MétaCan
Menu
Back to cohort
Record W2286243886

Fatigue in Progressive Neurological Conditions: A Literature Review

2013· review· en· W2286243886 on OpenAlexaff
Setareh Ghahari, Shahriar Parvaneh, Tanya Packer

Bibliographic record

VenueIranian Rehabilitation Journal · 2013
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsDalhousie UniversityQueen's University
Fundersnot available
KeywordsPsychosocialQuality of life (healthcare)Multiple sclerosisRehabilitationPsychological interventionDiseasePhysical therapyPsychologyPhysical medicine and rehabilitationPsychiatryPoliomyelitisMedicineClinical psychologyPediatricsPsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

This paper reviews the current literature examining the pervasive symptom of fatigue experienced in three of the most common degenerative neurological conditions: multiple sclerosis (MS), Parkinson’s disease (PD) and post-polio syndrome (PPS). The existing literature can be considered under four headings; definition and prevalence, type, cause, impact of fatigue. Fatigue is a common symptom in degenerative conditions and has physical, cognitive and psychosocial manifestations. Although the causes of fatigue seem to differ between conditions, its pattern, with few exceptions, is very similar regardless of diagnosis. The literature consistently shows that the impact of fatigue on the person’s physical and mental performance considerably increasing the risk of unemployment and reduced quality of life. Fatigue is one of the most disabling symptoms in degenerative neurological conditions. With few pharmacological solutions, non-pharmacological solutions for fatigue management should be considered when determining rehabilitation interventions for this group of people.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.103
GPT teacher head0.446
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueIranian Rehabilitation JournalSame topicMultiple Sclerosis Research StudiesFrench-language works237,207