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.

Lesioned hemisphere-specific phenotypes of post-stroke fatigue emerge from motor and mood characteristics in chronic stroke.

BACKGROUND AND PURPOSE: Post-stroke fatigue commonly presents alongside several comorbidities. The interaction between comorbidities and their relationship to fatigue is not known. In this study, we focus on physical and mood comorbidities, alongside lesion characteristics. We predict the emergence of distinct fatigue phenotypes with distinguishable physical and mood characteristics. METHODS: In this cross-sectional observational study, in 94 first time, non-depressed, moderate to minimally impaired chronic stroke survivors, the relationship between measures of motor function (grip strength, nine-hole peg test time), motor cortical excitability (resting motor threshold), Hospital Anxiety and Depression Scale and Fatigue Severity Scale-7 (FSS-7) scores, age, gender and side of stroke was established using Spearman's rank correlation. Mood and motor variables were then entered into a k-means clustering algorithm to identify the number of unique clusters, if any. Post hoc pairwise comparisons followed by corrections for multiple comparisons were performed to characterize differences among clusters in the variables included in k-means clustering. RESULTS: Clustering analysis revealed a four-cluster model to be the best model (average silhouette score of 0.311). There was no significant difference in FSS-7 scores among the four high-fatigue clusters. Two clusters consisted of only left-hemisphere strokes, and the remaining two were exclusively right-hemisphere strokes. Factors that differentiated hemisphere-specific clusters were the level of depressive symptoms and anxiety. Motor characteristics distinguished the low-depressive left-hemisphere from the right-hemisphere clusters. CONCLUSION: The significant differences in side of stroke and the differential relationship between mood and motor function in the four clusters reveal the heterogenous nature of post-stroke fatigue, which is amenable to categorization. Such categorization is critical to an understanding of the interactions between post-stroke fatigue and its presenting comorbid deficits, with significant implications for the development of context-/category-specific interventions.

Fatigue after spontaneous intracerebral haemorrhage: prevalence and associated factors.

BACKGROUND: Fatigue is a major complaint in stroke survivors, but data focusing on intracerebral haemorrhage (ICH) survivors are scarce. In a cohort of spontaneous ICH survivors, we assessed the long-term prevalence of fatigue and its associated factors. METHODS: We included consecutive 1-year ICH survivors from the prospective, observational, single-centre Prognosis of Intracerebral Haemorrhage (PITCH) study. We evaluated fatigue (defined as a score ≥ 4 in Chalder Fatigue Scale); the severity of neurological, depressive, and anxiety symptoms; and functional disability 1, 3, and 6 years after ICH. We performed univariable and multivariable models to evaluate clinical factors and brain magnetic resonance imaging (MRI) small vessel disease (SVD) markers associated with fatigue. RESULTS: Of 255 1-year ICH survivors, 153 (60%) underwent fatigue screening and were included in this study. Seventy-eight patients (51%) reported fatigue at 1-year, 56/110 (51%) at 3-year, and 27/67 (40%) at 6-year follow-up. Patients with fatigue exhibited more severe concomitant depressive/anxiety symptoms, but the severity of depressive symptoms was the only clinical factor significantly associated with 1-year fatigue in multivariable analysis (adjusted odds ratio 1.4 for one-point increase; 95% confidence interval 1.2-1.6). Patients with severe cortical atrophy at baseline had increased risk of fatigue at 1-year follow-up compared to patients with mild/no cortical atrophy (adjusted odds ratio 2.5; 95% confidence interval 1.1-5.8). CONCLUSIONS: Fatigue after ICH is frequent and long-lasting, and it is associated with cortical atrophy (but not with other MRI markers of cerebral SVD). The link between fatigue and depressive symptoms may represent a potential therapeutic target.

Post-stroke fatigue, hope and discharge readiness: A cross-sectional survey.

AIMS AND OBJECTIVES: To explore the relationships among post-stroke fatigue, hope and discharge readiness in stroke patients, and to determine whether hope mediates the relationship between post-stroke fatigue and discharge readiness. BACKGROUND: In stroke patients, inadequate discharge readiness has been found to correlate with higher readmission and mortality rates. Although previous qualitative studies have confirmed the impact of fatigue on discharge readiness, few studies explore the impact of post-stroke fatigue and hope on discharge readiness of stroke patients. Consequently, the current research on this relationship and its underlying mechanisms is still quite limited. DESIGN: Cross-sectional study. METHODS: Data were collected from 340 stroke patients. The research tools included demographic and disease characteristics, Discharge Readiness Assessment Scale for Stroke, Neurological Fatigue Index for Stroke and Herth Hope Index. The STROBE checklist was used to guide the presentation of this study. RESULTS: Discharge readiness was negatively correlated with post-stroke fatigue and positively correlated with hope. Additionally, post-stroke fatigue was negatively correlated with hope. Post-stroke fatigue had a direct negative effect on discharge readiness, and it can also generate indirect effects through hope. Hope was the partial mediator between post-stroke fatigue and discharge readiness, explaining 55.8% of the total effect. CONCLUSION: Discharge readiness of this population can be improved by reducing post-stroke fatigue and increasing hope. Therefore, effective management of post-stroke fatigue and hope will help improve discharge readiness. RELEVANCE TO CLINICAL PRACTICE: It is recommended that nursing staff should monitor the occurrence and development of post-stroke fatigue in stroke patients, dynamically evaluate the patient's level of hope, and pay attention to the important role of positive psychological qualities in the outcome of discharge. If medical staff can formulate corresponding intervention measures based on the influence path of discharge readiness, then the discharge readiness of stroke patients can be improved.

Fear of disease progression and resilience parallelly mediated the effect of post-stroke fatigue on post-stroke depression: A cross-sectional study.

AIMS: To explore the effect of post-stroke fatigue (PSF) on post-stroke depression (PSD) and examine the mediating effects of fear of disease progression (FOP) and resilience between PSF and PSD. DESIGN: A cross-sectional study. METHODS: A total of 315 stroke patients participated in the questionnaire survey between November 2022 and June 2023. Data were collected using the General Information Questionnaire, Fatigue Severity Scale, Fear of Disease Progression Questionnaire-Short Form, Connor-Davidson Resilience Scale-10 Item and Hospital Anxiety and Depression Scale-Depression Subscale. Data were analysed by descriptive analysis, Mann-Whitney U-test, Kruskal-Wallis H-test, Pearson or Spearman correlation, hierarchical regression analysis and mediation analysis. RESULTS: PSF had a significant positive total effect on PSD (ß = .354, 95% CI: .251, .454). Additionally, FOP and resilience played a partial parallel-mediating role in the relationship between PSF and PSD (ß = .202, 95% CI: .140, .265), and the total indirect effect accounted for 57.06% of the total effect. CONCLUSIONS: FOP and resilience parallelly mediated the effect of PSF on PSD, which may provide a novel perspective for healthcare professionals in preventing PSD. Targeted interventions aiming at reducing PSF, lowering FOP levels and enhancing resilience may be possible ways to alleviate PSD. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Interventions that tail to reducing PSF, lowering FOP levels and enhancing resilience may be considered as possible ways to alleviate PSD. IMPACT: This study enriched the literature by exploring the effect of PSF on PSD and further examining the mediating effects of FOP and resilience between PSF and PSD. Findings emphasized the important effects of PSF, FOP and resilience on PSD. REPORTING METHOD: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for cross-sectional studies was used to guide reporting. PATIENT OR PUBLIC CONTRIBUTION: One tertiary hospital assisted participants recruitment.

Clinical and neuroanatomical predictors of post-stroke fatigue.

INTRODUCTION: Post-stroke fatigue (PSF) has been described as early exhaustion with tiredness that develops during physical or mental activity and generally does not improve with rest. There are inconsistent findings on the relationship between the characteristics of the ischemic brain lesion and PSF. However, some studies suggest that specific neuroanatomical and neuroplastic changes could explain post-stroke fatigue. The aim was to evaluate the severity of PSF in relation to the location and the size of the ischemic lesion in acute stroke patients to establish possible predictors of PSF. PATIENTS AND METHODS: We performed a prospective observational study to establish potential early predictors of long-term PSF, which was assessed using the Fatigue Assessment Scale six months after ischemic stroke. After segmenting brain infarcts on Diffusion-Weighted Imaging (DWI) images, we studied the association with PSF using Voxel-Based Lesion-Symptom Mapping (VLSM). RESULTS: Out of 104 patients, 61 (59 %) reported PSF. Female sex and history of diabetes mellitus were associated with a greater risk of developing PSF. The association of PSF with female sex was confirmed in a replication cohort of 50 patients. The ischemic lesion volume was not associated with PSF, and VBLSM analysis did not identify any specific brain area significantly associated with PSF. CONCLUSIONS: PSF is frequent in stroke patients, especially women, even after six months. The absence of neuroanatomical correlates of PSF suggests that it is a multifactorial process with biological, psychological, and social risk factors that require further study.

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 (ß = 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.

Exploring the Mediating Role of Sleep Deficit-Related Functional Status in Subacute Stroke Survivors.

Background: Understanding post-stroke fatigue (PSF) and its associated factors is crucial for effective therapy and rehabilitation. This study aimed to assess the mediating role of the excessive daytime sleepiness-related functional status (SFS) on the relationship between sleep and the severity of fatigue in subacute stroke survivors. Methods: Subacute stroke survivors (n = 50; male = 38; female = 12), completed a cross-sectional study involving the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the insomnia severity index (ISI), the functional outcome of the sleep questionnaire (FOSQ), and the fatigue severity scale (FSS). Results: The SFS mediated the association between the severity of fatigue and sleep problems. The PSQI and FOSQ (b = -0.37, p < 0.001), and the FOSQ and FSS were correlated (b = -0.18, p < 0.05), with a significant indirect effect of the PSQI on the FSS. The ISI correlated with the FOSQ (b = -0.20, p < 0.001), with significant direct (b = 0.15, p < 0.001), as well as indirect, effects of the ISI on the FSS. The ESS correlated with the FOSQ (b = -0.23, p < 0.001), with a significant indirect effect of the ESS on the FSS. Conclusions: In subacute stroke survivors, fatigue and sleep are linked. Increased understanding of sleep-PSF may help in exploring new targets for supplement therapy.

Effects of focus training on heart rate variability in post-stroke fatigue patients.

OBJECTIVE: This study discusses the effects of focus training on heart rate variability (HRV) in post-stroke fatigue (PoSF) patients. METHODS: Self-generate physiological coherence system (SPCS) was used for the focus training of PoSF patients for 12 weeks. Then, fatigue severity scale (FSS), Hamilton depression scale (HAMD), HRV and satisfaction scale (SASC-19) before and after the training were assessed. RESULTS: Compared with the control group, FSS score, HAMD score, RMSSD, PNN50% were significantly lower in the research group at the end of the intervention (P < 0.05); SDNN, SDANN, LF, HF, LF/HF intervention satisfaction rate increased significantly in the research group at the end of the intervention (P < 0.05). CONCLUSION: The use of SPCS software during the focus training of PoSF patients reduced the fatigue and depression, meanwhile improved the HRV of the patients. Therefore, these patients were greatly satisfied with the intervention.

How do stroke survivors and their caregivers manage post-stroke fatigue? A qualitative study.

OBJECTIVES: The primary objective was to gain insight into the lived experiences of using day-to-day strategies to manage post-stroke fatigue. DESIGN: Qualitative, descriptive study. SETTING: Community telephone interviews. PARTICIPANTS: A purposive sample of 20 stroke survivors with current, or previous, post-stroke fatigue, and 8 caregivers, who provided informal care or support, were recruited. MAIN MEASURES: Semi-structured telephone interviews were undertaken. Data were analysed using a framework approach. RESULTS: Most participants had found their own ways of coping and their personal strategies included acceptance of having fatigue; 'pacing' (spreading activities out and interspersing with rest periods); keeping a diary in order to plan activities and to identify 'trigger' activities which induced fatigue; talking to (and educating) others about having fatigue; using relaxation; and accessing professional advice and support. The burden placed on caregivers was considerable and they often had to oversee the post-stroke fatigue management strategies used. CONCLUSIONS: Post-stroke fatigue is managed in different ways and there was not one particular strategy that seemed effective for everyone. Most people in our study had had to devise their own ways of coping practically. Given the scale of this problem, which profoundly impacts the lives of both stroke survivors and caregivers, the management of post-stroke fatigue merits more attention and evaluation. However, this must be directly informed by those with lived experience.

POSTSTROKE FATIGUE AND MOTOR RECOVERY AFTER ISCHEMIC STROKE.

OBJECTIVE: The aim: To determine the effect of post-stroke fatigue on the motor recovery after ischemic stroke. PATIENTS AND METHODS: Materials and methods: The study was conducted on the basis of the department of vascular neurology of the Uzhhorod Central City Clinical Hospital during the six months of 2020. We examined 92 patients who suffered a hemispheric ischemic stroke in the early recovery period. RESULTS: Results: At the end of therapy, improvement of motor function was observed in patients in both groups. We received a significant improvement(p<0,05) in the patients of the main group on the SSS and 6-point scale of muscle strength. We found that a high score on the FAS showed a significant correlation with the worst dynamics of recovery on the NIHSS, Scandinavian scale of stroke and 6-point scale of muscle strength (p <0,05). CONCLUSION: Conclusions: According to the results of the study, it was found that the presence of post-stroke fatigue significantly impairs the improvement of motor functions in patients with hemispheric ischemic stroke, patients who had more severe fatigue had worse recovery rates after stroke.

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

BACKGROUND: Post-stroke fatigue (PSF) is one of the most common complications of stroke and has a negative impact on quality of life over time. Although several therapeutic approaches have been explored in the last decade, the risk factors responsible for the occurrence of PSF are still largely unknown. OBJECTIVE: The aim of this meta-analysis was to identify the risk factors contributing to PSF, especially clinical and social risk factors, which may help to prevent PSF. METHODS: A systematic literature search was performed with PubMed, EMBASE, Cochrane Library, and Web of Science databases from inception until April 2019. Only original studies measuring the association between potential risk factors and PSF were included. All relevant data the included studies were extracted by two independent reviewers using predefined data fields. RESULTS: Fourteen studies (n = 3933) were included in this meta-analysis. Female (OR = 1.39; p < 0.01), thalamus (OR = 1.76; p = 0.02), leucoaraiosis (OR = 1.73; p < 0.01), NIHSS score (OR = 1.16; p < 0.01), modified Rankin Scale (OR = 1.63; p < 0.01), depression (OR = 1.75; p < 0.01), and sleeping disturbances (OR = 2.01; p < 0.01) were all significantly associated with PSF. In the subgroup analysis, depression (OR = 2.75; p < 0.01) tended to be associated with Asian patients with PSF. For patients who had a stroke survive for more than half a year, PSF was more likely to occur in stroke survivors with depression (OR = 1.46; p < 0.01), anxiety (OR = 1.13; p < 0.01), or sleeping disturbances (OR = 1.98; p < 0.01). CONCLUSION: Despite some limitations, this study first identified that female and depression conferred an increased susceptibility to PSF, regardless of whether in European or Asian populations. Risk factors associated with PSF included female, thalamic, leucoaraiosis, depression, sleeping disturbances, diabetes mellitus, and anxiety. This meta-analysis shows that chronic PSF appears to be largely attributable to patients with multiple comorbidities. It is necessary to strengthen the treatment for stroke-related complications and improve stroke patient care, which could help to reduce the incidence of PSF. TRIAL REGISTRATION: CRD42019128751.

Adjuvant therapy with Astragalus membranaceus for post-stroke fatigue: a systematic review.

Post-stroke fatigue (PSF) is a common symptom after stroke and interferes with the rehabilitation. There are limited pharmacological therapies for managing PSF. Astragalus membranaceus (Huangqi) is a frequently used Chinese herbal medicine (CHM) in the treatment of fatigue in China. The aim of this review was to summarize the efficacy of adjuvant therapy with CHM Huangqi (CHM-HQ) in managing fatigue after stroke. We searched the databases in both English and Chinese for randomized controlled trials (RCTs) on CHM-HQ for PSF till November 2016. The Cochrane risk of bias tool was used to assess the quality of included trials, and the Review Manager 5.3 software was used to conduct the data analysis. Sixteen RCTs with a total of 1222 participants were included. The evidence was poor in quality with unclear or high risks of bias. Compared to routine intervention, treatment with CHM-HQ decreased the fatigue severity based on the assessment of the Fatigue Severity Scale, Fugl-Meyer and Visual Analogue Scale, and improved the quality of life as measured by the Stroke Specific Quality of Life scale, the Barthel index, and the modified Barthel index, while the adverse effects were mild. In conclusions, adjuvant therapy with CHM-HQ may benefit in managing fatigue and quality of life in stroke patients. However, stronger evidence is needed for a promising conclusion and more rigorous designs of RCTs are merited in the future.

Post-stroke Fatigue is an Independent Predictor of Post-stroke Disability and Burden of Care: A Path analysis Study.

UNLABELLED: Post-stroke fatigue (PSF) is a common and one of the most distressing symptoms in stroke survivors. However, little is known about the relationship between severity of fatigue and the overall impact it has on post-stroke disability and burden of care. We aimed to examine the role of PSF in post-stroke disability and burden of care among stroke survivors after their first-ever stroke. METHODS: We prospectively recruited 163 subjects (35 females) from patients examined consecutively in a tertiary stroke care center in India, after their first-ever ischemic or hemorrhagic stroke (>3 months after event). In addition to demographic and clinical characteristics, the following assessments were done - SF-36 vitality domain (fatigue), Modified Rankin Scale (functional recovery), Hospital anxiety and depression scale (depression), Functional independence measure (disability and burden of care). We used path analysis to identify a model that will capture the interactions of fatigue, depression, and degree of functional recovery in stroke survivors. RESULTS: The severity of PSF positively correlated with the severity of disability and PSF had significant contribution to disability over and above functional recovery and depression, with all three factors accounting for 43% of the variance. Among the four models that were proposed to explore these relationships, the best fitting model showed that the effect of PSF is mediated through both the direct effect of fatigue on disability and through its interaction with depression, which remained a separate contributor to post-stroke disability and burden of care. CONCLUSIONS: PSF, therefore, is an important determinant of post-stroke disability and should be evaluated for successful post-stroke rehabilitation.

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.

Influence of Perceptual Load on Attentional Orienting in Post-Stroke Fatigue: A Study of Auditory Evoked Potentials.

OBJECTIVE: Increasing perceptual load alters behavioral outcomes in post-stroke fatigue (PSF). While the effect of perceptual load on top-down attentional processing is known, here we investigate if increasing perceptual load modulates bottom-up attentional processing in a fatigue dependent manner. METHODS: In this cross-sectional observational study, in 29 first-time stroke survivors with no clinical depression, an auditory oddball task consisting of target, standard, and novel tones was performed in conditions of low and high perceptual load. Electroencephalography was used to measure auditory evoked potentials. Perceived effort was rated using the visual analog scale at regular intervals during the experiment. Fatigue was measured using the fatigue severity scale. The effect of fatigue and perceptual load on behavior (response time, accuracy, and effort rating) and auditory evoked potentials (amplitude and latency) was examined using mixed model ananlysis of variances (ANOVA). RESULTS: Response time was prolonged with greater perceptual load and fatigue. There was no effect of load or fatigue on accuracy. Greater effort was reported with higher perceptual load both in high and low fatigue. p300a amplitude of auditory evoked potentials (AEP) for novel stimuli was attenuated in high fatigue with increasing load when compared to low fatigue. Latency of p300a was longer in low fatigue with increasing load when compared to high fatigue. There were no effects on p300b components, with smaller N100 in high load conditions. INTERPRETATION: High fatigue specific modulation of p300a component of AEP with increasing load is indicative of distractor driven alteration in orienting response, suggestive of compromise in bottom-up selective attention in PSF.

Relationships of post-stroke fatigue with mobility, recovery, performance, and participation-related outcomes: a systematic review and meta-analysis.

Background: Effective post-stroke mobility, recovery, performance, and participation are key goals for stroke survivors. However, these outcomes may be hindered by post-stroke fatigue (PSF), which can affect numerous aspects of post-stroke mobility, recovery, performance, functioning, community participation, and return to work. This review aimed to assess the scientific evidence on the relationship between PSF and mobility function, functional recovery, functional performance, and participation-related outcomes among stroke survivors. Method: A comprehensive search of Cochrane Central, PubMed, Embase, and Web of Science (WoS) databases was conducted from inception to December 2023. Observational, cross-sectional, and longitudinal studies were included. The methodological quality of the included studies was assessed using the National Institute of Health's quality assessment tool, while the risk of bias was assessed using the Quality in Prognostic Studies tool. A total of 28 studies (n = 2,495 participants, 1,626 men, mean age ranging from 52.5 ± 9.5 to 71.1 ± 9.9 years) were included. The data analysis was conducted using narrative and quantitative synthesis. Fixed and random effects meta-analyses were conducted to explore the relationships between PSF and relevant outcomes. Results: Chronic PSF was found to have significant negative correlations with mobility (meta r = -0.106, p < 0.001), balance performance (meta r = -0.172; 95%; p = 0.004), and quality of life (meta r = -0.647; p < 0.001). It also showed significant positive correlations with stroke impairment (meta r = 0.144, p < 0.001) and disability (meta r = 0.480, p < 0.001). Additionally, exertion/acute PSF had significantly negative correlations with walking economy (meta r = -0.627, p < 0.001) and walking endurance (meta r = -0.421, p = 0.022). The certainty of evidence was deemed moderate for these relationships. Conclusion: Our findings indicate that higher levels of PSF are associated with poorer mobility, balance, and participation, as well as greater disability and stroke impairment. Future studies, especially prospective longitudinal and randomized controlled trials, are warranted to substantiate our findings. Systematic review registration: PROSPERO, identifier: CRD42023492045.

Managing Post-Stroke Fatigue Using a Mobile Health Called iHealth After Intracerebral Hemorrhage.

Background: Post-stroke Fatigue (PSF) after Intracerebral Hemorrhage (ICH) is a long-term symptom in stroke survivors. However, the pathogenesis of PSF remains inadequately understood and sufficient evidence-based treatments are lacking. Mobile health (mHealth) technology offers a promising approach to expanding access to high-quality and culturally tailored evidence-based mental care. Aim: This study examined the role of mHealth called iHealth in the management of PSF after ICH. Methods: A total of 225 patients diagnosed with intracerebral hemorrhage (ICH) were included in the study and randomly assigned to either the Mobile Health Intervention Group (mHI Group) or the non-Mobile Health Intervention Group (non-mHI). The management involved the utilization of a digital healthcare application named iHealth, which incorporated digital questionnaires, fatigue scale tests, and online videos for the purpose of administering the Patient Fatigue Reporting Measurement Information System (PFRMIS) short form as part of the initial patient assessment following ICH. The study was conducted remotely via video conferencing over a 12-week period in mHI Group, with fatigue assessments being conducted 3 months post-ICH onset in two groups. Results: Following the administration of PSF by iHealth, Univariate Logistic analyses indicated a significant association between fatigue and the type of activity, with patients who were sedentary or did nothing experiencing higher levels of fatigue (ß=2.332, p<0.001; ß=2.517, p<0.001). Multivariate Logistic analyses demonstrated a positive association between the intensity of physical activity and decreased emotional well-being and family support, as well as increased fatigue. (p=0.001, p=0.002, p=0.001). The FSS results demonstrated a significantly reduced incidence of PSF in the MHI group in comparison to non-mHI group following the conclusion of the programme. (13.1% vs 40%, p<0.001). Conclusion: This study explored the effectiveness of the iHealth app for PSF following ICH, indicating that iHealth is a clinically valuable tool that warrants further dissemination.

A systematic review of post-stroke fatigue measurement scale based on COSMIN guidelines.

Objective: This study aimed to evaluate the methodological quality and measurement attribute quality of the post-stroke fatigue measurement scale, so as to provide some basis for the clinical application and promotion of related scales. Methods: The Chinese National Knowledge Infrastructure, the Wanfang Data Knowledge Service Platform, the China Science and Technology Journal Database, the Chinese Medical Journal Full-text Database, the Chinese Biology Medicine, PubMed, Embase, Medline, the Cochrane Library, the Web of Science, CINAHL, and PsycINFO databases were searched for literature on the post-stroke fatigue measurement scale up to June 2022. Literature screening and data extraction were carried out independently by two researchers, and in the case of disagreement, discussions were held with a third investigator to reach an agreement, and the COSMIN checklist and criteria were used to systematically evaluate the attributes of the measurement scale. Results: A total of 17 studies were included, involving 10 post-stroke fatigue measurement scales. The content validity of FSS-7, FACIT-F, NRS-FRS, and MFI-20 was "not mentioned," and the remaining scales were "uncertain." In terms of construct validity, MFS was "adequate"; FSS-7, FACIT-F, and NRS-FRS were "not mentioned"; and the remaining scales were "uncertain." In terms of internal consistency, NRS-FRS was "not mentioned"; FSS and MFS were "adequate"; and the remaining scales were "uncertain." In terms of hypothesis testing, CIS and FACIT-F were "not mentioned," NRS-FRS was "adequate," and the remaining scales were "uncertain." The stability of FSS-7, CIS, FACIT-F, and MFI-20 was "not mentioned," and the remaining scales were "adequate." The cross-cultural validity of FSS-7 was "adequate," and the remaining scales were "not mentioned." All 10 scales were given a recommendation grade of "B". Conclusion: For the time being, the FSS can be recommended to measure post-stroke fatigue, but it still needs to be tested for more relevant measurement properties in order to gain more support from high-quality evidence. For a more comprehensive assessment of post-stroke fatigue, the FIS, FAS, and NFI-stroke should perhaps be considered, as the FSS is a one-dimensional scale that can only measure physical fatigue in patients; however, these scales also need to be tested for more relevant measurement properties to verify their clinical applicability.

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.