The minimal clinically important difference of two multifaceted fatigue evaluation questionnaires in chronic stroke.

PURPOSE: This research sought to ascertain the Minimal Clinically Important Difference (MCID) and Robust Clinically Important Difference (RCID) of the Multidimensional Fatigue Symptom Inventory-Short Form (MFSI-SF) and Chalder Fatigue Questionnaire-11 (CFQ-11) as two important concepts for the clinical interpretation of the results in chronic post-stroke population. METHODS: A total of 128 subjects with chronic post-stroke completed the MFSI-SF and CFQ-11 before and after six weeks of intervention. The MCIDs were derived using both anchor- and distribution-based methods; however, only anchor-based methods were used to estimate RCIDs. RESULTS: Anchor-based MCIDs for MFSI-SF and CFQ-11 were in the range of -5 to -6.28 and -2 to -4.56, respectively. Distribution-based MCIDs in MFSI-SF and CFQ-11 were calculated in the range of -4.17 to -24.05 and -1.72 to -7.68, respectively. RCID ranges of -10 to -15 were obtained for the MFSI-SF and -6 to -7.33 for the CFQ-11. CONCLUSION: These findings may have implications for clinical experts in the clinical interpretation of fatigue changes observed in MFSI-SF and CFQ-11 in individuals with chronic stroke.

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.

Minimal and robust clinically important differences for patient-reported outcome measures of fatigue in chronic stroke survivors after fatigue rehabilitation.

PURPOSE: The minimal and robust clinically important difference (MCID and/or RCID) are essential in assessing the clinical significance of multidimensional fatigue inventory-20 and checklist of individual strength-fatigue subscale questionnaires changes scores. This is the first study to determine the MCID and RCID of these questionnaires in chronic stroke survivors. MATERIALS AND METHODS: A total of 125 participants in an observational cohort study completed MFI-20 and CIS-fs before and after receiving multidisciplinary rehabilitation (cognitive behavioral therapy, graded exercise and adaptive pacing therapy). Anchor-based MCIDs and RCIDs were calculated using the mean change, the mean difference and the receiver operating characteristics methods. To evaluate the accordance between of distribution-based MCIDs (1 SD, ½ SD, SEM, 1.96 SEM and MDC values) with anchored values, the accuracy, sensitivity, specificity and Youden's index were calculated. RESULTS: The anchored MCIDs were between -5 to -7.33 for MFI-20 and -4.87 to -5.40 for CIS-fs. The anchored RCIDs ranged from -5 to -13.88 and -6 to -9.88 for MFI-20 and CIS-fs, respectively. The values of ½ SD and SEM for CIS-fs were consistent with anchored RCIDs. CONCLUSIONS: The estimated MCIDs and RCIDs of MFI-20 and CIS-fs can help researchers and clinicians interpret their chronic stroke patient data.

The Multidimensional Fatigue Inventory-20 (MFI-20) And Checklist Individual Strength-20 (CIS-20) Measures Are Two Important And Valid Instruments For Measuring Fatigue In Patients With Chronic Stroke.The Identified Minimal Clinically Important Differences (MCID) And Robust Clinically Important Difference In The Current Study Can Assist Clinicians In The Clinical Interpretation Of Fatigue Changes Observed In MFI-20 And CIS-20 Scores.The MCID Obtained In This Study Can Be Useful In Determining The Proportion Of Patients Who Benefit From Fatigue Treatment In Stroke Rehabilitation.

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.

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.

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.

Cardiorespiratory fitness, physical activity, and fatigue three months after first-ever ischemic stroke.

BACKGROUND: Research on cardiorespiratory fitness (CRF) in relation to physical activity (PA) and fatigue after stroke is limited. Increased knowledge of interrelationships between these factors can help optimize rehabilitation strategies and improve health-outcomes. OBJECTIVES: We aimed to: 1) evaluate CRF, PA, and fatigue, 2) characterize patients with impaired versus non-impaired CRF, and 3) examine associations of CRF with PA and fatigue, three months after first-ever ischemic stroke. METHODS: In this cross-sectional study CRF was measured as peak oxygen uptake (VO2peak) by cardiopulmonary exercise testing. PA was measured using accelerometers. Fatigue was assessed with the 7-item Fatigue Severity Scale (FSS). RESULTS: The sample (n=74, mean age 64±13 years, 36% women) had a mean VO2peak of 27.0±8.7 (86% of predicted). Fifty-one percent met the World Health Organization's recommendation of ≥150 min of moderate PA/week. Mean steps-per-day was 9316±4424 (113% of predicted). Thirty-five percent of the sample had moderate-to-high fatigue (FSS≥4), mean FSS score was 3.2±1.8.  Patients with impaired CRF (VO2peak<80% of predicted) had higher body-fat-percent (p<0.01), less moderate-to-vigorous PA (MVPA) (p<0.01) and a trend toward higher fatigue (p=0.053) compared to the non-impaired. Backward regression analysis showed that higher CRF was associated with more MVPA (unstandardized beta [95% CI]: 0.38 [0.15, 0.63], p=0.002) and less fatigue (unstandardized beta [95% CI]: -3.9 [-6.4, -1.6], p=0.004). CONCLUSIONS: Stroke patients had lower CRF compared to reference values. Impaired CRF was mainly related to overweight. Higher CRF was associated with more MVPA and less fatigue. Exercise after stroke may be especially beneficial for patients with impaired CRF.

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.

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.

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.

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.

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.

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.

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.Implications for rehabilitationPost-stroke fatigue is a complex individual experience involving biopsychosocial factors, and stroke survivors need assistance to identify their triggers and support from family, peers, and the stroke community to live well with fatigue.Fatigue is not commonly discussed by health professionals and stroke survivors need simple, practical advice over the long-term to reduce fear and distress.There are a range of strategies that may be helpful. Stroke survivors may benefit from adopting problem-solving approaches, trial pacing, lifestyle modifications and planning, and find forms of rest that work for them.

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.

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.

People of working age who experience post-stroke fatigue encounter difficulties with complex rather than basic activities.Post-stroke fatigue may be developed when reclaiming complex activities; thus, long term routine assessments after discharge are recommended.Interventions addressing post-stroke fatigue are warranted, as the absence of post-stroke fatigue increases the chance of returning to everyday life, including work.

Persian version of the Chalder Fatigue Questionnaire and Multidimensional Fatigue Symptom Inventory-Short Form: psychometric properties in Iranian chronic stroke survivors.

BACKGROUND: Post-stroke fatigue is a disturbing condition with various physical and psychological facets, which needs to be assessed by meaningful and psychometrically valid and reliable tools. The Chalder Fatigue Questionnaire (CFQ) and Multidimensional Fatigue Symptom Inventory-Short Form (MFSI-SF) have been designed to assess diverse dimensions of fatigue. OBJECTIVES: The present study aimed to investigate the psychometric properties of the CFQ and MFSI-SF in people with chronic stroke. METHODS: Both measures were translated according to forward-backward standard protocol. This cross-sectional study was conducted with 130 first-time stroke survivors. The multidimensional fatigue inventory, checklist individual strength, fatigue assessment scale, fatigue subscale of profiles of mood state, fatigue severity scale, visual analogue scale-fatigue, beck anxiety inventory, center for epidemiologic studies of depression scale, and 36-item short-form health survey were administered in addition to the CFQ and MFSI-SF. Reliability, precision, known-groups validity, and convergent validity were examined for the CFQ and MFSI-SF. RESULTS: The results showed an acceptable (Cronbach's alpha = 0.81-0.97) internal consistency and test-retest reliability (intra-class correlation = 0.75-0.97). The CFQ and MFSI-SF revealed good ability (P < 0.001) to differentiate chronic stroke survivors with different disability levels. Significant high correlation (P = -0.61-0.87) was found between CFQ and MFSI-SF and other fatigue scales. CONCLUSIONS: The results of this study showed that the CFQ and MFSI-SF have high reliability and validity for chronic stroke survivors.

Neuroimaging correlates of post-stroke fatigue: A systematic review and meta-analysis.

BACKGROUND: Fatigue is a common and disabling symptom following stroke, but its underlying mechanisms are unknown. Associations with a number of imaging features have been proposed. AIMS: We aimed to assess whether neuroimaging parameters could better inform our understanding of possible causes of post-stroke fatigue (PSF) through systematic review and meta-analysis. METHODS: Using a predefined protocol registered with PROSPERO (ID: CRD42022303168), we searched EMBASE, MEDLINE, PubMed, and PsycInfo for studies assessing PSF and computerized tomography (CT), magnetic resonance (MR), positron emission tomography (PET) imaging, or diffusion tensor imaging (DTI). We extracted neuroimaging parameters and narratively analyzed study results to assess any association with PSF. Where there were 3+ similar studies, we carried out a meta-analysis using inverse-variance random-effects model to estimate the total association of each neuroimaging parameter on PSF. The risk of bias was assessed using the Newcastle and Ottawa Scale. RESULTS: We identified 46 studies (N = 6543); in many studies, associations with fatigue were secondary or subanalyses (28.3%). Imaging parameters were assessed across eight variables: lesion lateralization, lesion location, lesion volume, brain atrophy, infarct number, cerebral microbleeds, white matter hyperintensities (WMHs), and network measures. Most variables showed no conclusive evidence for any association with fatigue. Meta-analysis, where possible, showed no association of the following with PSF; left lesion lateralization (OR: 0.88, 95% CI (0.64, 1. 22) (p = 0.45)), infratentorial lesion location (OR: 1.83, 95% CI (0.63, 5.32) (p = 0.27)), and WMH (OR: 1.21, 95% CI (0.84, 1.75) (p = 0.29)). Many studies assessed lesion location with mixed findings; only one used voxel-symptom lesion-mapping (VSLM). Some small studies suggested an association between altered functional brain networks, namely frontal, fronto-striato-thalamic, and sensory processing networks, with PSF. CONCLUSION: There was little evidence for the association between any neuroimaging parameters and PSF. Future studies should utilize advanced imaging techniques to fully understand the role of lesion location in PSF, while the role of altered brain networks in mediating PSF merits further research.