Trajectories of fatigue among stroke patients from the acute phase to 18 months post-injury: A latent class analysis

Kjeverud, Anita; Østlie, Kristin; Schanke, Anne‐Kristine; Thoresen, Magne; Lerdal, Anners

doi:10.1371/journal.pone.0231709

Cited by 23 publications

(34 citation statements)

References 29 publications

(35 reference statements)

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“…In line with the findings of previous studies (Acciarresi et al, 2014;Kjeverud et al, 2020), the bidirectional relationship between depression and insomnia played a prominent role in the occurrence of PSF. Although fatigue is a characteristic symptom of depression, PSF and post-stroke depression also share common risk factors, such as functional impairments (MacIntosh et al, 2017).…”

Section: Discussionsupporting

confidence: 91%

“…There might be numerous potential explanations for this finding, including pre-existing disease, poor health, lifestyle factors, vulnerability to stress, and mental health conditions (Kjeverud et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…In the univariate and multivariate analyses, pre‐stroke fatigue was correlated to post‐stroke fatigue, consistent with previous findings (Lerdal et al., 2011). There might be numerous potential explanations for this finding, including pre‐existing disease, poor health, lifestyle factors, vulnerability to stress, and mental health conditions (Kjeverud et al., 2020).…”

Section: Discussionmentioning

confidence: 99%

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Predictors and short‐term outcomes of post‐stroke fatigue in initial phase of transition from hospital to home: A prospective observational study

Asamoto

Yuki

et al. 2020

Journal of Advanced Nursing

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Aim To analyse the interactions of associated factors with post stroke fatigue (PSF) after discharge home and determine the predictors of PSF and their impact on stroke survivors. Design A prospective observational study. Methods A total of 94 patients with acute stroke were recruited between May 2019 ‐July 2020. The main outcomes were fatigue, depression, insomnia, sarcopenia, and health‐related quality of life (HRQOL) and were assessed at admission and 1 month after discharge. Fatigue was measured using the Fatigue Assessment Scale. Depression and Insomnia were assessed using the Hospital Anxiety and Depression Scale‐Depression and Insomnia Severity Index, respectively. Sarcopenia was measured using the SARC‐F questionnaire, and HRQOL was assessed using the Short Form‐8. Results Acute phase PSF was an independent predictor of PSF after discharge home. Moreover the path analysis revealed that this effect is mediated through both the direct effect of acute‐phase PSF on PSF after discharge home and through the indirect effect of interaction with pre‐stroke SARC‐F, acute phase depression, and acute phase insomnia, which remains a separate predictor of acute‐phase PSF. In total, 17% of the survivors had persistent PSF. Persistent PSF was significantly associated with depression, insomnia, sarcopenia, and a lower quality of life scores. Conclusions Post‐stroke fatigue may occur in the acute phase and persists after discharge, it will not only affect later depression, insomnia, and quality of life, but also sarcopenia. Impact Acute phase PSF was found to be an independent predictor of PSF after discharge home. In addition, the interaction with pre‐stroke SARC‐F, acute phase depression and insomnia had an indirect connection with PSF after discharge home, which remains a separate predictor of acute‐phase PSF. Thus, early assessment and management of mental status, sleep problems, and sarcopenia during hospitalization might be an important step in post‐stroke rehabilitation and home transition.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Predictors and short‐term outcomes of post‐stroke fatigue in initial phase of transition from hospital to home: A prospective observational study

Asamoto

Yuki

et al. 2020

Journal of Advanced Nursing

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“…Kjeverud et al. (2020) identified low, moderate and high latent classes of fatigue trajectories over 18 months and severity was stable over time. In this sample, overall median fatigue scores indicated survivors were fatigued at 1‐month post‐stroke, but scores were just above the cut‐off (>22).…”

Section: Discussionmentioning

confidence: 99%

Socio‐ecological perspective on factors influencing acute recovery of younger stroke survivors: A mixed methods study

Walker

González-Guarda

Yang

et al. 2021

Journal of Advanced Nursing

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Aims Stroke is affecting an increasing number of young and middle‐aged adults. Given the substantial diversion from anticipated life trajectories that younger stroke survivors experience as a result of their stroke deficits, their health‐related quality of life (HRQOL) is likely to be negatively impacted during the immediate post‐acute recovery period. The aim of this study was to generate a comprehensive understanding of the influences on HRQOL and acute recovery during the first three months following stroke for younger adults using a socio‐ecological perspective. Design Longitudinal, convergent mixed methods design. Methods HRQOL survey data, assessed using the Patient Generated Index (N = 31), and qualitative interview data about survivors’ recovery experiences (N = 20) were collected. Simple linear regression and effect size results were integrated with themes and sub‐themes identified from conventional content analysis using joint data displays. Results Depression and fatigue negatively affected recovery at the individual level. At the family and societal level, family functioning, social support including being married, having insurance, working, adequate income and being unemployed post‐stroke all positively impacted recovery. Qualitative findings revealed determination, coping, and accessing healthcare to positively affect recovery though a meta‐inference could not be drawn as no quantitative data addressed these concepts. Conclusion A variety of factors intersecting across socio‐ecological levels were perceived by young stroke survivors to influence acute recovery experiences and outcomes. Impact This study identified individual‐, family‐ and societal‐level factors in younger adults’ environments that may affect the acute stroke recovery experience. Findings underscore the need for research and clinical approaches that consider environmental factors at multiple levels of influence when supporting stroke recovery for younger adults.

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“…FSS scores are usually reported as mean values (lowest mean 1, highest mean 7), where higher scores indicate higher fatigue impact. The cut-off for clinically significant fatigue applied in the literature is either ≥ 4 (Nadarajah & Goh, 2015;Schepers, Visser-Meily, Ketelaar, & Lindeman, 2006) or ≥ 5 (Kjeverud et al, 2020;Lerdal, Wahl, Rustoen, Hanestad, & Moum, 2005;Morsund et al, 2019;Naess, Lunde, Brogger, & Waje-Andreassen, 2012). A cut-off of ≥ 5 has been recommended to prevent overestimation of cases, as a cut-off of ≥ 4 resulted in 42% of healthy controls being identified as fatigued in a large (N=1800) Norwegian sample (Lerdal et al, 2005).…”

Section: Fatigue and Depression Self-report Measuresmentioning

confidence: 99%

No effect of tDCS on fatigue and depression in chronic stroke patients: an exploratory randomized sham-controlled trial combining tDCS with computerized cognitive training

Ulrichsen

Richard

et al. 2021

Preprint

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Fatigue and emotional distress rank high among self-reported unmet needs in stroke survivors. Currently, few treatment options exist for post stroke fatigue, a condition frequently associated with depression. Non-invasive brain stimulation techniques such as transcranial direct current stimulation (tDCS) have shown promise in alleviating fatigue and depression in other patient groups, but the acceptability and effects for chronic phase stroke survivors are not established. Here, we used a randomized sham-controlled design to evaluate the added effect of tDCS combined with computerized cognitive training to alleviate symptoms of fatigue and depression. 74 patients were enrolled at baseline (mean time since stroke = 26 months) and 54 patients completed the intervention. Self-report measures of fatigue and depression were collected at five consecutive timepoints, spanning a period of two months. While fatigue and depression severity were reduced during the course of the intervention, Bayesian analyses provided evidence for no added effect of tDCS. Less severe symptoms of fatigue and depression were associated with higher improvement rate in select tasks, and study withdrawal was higher in patients with more severe fatigue and younger age. Time-resolved analyses of individual symptoms by a network-approach suggested overall higher centrality of fatigue symptoms (except item 1 and 2) than depression symptoms. In conclusion, the results support the notion of fatigue as a significant stroke sequela with possible implications for treatment adherence and response, but reveal no effect of tDCS on fatigue or depression.

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Trajectories of fatigue among stroke patients from the acute phase to 18 months post-injury: A latent class analysis

Cited by 23 publications

References 29 publications

Predictors and short‐term outcomes of post‐stroke fatigue in initial phase of transition from hospital to home: A prospective observational study

Predictors and short‐term outcomes of post‐stroke fatigue in initial phase of transition from hospital to home: A prospective observational study

Socio‐ecological perspective on factors influencing acute recovery of younger stroke survivors: A mixed methods study

No effect of tDCS on fatigue and depression in chronic stroke patients: an exploratory randomized sham-controlled trial combining tDCS with computerized cognitive training

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