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Carnitine for fatigue in multiple sclerosis

2010· reference-entry· en· W4251412183 on OpenAlexaff
Aaron M Tejani, Michael Wasdell, Rae Spiwak, Greg Rowell, Shabita Nathwani

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2010
Typereference-entry
Languageen
Field
Topic
Canadian institutionsUniversity of British ColumbiaBurnaby HospitalFraser Health
Fundersnot available
KeywordsMedicineRandomized controlled trialCochrane LibraryMEDLINEData extractionClinical trialAdverse effectRandomizationPhysical therapyMultiple sclerosisMeta-analysisQuality of life (healthcare)Internal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Fatigue is reported to occur in up to 92% of patients with multiple sclerosis (MS) and has been described as the most debilitating of all MS symptoms by 28% to 40% of MS patients. OBJECTIVES: To assess whether carnitine (enteral or intravenous) supplementation can improve the quality of life and reduce the symptoms of fatigue in patients with MS-related fatigue and to identify any adverse effects of carnitine when used for this purpose. SEARCH STRATEGY: A literature search was performed using Cochrane MS Group Trials Register (21 May 2009), Cochrane Central Register of Controlled Trials (CENTRAL) "The Cochrane Library 2009, issue 2, MEDLINE (PubMed) (1966-21 May 2009), EMBASE (1974-21 May 2009). Reference lists of review articles and primary studies were also screened. A hand search of the abstract book of recent relevant conference symposia was also conducted. Personal contact with MS experts and a manufacturer (Source Naturals, United States) of carnitine formulation was contacted to determine if they knew of other clinical trials. No language restrictions were applied. SELECTION CRITERIA: Full reports of published and unpublished randomized controlled trials and quasi-randomized trials of any carnitine intervention in adults with a clinical diagnosis of fatigue associated with multiple sclerosis were included. DATA COLLECTION AND ANALYSIS: Data from the eligible trials was extracted and coded using a standardized data extraction form and entered into RevMan 5. Discrepancies were to be resolved by discussion with a third reviewer however this was not necessary. The quality items to be assessed were method of randomization, allocation concealment, blinding (participants, investigators, outcome assessors and data analysis), intention-to-treat analysis and completeness of follow up. MAIN RESULTS: The search identified one randomized cross-over trial. In this study patients were exposed to both acetyl L-carnitine (ALCAR(tm)) 2 grams daily and amantadine 200 mg daily in adult patients with relapsing-remitting and secondary progressive MS. The effects of carnitine on fatigue are not clear based on the one included crossover RCT. There was no difference between carnitine and amantadine for the number of patients withdrawing from the study due to an adverse event (relative risk ratio 0.20; 95% confidence interval 0.03 to 1.55. Mortality, serious adverse events, total adverse events, and quality of life were not reported. AUTHORS' CONCLUSIONS: There is insufficient evidence that carnitine for the treatment of MS-related fatigue offers a therapeutic advantage over placebo or active comparators.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.265
GPT teacher head0.369
Teacher spread0.103 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations14
Published2010
Admission routes1
Has abstractyes

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