Evidence map›Paper›PMID 33368578›Full record

Observational studyJournal of advanced nursing2021

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

Ya Su, Mitsuko Asamoto, Michiko Yuki, Masaru Saito, Naoko Hasebe, Kengo Hirayama, Mika Otsuki, Chieko Iino

Registry-linked trialOpen access · hybridAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Journal of advanced nursing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06255145 (Assessment of Body Composition, Fatigue, Mobility and Functional Status in Post-Stroke Individuals), which is not on this map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06255145 nacompletednot on this map

Assessment of Body Composition, Fatigue, Mobility and Functional Status in Post-Stroke Individuals

TypeinterventionalSponsorPamukkale UniversityRan2021 to 2022Enrolled42ConditionsCerebrovascular Stroke, Body CompositionArmsBioelectrical Impedance Analysis
3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Biological, Psychiatric, Psychosocial, and Cognitive Factors of Poststroke Depression.International journal of environmental research and public health · 2023
    Article
  5. Review
  6. Review
  7. Article
  8. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Ya SuGraduate School of Health Sciences, Hokkaido University, Sapporo, Japan.ORCID https://orcid.org/0000-0002-3739-3587
Mitsuko AsamotoNursing Department, Sapporo Azabu Neurosurgical Hospital, Sapporo, Japan.
Michiko YukiFaculty of Health Sciences, Hokkaido University, Sapporo, Japan.ORCID https://orcid.org/0000-0002-8544-4545
Masaru SaitoNursing Department, Sapporo Azabu Neurosurgical Hospital, Sapporo, Japan.
Naoko HasebeNursing Department, Sapporo Azabu Neurosurgical Hospital, Sapporo, Japan.
Kengo HirayamaFaculty of Health Sciences, Hokkaido University, Sapporo, Japan.
Mika OtsukiFaculty of Health Sciences, Hokkaido University, Sapporo, Japan.
Chieko IinoNursing Department, Sapporo Azabu Neurosurgical Hospital, Sapporo, Japan.
Sapporo Azabu Neurosurgical Hospital · JPSapporo University · JP

Funding

Yuumi Memorial Foundation for Home Health Care 2018
6 · The paper itself

Abstract

aimTo 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.

designA prospective observational study.

methodsA 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.

resultsAcute 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.

conclusionsPost-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.

Indexed as

Quality of LifeStrokeDepressionFatigueHospitalsHumansSeverity of Illness Indexdepressionfatigueinsomnianursingquality of lifesarcopeniastroke

Identifiers

PMID33368578
PMCPMC8048815
OpenAlexW3114335087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.