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Join IBIA’s Webinar Event

Join your colleagues from around the world for a wide variety of learning opportunities through December 2024. Registration is free for IBIA Members and $25 for non-members. We look forward to welcoming you to the 2024 IBIA Webinar Series. Questions: congress@internationalbrain.org

Registration links are below.  

Post Traumatic Fatigue: Best Practices Assessment and Clinical Management

Speaker: Brian Greenwald, MD
Date and Time: May 9, 2024 at 12 PM ET
Organized by North America Brain Injury Society.

This webinar will review the definition of fatigue as well as how it is conceptualized including peripheral versus central fatigue. Anatomic areas of the brain implicated in fatigue will be reviewed. Assessment tool for fatigue, the differential diagnosis, medical work up and a range of treatment considerations will be discussed.

Brian Greenwald, MD, is the Medical Director of the Center for Brain Injuries and the Associate Medical Director of JFK Johnson Rehabilitation Institute. He is the Fellowship Director for JFK Johnson’s Accreditation Council for Graduate Medical Education (ACGME)- certified Brain Injury Medicine fellowship. Additionally, Dr. Greenwald is a Clinical Associate Professor in the Department of Physical Medicine and Rehabilitation at Rutgers Robert Wood Johnson Medical School and is a Core Associate Professor in the Department of Physical Medicine and Rehabilitation at the Hackensack Meridian School of Medicine.

Registration – Post Traumatic Fatigue Webinar

Functional Brain Imaging in DoC Clinical Practice and the Forensic Arena: What Can Be Said with Confidence

Speaker: Steven Laureys, MD, PhD, FEAN
Date and Time: May 29, 2024 at 11 AM ET
Organized by Disorders of Consciousness Special Interest Group.

This talk will explore the role of functional brain imaging in assessing patients with disorders of consciousness (DoC) both in clinical practice and forensic settings. We will discuss the current state of knowledge regarding the use of functional imaging techniques such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), highlighting what can be confidently inferred from these methods in terms of diagnosis, prognosis, and the detection of covert consciousness. The talk will also address the challenges and limitations of these techniques, emphasizing the need for cautious interpretation and the integration of multiple assessment tools in comprehensive patient care.

Dr. Steven Laureys is a prominent neurologist and neuroscientist known for his work in the field of consciousness research.  He headed, until early 2020, the Coma Science Group that he created in 2014 within the GIGA Consciousness Centre at the University of Liège. Most of his research work is devoted to the study of alterations in consciousness in severely brain-damaged patients, as well as during anesthesia, sleep, meditation and in the hypnotic state. Steven Laureys is the author of over 450 scientific articles, some of which have been published in the most prestigious journals. Winner of numerous scientific awards, including the Francqui Prize (2017) – Belgium’s most prestigious scientific prize – and the Generet Prize (2019), Steven Laureys is undoubtedly one of the world’s leading specialists on the issue of altered states. He is currently professor at the CERVO research centre at Laval University (Quebec, QC, Canada).

Registration – Functional Brain Imaging

For more information on the IBIA webinars, please contact congress@internationalbrain.org.

[Abstract] Survey of the clinical practices of physiotherapists for the management of post-stroke fatigue

OBJECTIVE: Post-stroke fatigue (PSF) is a common condition among stroke survivors. However, evidence supporting the effective clinical management of PSF is insufficient. Our objectives were to examine the clinical practices of physiotherapists for the management of PSF and evaluate their clinical knowledge and confidence in managing PSF.

SUBJECTS AND METHODS: We conducted a cross-sectional study using an online survey of the sociodemographic profiles of participating physiotherapists, their current clinical practices, clinical knowledge, confidence in their clinical management of PSF, and the types and intensity of the exercises used in the management of PSF.

RESULTS: A total of 160 physiotherapists completed the survey: 86 (53.8%) were women, 148 (92.5%) were Saudi nationals, 126 (78.7%) were employed by the Ministry of Health, and 34 (21.3%) worked in the private sector. The majority (60%) of physiotherapists did not routinely assess their patients for the presence of fatigue. Likewise, 93 (58.1%) did not provide any PSF-related educational material to their patients; however, 67 (41.9%) did provide these materials. The preferred exercises of the physiotherapists for their patients were bed and chair exercises (59.5%), followed by functional training (51.4%), and resistance training (23.1%).

CONCLUSIONS: Our results suggest that while physiotherapists practicing in Saudi Arabia have a sound theoretical understanding of PSF management, their knowledge does not necessarily translate into practice. Interventions used to treat PSF include bed and chair exercises, functional training, and resistance training.

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[Abstract] Effects of non-pharmacological interventions on fatigue in people with stroke: a systematic review and meta-analysis

ABSTRACT

Background

Fatigue, a common problem following a stroke, can have negative effects on a person’s daily life. There are no good interventions thus far for alleviating fatigue among those affected.

Objective

This review aimed to evaluate the effects of non-pharmacological interventions on fatigue among people with stroke.

Methods

A search was conducted for articles in seven databases, clinical trial registry, and backward and forward citations of included publications. Randomized controlled trials, including feasibility and pilot trials, of non-pharmacological interventions for managing fatigue or promoting sleep or both in people with stroke were included. The standardized mean difference in scores for fatigue was analyzed using random effects models.

Results

Ten studies, with 806 participants, were analyzed. The identified interventions included physical interventions, cognitive interventions, a combination of physical and cognitive interventions, oxygen therapy, and complementary interventions. Non-pharmacological interventions had no significant immediate, short-term and medium-term effects on fatigue. The adverse effects of falls and arrhythmia were each found in one participant in circuit training. The risk of bias was high in all studies. The certainty of the evidence ranged from very low to low.

Conclusions

The evidence in support of any non-pharmacological interventions for alleviating fatigue is still inconclusive in people with stroke. In view of the inadequacies of existing interventions and study designs, addressing the multidimensional characteristics of fatigue may be a possible direction in developing interventions. A robust study design with a larger sample size of people with stroke experiencing fatigue is required to evaluate the effects of interventions.

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[REVIEW] Using the ICF framework to explore a multidisciplinary approach to fatigue following traumatic brain injury – Full Text

Abstract

Background

Fatigue following a traumatic brain injury (TBI) is a complex, chronic symptom, which can significantly impact quality of life. Investigation into the types of fatigue addressed by the multidisciplinary team and consequent outcomes may assist clinicians to target their care. The use of health frameworks to explore such phenomena may increase a teams’ ability to incorporate multifaceted interventions. The objective of this paper is to profile and map the available evidence for fatigue management used for the TBI population onto the International Classification of Functioning, Disability, and Health framework.

Methods

A scoping review was conducted and included papers that described an intervention focussing on post-TBI fatigue and used fatigue-specific outcome measures with an adult population. Studies were collated and summarised, and key findings are presented.

Results

Forty-seven articles met the inclusion criteria. The results indicate that post-traumatic fatigue interventions in the literature are conducted by singular professions, that there is a strong focus on a body functions approach, and that there is a discrepancy between intervention intent and measurement.

Conclusion

Although there is variety in multidisciplinary fatigue treatment, further opportunities to develop interventions that target other health and function components, including activities and participation, environment, and personal factors, may enable a greater impact of fatigue management approaches. […]

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[ARTICLE] A roadmap for research in post-stroke fatigue: Consensus-based core recommendations from the third Stroke Recovery and Rehabilitation Roundtable – Full Text

Abstract

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.

Graphical Abstract This is a visual representation of the abstract.

Introduction

One in two stroke survivors experience post-stroke fatigue (pooled prevalence estimate 47% (95% CI = 43–50%)).¹ Fatigue is a significant and disabling condition in its own right and is a significant barrier to engaging in rehabilitation and other activities that promote recovery. Despite its prevalence and impact, a recent systematic review of 200 stroke clinical guidelines found no strong recommendations for fatigue prevention or management.² Fatigue is a critical unmet need which stroke survivors identify as a high-priority research area.³ Therefore, the International Stroke Recovery and Research Alliance selected post-stroke fatigue as a focus topic of their 3rd Stroke Recovery and Rehabilitation Roundtable (SRRR).

Post-stroke fatigue is not merely “tiredness,” nor simply physical deconditioning; some people have post-stroke fatigue despite high fitness levels.⁴ Post-stroke fatigue is not always associated with effort, nor always relieved by rest. Superficially, fatigue can seem like depression or apathy, and it may co-present with both, but is distinct. For the purposes of this work, we undertook a process of literature reviews, expert consensus, and engagement with people with lived experience of stroke to define to define post-stroke fatigue as:

. . . a feeling of exhaustion, weariness or lack of energy that can be overwhelming, and which can involve physical, emotional, cognitive and perceptual contributors, which is not relieved by rest and affects a person’s daily life.

Despite the high prevalence and burden of post-stroke fatigue, research is limited. Cohorts and assessment tools vary, making pooling data and systematic analysis difficult. Intervention trials are mostly underpowered and inconclusive. Few studies include participants with a speech-language disorder, and fewer have explored the relationship between fatigue and aphasia. Yet some hypothesize a bidirectional relationship⁵ given the large effort required to understand and/or produce language.

Clearly, post-stroke fatigue is a multi-faceted condition. An abundance of biopsychosocial factors are associated with fatigue,⁶ but causal relationships remain unclear, and there is overlap between depression and fatigue. Fatigue may predispose the development of depression, and fatigue can be a symptom of depression,⁷ but the selective efficacy of fluoxetine on depression and not fatigue⁸ suggests that they can be distinct. Fatigue likely hampers engagement in productive and meaningful activities, and elevates risk of social isolation and its secondary effects.

The overarching aim of this Roundtable was to bring together current knowledge of post-stroke fatigue based on best available evidence from multidisciplinary perspectives (clinical, pre-clinical, and lived experience), identify key knowledge gaps, and provide a roadmap for future research.

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[Abstract + References] Minimal Clinically Important Difference of Fatigue Severity Scale in Patients with Chronic Stroke

Abstract

Background

One of the most prevalent symptoms of stroke is fatigue. Fatigue severity scale is the most often used tool for evaluating fatigue in stroke patients, its minimal clinically important difference threshold has not been determined. This study aimed to identify the minimal clinically important difference of fatigue severity scale in stroke patients.

Methods

All study participants were examined using fatigue severity scale and multidimensional fatigue symptom inventory-short form before and after the intervention. The 6-week intervention combined graded activity training and pacing therapy employed to reduce fatigue severity. Participants reported changes in their fatigue severity after the intervention with the global rating of change and visual analog scale. The minimal clinically important difference of the fatigue severity scale calculated using both anchor- and distribution-based methods.

Results

A total of 117 stroke patients were included in the study. Using multidimensional fatigue symptom inventory-short form, global rating of change, and visual analog scale as an anchor, the minimal clinically important difference of fatigue severity scale was obtained at 3.5, 4.5, and 4.5, respectively. The minimal clinically important difference for fatigue severity scale varied from 4.28 to 12.90 using the distribution-based method, with SEM = 4.28 displaying the best sensitivity and specificity for use as minimal clinically important difference.

Conclusions

The minimal clinically important difference value for the fatigue severity scale was estimated at 3.5_12.90 using anchor-based and distribution-based methods. The study’s results can be utilized to understand the effectiveness of fatigue interventions in stroke patients in clinical and research settings

Introduction

Fatigue is one of the most common symptoms of a stroke. Post-stroke fatigue (PSF) prevalence is about 50%¹. PSF is characterized as a persistent weakness and a lack of physical or mental energy not relieved by rest and sleep². Fatigue interferes with social participation, decreases independence in activities of daily living, increases sleep duration, and has been linked to an increased risk of suicide and mortality after a stroke3, 4, 5. Although the underlying mechanism of PSF is unclear, numerous individual factors (such as age, gender, and injury site) and psychological components (such as depression, anxiety, pain, and sleep disorders) have been identified as risk factors^6, 7.

Due to the subjective character of fatigue, assessing the intensity of symptoms by self-report tools can provide more useful information⁸. Various tools have been used to assess PSF, with the fatigue severity scale (FSS) being the most frequently used¹. The FSS is a self-report questionnaire with nine items assessing fatigue’s impact and severity. FSS showed good internal consistency (Cronbach’s alpha >0.90) and excellent test-retest reliability (ICC=0.93) in stroke patients⁹. However, the minimal clinically important difference (MCID) of the FSS has not been established in stroke patients. MCID is defined as the minimum change in an outcome measure scores that individuals consider a significant or effective change in their condition¹⁰. The concept of MCID was developed because sometimes, in a research or clinical setting, change in score of a measurement tool or statistically significant change does not match consonant with individuals’ clinical conditions or their perception of change in their health status¹¹. In the clinical setting, MCID can assist in determining the effectiveness of an intervention and continue or change it and provide a better picture of the client’s degree of change. Using MCID in a research setting allows researchers to identify the number of people who responded positively to intervention and provide a better knowledge of treatment effectiveness. Furthermore, the personal factors associated with increasing or decreasing the effects of a new treatment can be established by examining various characteristics of persons who improved or did not improve based on MCID¹².

There are two main methods for calculating MCID: anchor-based and distribution-based. In the anchor-based method, the extent of the change in the assessment tool is compared to an external anchor. External anchors are intended to analyze the amount of changes accomplished from an individual viewpoint, and it is recommended that various anchors be utilized to calculate MCID. In the distribution-based method, MCID is calculated based on statistical indicators such as standard error of measurement (SEM) and Standard deviation (SD). For examining and comparing the values for MCID calculated by different methods, triangulating on the values has been recommended^10, 12, 13.

Despite the high prevalence of fatigue in stroke patients and the widespread use of FSS for evaluating it, the MCID of FSS has not yet been investigated. Thus, this study aimed to investigate the MCID of FSS in persons with chronic stroke.

Section snippets

Study Design and Participants

The convenience non-probability sampling method was used to recruit patients with chronic stroke at four rehabilitation centers. The inclusion criteria of the study included (1) a history of stroke that occurred at least six months before the study; (2) no cognition impairments (MMSE≥24)¹⁴; (3) no severe communication impairments, such as aphasia; (4) no psychological, orthopedic, rheumatic, general, or neurological diseases, no cardiovascular instability, and no unilateral visual-spatial

Results

One hundred seventeen stroke survivors were recruited in this study. The participants’ mean age was 59.45±12.00 years, with 50 females and 67 males. Table 1 provides the demographic characteristics of the participants. Two participants were excluded because they did not complete questionnaires. The mean ± SD FSS score pre-intervention was 40.89±12.90, post-intervention was 34.19±13.69, and the mean change in score was 6.74±6.63 (P<0.001). Internal consistency of FSS was excellent (Cronbach’s

Discussion

This study is the first study investigating the MCID of FSS in chronic stroke patients. FSS is the most often used tool for measuring fatigue in stroke patients¹. Estimated MCID for FSS using both anchor-based and distribution-based methods indicated that the MCID for FSS ranges between 3.5 and 12.90 (5.5-20.5% of the FSS total score).

The anchor-based method’s objective was to connect changes in the FSS with the external anchor, which examined fatigue severity changes²⁹. This study used three

Conclusion

In conclusion, considering the prevalence of fatigue in patients with stroke, it is vital to interpret assessments accurately. The MCID of the FSS instrument was calculated in this study as the most widely used instrument for measuring fatigue in stroke patients. The study results allow a more precise interpretation of interventions in the therapeutic or clinical context, and a more precise understanding of patient problems permits the provision of more appropriate interventions for clients.

References (47)

• W-K Tang et al.Is fatigue associated with suicidality in stroke?Archives of physical medicine rehabilitation(2011)
• A Lerdal et al.Psychometric properties of the Fatigue Severity Scale—Rasch analyses of individual responses in a Norwegian stroke cohortInternational journal of nursing studies(2011)
• D Revicki et al.Recommended methods for determining responsiveness and minimally important differences for patient-reported outcomesJournal of clinical epidemiology(2008)
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• AG Copay et al.Understanding the minimum clinically important difference: a review of concepts and methodsThe Spine Journal(2007)
• BM Kluger et al.Minimal clinically important difference of the Modified Fatigue Impact Scale in Parkinson’s diseaseParkinsonism Related Disorders(2017)
• PD White et al.Comparison of adaptive pacing therapy, cognitive behaviour therapy, graded exercise therapy, and specialist medical care for chronic fatigue syndrome (PACE): a randomised trialThe Lancet(2011)
• KD Stein et al.Further validation of the multidimensional fatigue symptom inventory-short formJournal of pain and symptom management(2004)
• AA Sorensen et al.Minimal clinically important differences of 3 patient-rated outcomes instrumentsThe Journal of hand surgery(2013)
• JA Husted et al.Methods for assessing responsiveness: a critical review and recommendationsJournal of clinical epidemiology(2000)
• J Maringwa et al.Minimal clinically meaningful differences for the EORTC QLQ-C30 and EORTC QLQ-BN20 scales in brain cancer patientsAnnals of Oncology(2011)
• JV Carter et al.ROC-ing along: Evaluation and interpretation of receiver operating characteristic curvesSurgery(2016)
• KJ Yost et al.Minimally important differences were estimated for six Patient-Reported Outcomes Measurement Information System-Cancer scales in advanced-stage cancer patientsJournal of clinical epidemiology(2011)
• TB Cumming et al.The prevalence of fatigue after stroke: a systematic review and meta-analysisInternational Journal of stroke(2016)
• A Kuppuswamy et al.A model of poststroke fatigue based on sensorimotor deficitsCurrent opinion in neurology(2015)
• G Eilertsen et al.Experiences of poststroke fatigue: qualitative meta-synthesisJournal of Advanced Nursing(2013)
• VL Barbour et al.Fatigue after stroke: the patient’s perspectiveStroke research treatment(2012)
• S Wu et al.Psychological associations of poststroke fatigue: a systematic review and meta-analysisStroke(2014)
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• JF Malec et al.A standard method for determining the minimal clinically important difference for rehabilitation measuresArchives of Physical Medicine Rehabilitation(2020)
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There are more references available in the full text version of this article.

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[Review ARTICLE] Poststroke Fatigue – Full Text

Poststroke fatigue is a common symptom that can have debilitating effects. Moreover, up to 40% of stroke survivors report it as their worst or one of their worst symptoms.^1,2 This increasingly recognized symptom has been reported to have a prevalence that varies widely.^3,4 Whereas, a systematic review and meta-analysis found marked variabilities in estimates of poststroke-fatigue prevalence, ranging from 25% to 85%.² This wide variability across studies has been attributed to the multifactorial features underlying fatigue, the varying times of assessment, and the methodological differences among studies including assessment techniques and diagnostic cut offs-used. A recent study has concluded that the Fatigue Severity Scale can be reliably used for diagnosis of poststroke fatigue, although it lacks specificity.⁵ Moreover, patient characteristics may be associated with differences in poststroke fatigue prevalence.

Low fatigue prevalence has been reported in Asian populations that have different epidemiologies of stroke, due to younger age and a high incidence of hemorrhagic stroke; however, these 2 variables have not been clearly associated to low fatigue prevalence. Cumming et al² hypothesized that a more generalized cultural difference in psychosocial factors might contribute to fatigue.

The aims of this narrative review were (1) to provide an overview of current literature on the definitions, clinical characteristics, time courses, influences on clinical outcome, causes and treatments of poststroke fatigue; (2) to summarize these findings, discuss and suggest existing conceptual models, and highlight controversial issues on poststroke fatigue; (3) to propose steps that could better explain the underlying pathophysiology of poststroke fatigue.

Definition and Clinical Characteristics

A proposed definition of poststroke fatigue is a self-reported perceived lack of physical or mental energy that interferes with daily activities.^6,7 Clinical characteristics of poststroke fatigue have been reported to include self-control and emotional instabilities, reduced mental capacity, as well as a reduction in energy needed for daily activities.⁸

Poststroke fatigue is generally qualitatively different from fatigue experienced before stroke, as the former can be exacerbated by stress and physical exercise, and generally responds well to rest and adequate sleep.⁹ This type of poststroke fatigue, commonly known as exertion fatigue, is experienced typically after intense physical exertion or use of mental effort. It is manifested in the early phase of poststroke as acute episode, with a rapid onset, short duration, and short recovery.^10–12 The other type of poststroke fatigue is chronic fatigue, manifesting in the late phase of poststroke, and characterized by mental and psychological symptoms; the former appears with cognitively demanding tasks, whereas the latter is associated with a lack of interest or poor motivation.¹³ Both types of poststroke fatigue are not considered mutually exclusive, although early fatigue has been reported to be more prevalent in patients after stroke, whereas late fatigue has been reported to be more prevalent in patients with other neurological chronic diseases, including multiple sclerosis.^9,14 Tseng et al¹⁰ reported aerobic fitness and depression to be strong independent predictors of early fatigue and late fatigue, respectively. The authors suggested that these 2 poststroke fatigue types are distinct.

Time Courses and Influences on Outcome

A prospective study has reported that, at 6 months after stroke, approximately half (51%) of all patients complained of fatigue. Of those reporting early fatigue, 69% continued to report fatigue. Whereas, of those reporting late fatigue, 38% had not experienced early fatigue.¹⁵

A Danish study¹⁶ analyzing the course of fatigue over a 2-year follow-up after first-ever stroke found the poststroke fatigue level to decrease over the first 3 months from hospital discharge. This result remained unchanged at 2-year follow-up. Conflicting findings have come from a study by Schepers et al¹⁷ who reported an increase in the prevalence of fatigue during the first year after stroke. This could be explained by the high prevalence of depression in Schepers’s study, as it could have influenced the time course of fatigue.

Regarding the duration of fatigue after stroke, acute fatigue can last up to 6 months, whereas the chronic type can persist in 40% of patients after 2 years.¹⁶ Another study reported fatigue to be still present in one-third of patients up to 6 years after stroke onset.¹⁸ The initial level of fatigue is considered the main predictor of increasing fatigue over time.¹⁹

Several studies have reported poststroke fatigue to be an independent predictor of shorter survival,^20,21 institutionalization,^20,22 poorer functional outcome,^16,23 and greater dependency for activities of daily living along with instrumental activities of daily living.²⁴ Moreover, in young patients, poststroke fatigue has been reported to be a determinant to resuming work, independent of physical disability or cognitive deficit.²⁵ In addition, in patients aged 18 to 50 years, poststroke fatigue has been associated with a poor functional outcome, as assessed by the modified Rankin Scale (odds ratio, 4.0; 95% CI, 1.6–9.6), instrumental activities of daily living (odds ratio 2.2; 95% CI, 1.1–4.6), and impairment in speed of information processing (odds ratio, 2.2; 95% CI, 1.3–3.9) even after almost a decade of follow-up.²⁶

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[Literature Review] Fatigue Models and Poststroke Fatigue – PDF file

Abstract
Poststroke fatigue (PSF) is a common complication affecting a wide range of stroke patients, yet it remains under-reported and underestimated. PSF’s exact underlying cause has not yet been identified and it seems to be multifactorial, with several models developed to answer that question. Identifying the true nature of PSF and its riskfactors would help improve the quality of life of stroke patients. […]

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[Abstract] Change characteristics of health-related quality of life and its association with post-stroke fatigue at four-year follow-up

ABSTRACT

Objective: To explore trajectories that describe change in post-stroke health-related quality of life with fatigue as outcome.

Design: Observational and prospective study.

Subjects: Stroke survivors (N = 144) with predominantly mild or moderate strokes.

Methods: The multidimensional Stroke-Specific Quality of Life scale was used at 1 and 4 years, and the Fatigue Severity Scale at 4 years post-stroke. Latent class growth analyses were used as person-oriented analyses to identify meaningful trajectories. Socio-demographic and stroke-related covariables provided customary adjustment of the outcome, as well as prediction of class membership.

Results: The latent class growth analysis models were estimated for “physical health”, “visual-language”, and “cognitive-social-mental” components of the Stroke-Specific Quality of Life scale, which extracted trajectories describing a variation in stable, deteriorating and improving functional patterns. The stable, well-functioning trajectory was most frequent across all components. More pronounced fatigue was associated with trajectories describing worse functioning, which was more prominent among females compared with males. Living alone implied more fatigue in the “cognitive-social-mental” component. Within the “visual-language” components’ trajectories, younger and older participants reported more fatigue compared with middle-aged participants.

Conclusion: Most participants belonged to the stable, well-functioning trajectories, which showed a consistently lower level of fatigue compared with the other trajectories.

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[Abstract] Fatigue predicts level of community integration in people with stroke

ABSTRACT

Background

The independent predictive power of fatigue for community integration has not been investigated, although there is an increasing amount of literature that recognizes the importance of fatigue in people with stroke.

Objectives

To examine the correlation between community integration and fatigue, walking endurance, and fear of falling; and to quantify the relative contribution of fatigue to community integration in people with stroke.

Methods

This was a cross-sectional study with 75 community-dwelling people with stroke. Data were collected using the Community Integration Measure (CIM), Fatigue Assessment Scale (FAS), 6-minute walk test (6MWT), and Survey of Activities and Fear of Falling in the Elderly (SAFE). Multiple linear regressions (forced entry method) were used to quantify the relative power of the FAS score to predict community integration in a model covering distance in the 6MWT and the SAFE score.

Results

After controlling for age, the CIM score significantly correlated with the scores for FAS (r=-0.48, p < 0.001), 6MWT distance (r = 0.24, p = 0.039), and SAFE (r=-0.39, p = 0.001). The entire model, including age, FAS score, 6MWT distance, and SAFE score, explained 26.1% of the variance in the CIM scores (F [4, 70] = 7.52, p < 0.001). The FAS scores independently explained 10.6% of the variance in the CIM scores.

Conclusions

This study suggests that fatigue is an independent predictor of community integration among people with stroke, taking into account walking endurance and fear of falling.

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