflects small study sample sizes, high risk of bias, and inconsistent results.

CONCLUSIONS

The meta-analysis showed moderate-certainty evidence of an association between higher PSF and impaired fitness. These results indicate that fitness might protect against PSF. Larger prospective studies and randomized controlled trials evaluating the effect of exercise on PSF are needed to confirm these findings.

Awareness and support for post-stroke fatigue among medical professionals in the recovery phase rehabilitation ward

Sato M, Hyakuta T. Awareness and support for post-stroke fatigue among medical professionals in the recovery phase rehabilitation ward. Jpn J Compr Rehabil Sci 2023; 14: 39-48.

Objective

To clarify the level of awareness of and support for post-stroke fatigue among medical professionals working in recovery phase rehabilitation wards.

Methods

We conducted a questionnaire survey targeting all medical professionals (physicians, nurses, physical therapists, occupational therapists, and speech therapists) working in recovery phase rehabilitation wards of three facilities to evaluate their awareness of post-stroke fatigue and the support they were offering to address this. Quantitative data were subjected to statistical analysis and free description data were subjected to content analysis.

Results

Of the 130 participants, we obtained responses from 94 (collection rate, 72.3%; valid response rate, 100%). Those who felt that post-stroke patients are always tired or tire easily comprised 63.8%. Those who acknowledged the importance of post-stroke fatigue as a problem and that it is an issue that must be addressed comprised 70.2% and 73.4%, respectively. Issues emerging due to post-stroke fatigue were extracted as follows: "Difficulty continuing with rehabilitation," "Decreased drive," "Difficulty with emotional control/depression," "Fewer interactions with others," and "Loss of goals." Support for post-stroke fatigue was offered by 57.4% of medical professionals, most commonly as individual support such as "Ensure rest." The effects of support were described as "Cannot say either way" (44.4%), with 3.7% noting that they were not very effective. Awareness and support rates among therapists were significantly higher than those among nurses.

Conclusions

Post-stroke fatigue is acknowledged by medical professionals as a critical issue that negatively influences the patient's physical, emotional, and daily living functions. Unfortunately, effective support is not currently being offered, demonstrating the need for the development of appropriate interventions.

Is Cardiorespiratory Fitness Independently Associated with Fatigue in Patients with Transient Ischemic Attack or Minor Stroke?

Fatigue is a common complaint and a disabling symptom among patients following transient ischemic attack (TIA) or minor stroke. In patients with stroke, decreased cardiorespiratory fitness (CRF) is believed to be related to increased severity of post-stroke fatigue (PSF). However, this association between PSF and CRF in patients with TIA or minor stroke has been less investigated, and currently there is no proven treatment for PSF. We aimed to determine the association between PSF and CRF in patients with TIA or minor stroke and to find out whether this association was distorted by confounders. A cross-sectional association study was conducted among a total of 119 patients with TIA or minor stroke. PSF was measured by the Fatigue Severity Scale (FSS) and CRF was quantified by maximal exercise capacity (V̇O2max). The FSS showed a significant association with V̇O2max (ß = −0.061, SE: 0.022; p = 0.007). This association was confounded by anxiety (ß = −0.044, SE: 0.020; p = 0.028) and depression (ß = −0.030, SE: 0.022; p = 0.177) as measured by the subscales of the Hospital Anxiety and Depression Scale (HADS). After controlling for HADS scores on depression and anxiety, the univariate relationship between V̇O2max and FSS was no longer significant. These results suggest that the association between PSF and CRF in patients with TIA or minor stroke is weak and significantly confounded by the factors of depression and anxiety.

Factors Associated With Fatigue in People With Spinal Cord Injury: A Systematic Review and Meta-analysis

OBJECTIVE

To investigate the association between fatigue and clinical and demographic variables in people with spinal cord injury (SCI).

DATA SOURCES

Five databases (MEDLINE, Physiotherapy Evidence Database, Cochrane, Google Scholar, Cumulative Index to Nursing and Allied Health) were searched up to November 2021.

STUDY SELECTION

Observational studies that reported the association between fatigue and clinical and demographic variables in English or Spanish were eligible. Reviews, qualitative research studies, and nonoriginal articles were excluded. Twenty-three of the 782 identified studies met the inclusion criteria for the meta-analysis.

DATA EXTRACTION

Two researchers independently extracted the data. The strength of the association between each factor and fatigue was determined by the effect size. When the results of the effect size were expressed with different statistics, the correlation coefficient was the preferred estimation. The risk of bias was assessed using the Appraisal Tool for Cross-Sectional Studies and the Newcastle-Ottawa Scale.

DATA SUMMARY

A pooled analysis of the associations between fatigue and 17 factors was performed. A direct association was found between fatigue and 9 factors (sorted by effect size): anxiety (r=0.57; 95% CI, 0.29-0.75), stress (r=0.54; 95% confidence interval [CI], 0.26-0.74), depression (r=0.47; 95% CI, 0.44-0.50), pain (r=0.34; 95% CI, 0.16-0.50), analgesic medication (r=0.32; 95% CI, 0.28-0.36), assistive devices (r=0.23; 95% CI, 0.17-0.29), lesion level (r=0.15; 95% CI, 0.07-0.23), incomplete SCI (r=0.13; 95% CI, 0.05-0.22), and medication (r=0.12; 95% CI, 0.01-0.23). An inverse association was found with 3 factors (sorted by effect size): self-efficacy (r=-0.63; 95% CI, -0.81 to -0.35), participation (r=-0.32; 95% CI, -0.58 to -0.001), and physical activity (r=-0.17; 95% CI, -0.28 to -0.05). No association was found with age, sex, educational level, time since injury, and spasticity.

CONCLUSIONS

Several factors were associated with fatigue in people with SCI, with those related to mental health showing the strongest associations. These results should be interpreted with caution because of the high heterogeneity observed in some factors.

Is the Pandemic Wearing Us Out? A Cross-Sectional Study of the Prevalence of Fatigue in Adult Twins without Previous SARS-CoV-2 Infection

During the pandemic, mental health was not only impaired in people after a SARS-CoV-2 infection, but also in people without previous infection. This is the first study on twins without prior SARS-CoV-2 infection to estimate the influence of genetic components and shared as well as individual environments on pandemic-associated fatigue. The study sample included 55 monozygotic and 45 dizygotic twin pairs. A total of 34.5% reported an increase in fatigue since the pandemic. A significant correlation was shown between the responses within monozygotic (χ2[1] = 11.14, p = 0.001) and dizygotic pairs (χ2[1] = 18.72, p < 0.001). In all pandemic-associated fatigue dimensions, individual environment (ranging from e2 = 0.64 to e2 = 0.84) and heritability (ranging from h2 = 0.32 to h2 = 1.04) seem to have the highest impact. The number of comorbidities significantly correlated with physical fatigue (Spearman’s ρ = 0.232, p < 0.001) and psychological impairment due to pandemic measures with the total fatigue score (Spearman’s ρ = 0.243, p < 0.001). However, calculated ANCOVAs with these significant correlations as covariates showed no significant influence on the mean values of the respective fatigue dimensions. Susceptibility to pandemic-associated fatigue may be genetically and environmentally determined, while intensity is also influenced by individual components. The prevalence of fatigue is high even in individuals without prior SARS-CoV-2 infection. Future mental health prevention and intervention programs should be implemented to alleviate the impact of the pandemic on the global population.

Fatigue 7 years post-stroke: Predictors and correlated features

Background

Post‐stroke fatigue (PSF) is common with great impact on quality of life. We explored predictive and cross‐sectionally correlated features in the long term after ischemic stroke.

Methods

This study comprises 430 participants of the prospective Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS), aged 18–69 years at index stroke. Information on acute stroke severity and cardiovascular risk factors was collected at index stroke. After 7 years, PSF was assessed by the Daily Fatigue Impact Scale (D‐FIS). Cognitive, neurological, and functional outcomes, and symptoms of depression and anxiety, pain, insomnia, and physical activity were also assessed. Associations between baseline variables and PSF were analyzed by ordinal regression. Correlations between PSF and cross‐sectionally assessed variables, and between PSF and baseline variables, were analyzed with Spearman's or point‐biserial correlation for the whole sample and in sex‐stratified analyses.

Results

At 7 years post‐stroke, 80% of the participants reported some impact of fatigue. Female sex and stroke severity were independently associated with PSF, whereas no associations were detected with baseline cardiovascular risk factors. In cross‐sectional analyses at 7 years, we found correlations between PSF and poor functional, neurological, and cognitive outcomes, as well as depressive symptoms, anxiety, insomnia, pain, and low physical activity (p < .001 throughout). The correlation with insomnia was stronger in women than in men (two‐way ANOVA interaction test, p = .03).

Conclusions

Our findings confirm that PSF is common in the long term after ischemic stroke and show a complex interplay with sex and several other outcomes. Future studies should address causal relationships and interventions towards fatigue and coexisting features.

The Impact of Online Learning System on Students Affected with Stroke Disease

Stroke, also known as a cerebrovascular accident, is a medical emergency that causes temporary or permanent behavioral dysfunction in people. Sleep deprivation affects our brains in a variety of ways. The advantages of sleep much justify the risks of not having enough sleep. Sleep deprivation (SD) includes a variety of factors, including prolonged awake. Neuroimaging investigates SD's impact on attention, working memory, mood, and hippocampal learning. We analyzed how this data enriches our mechanistic understanding of these alterations and the clinical illnesses linked with sleep disruption. We have used Cronbach's alpha to test the reliability of a scale, so we then have 19 individual attributes responding to 174 participants via survey. The evaluated result shows the reliability statistics; the value for Cronbach's alpha is .962, which is very excellent as it reaches 1. So, there is very strong reliability. If the value falls under .6, we look back to the mean and standard deviation table and remove the attribute with low values for mean or standard deviation and try the remaining attributes. Cronbach's alpha tells us which attribute or item to delete to increase the reliability, and we also have analyzed the correlation among the class students while watching the same video lecture. We have collected data for at least ten students watching the same video using a webcam. Once the data is collected, we then have applied some correlation techniques to determine the class students' behavior towards the same video lecture. This way, we can see the overall behavior of the class upon a specific video lecture. The study further reveals that subjective happiness is influenced by its efficiency, entertainment value, and effectiveness. Does the research offer an original emphasis on analyzing how does lack of sleep affect our brains? Sleep loss frameworks are minimal compared to the benefits of sleep.

Sleep and Stroke: Opening Our Eyes to Current Knowledge of a Key Relationship

PURPOSE OF REVIEW

To elucidate the interconnection between sleep and stroke.

RECENT FINDINGS

Growing data support a bidirectional relationship between stroke and sleep. In particular, there is strong evidence that sleep-disordered breathing plays a pivotal role as risk factor and concur to worsening functional outcome. Conversely, for others sleep disorders (e.g., insomnia, restless legs syndrome, periodic limb movements of sleep, REM sleep behavior disorder), the evidence is weak. Moreover, sleep disturbances are highly prevalent also in chronic stroke and concur to worsening quality of life of patients. Promising novel technologies will probably allow, in a near future, to guarantee a screening of commonest sleep disturbances in a larger proportion of patients with stroke. Sleep assessment and management should enter in the routinary evaluation of stroke patients, of both acute and chronic phase. Future research should focus on the efficacy of specific sleep intervention as a therapeutic option for stroke patients.

Fatigue in community-dwelling older adults: A review of definitions, measures, and related factors

Fatigue is a common age-related symptom among community-dwelling adults aged 65 years and older. Yet, a systematic approach has rarely been applied to review definitions, measures, related factors, and consequences of fatigue in this population. A scoping review was conducted in December 2020 to fill the gap, and 36 articles met the inclusion criteria. Definitions, albeit diverse, included at least one of the following attributes: an early indicator of disablement, subjective, a lack of energy, multidimensional, impaired daily activities, and temporal. A summary of fatigue measures used in this population was provided, including a brief overview, number of items, reliability, and validity. In general, different measures were used with considerable variability in the content. Additionally, most measures had limited information on test-retest reliability and validity. Fatigue-related factors mapped into biological, psychological, social, and behavioral factors. Fatigue consequences were primarily declines in physical and cognitive functions. (100-150 words).

Very Early Cognitive Screening and Self-Reported Feeling of Fatigue Three Months After Stroke

Stroke is a major cause of disability and the second leading cause of death worldwide. Post-stroke fatigue has been reported as one of the most limiting symptoms after a stroke. Early identification of risk factors for developing post-stroke fatigue is important for providing timely rehabilitation. A correlation has been found between fatigue and cognitive impairment after stroke, but 2 months after stroke at the earliest. In the present study, we examined whether cognitive function screening using the Montreal Cognitive Assessment (MoCA) very early after stroke could explain fatigue 3 months after stroke. A total of 311 stroke patients admitted to a comprehensive stroke unit in Sweden between 2011 and 2016 were included in this longitudinal study. Cognition was screened within 2 days after admission to the stroke unit. Data on self-reported feeling of fatigue were retrieved from Riksstroke's 3-month follow-up form. The data were analyzed using binary logistic regression. We found that the cognitive function in an acute phase after stroke could not explain self-reported feeling of fatigue in a later stage. The correlation between cognitive impairment and fatigue that has been reported may be detectable no earlier than the subacute phase of stroke. As previous studies have shown that functional outcome, severity of stroke, and sex also correlate with fatigue after stroke, we controlled for these variables in our analysis. In line with previous studies, we found that female patients had higher odds of experiencing fatigue. This is something that health care professionals should be aware of when working with stroke patients.

Study on potential differentially expressed genes in stroke by bioinformatics analysis

Stroke is a sudden cerebrovascular circulatory disorder with high morbidity, disability, mortality, and recurrence rate, but its pathogenesis and key genes are still unclear. In this study, bioinformatics was used to deeply analyze the pathogenesis of stroke and related key genes, so as to study the potential pathogenesis of stroke and provide guidance for clinical treatment. Gene Expression profiles of GSE58294 and GSE16561 were obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IS and normal control group. The different expression genes (DEGs) between IS and normal control group were screened with the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), the function and pathway enrichment analysis of DEGS were performed. Then, a protein–protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. Cytoscape with CytoHubba were used to identify the hub genes. Finally, NetworkAnalyst was used to construct the targeted microRNAs (miRNAs) of the hub genes. A total of 85 DEGs were screened out in this study, including 65 upward genes and 20 downward genes. In addition, 3 KEGG pathways, cytokine − cytokine receptor interaction, hematopoietic cell lineage, B cell receptor signaling pathway, were significantly enriched using a database for labeling, visualization, and synthetic discovery. In combination with the results of the PPI network and CytoHubba, 10 hub genes including CEACAM8, CD19, MMP9, ARG1, CKAP4, CCR7, MGAM, CD79A, CD79B, and CLEC4D were selected. Combined with DEG-miRNAs visualization, 5 miRNAs, including hsa-mir-146a-5p, hsa-mir-7-5p, hsa-mir-335-5p, and hsa-mir-27a- 3p, were predicted as possibly the key miRNAs. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of ischemic stroke, and provide a new strategy for clinical therapy.

Risk Factors and Imaging Mechanisms of Fatigue After Mild Ischemic Stroke: An Exploratory Study From a Single Chinese Center

Objective: To explore the biochemical risk factors and imaging mechanisms of post fatigue after mild ischemic stroke among a Chinese population. Methods: Forty consecutive patients with mild ischemic stroke within onset of 14 ± 2 days were enrolled between March and June 2018. The clinical information, scale data, biomarkers in peripheral venous blood, and imaging data during hospitalization and follow-up period were collected. Results: Patient age (range 34-78) was positively correlated with the prevalence of fatigue (p = 0.009). Both blood norepinephrine and serotonin levels during hospitalization were negatively correlated to the prevalence of post-stroke fatigue (model 1 p = 0.009 and model 2 P = 0.043, respectively). Infarct of right cerebral hemisphere is positively correlated with the occurrence of fatigue after mild ischemic stroke (p = 0.020). Compared to non-fatigue patients, amplitude of low-frequency fluctuation (ALFF) was lower in several areas of brain in stroke patients with fatigue, including the right orbital inferior frontal, right inner orbital frontal, right frontal, right triangular frontal inferior, right anterior and lateral cingulate, and right medial frontal gyruses. Analysis of the difference in functional connectivity between the fatigue and non-fatigue groups found no cluster. Conclusions: Frontal lobe-related neural pathways may play an essential role in the regulation of fatigue after mild ischemic stroke. Abnormal neural circuits may reduce the levels of neurotransmitters such as serotonin and norepinephrine and lead to post-stroke fatigue.