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Record W2120518759 · doi:10.1186/ar4441

Review of pharmacological therapies in fibromyalgia syndrome

2014· review· en· W2120518759 on OpenAlexaff
Winfried Häuser, Brian Walitt, Mary‐Ann Fitzcharles, Claudia Sommer

Bibliographic record

VenueArthritis Research & Therapy · 2014
Typereview
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineDuloxetineTolerabilityObservational studyFibromyalgiaPregabalinIntensive care medicineMilnacipranPharmacotherapyAmitriptylineClinical trialDrugPhysical therapyAlternative medicineInternal medicineAdverse effectPharmacologyPsychiatryAntidepressant

Abstract

fetched live from OpenAlex

This review addresses the current status of drug therapy for the management of fibromyalgia syndrome (FMS) and is based on interdisciplinary FMS management guidelines, meta-analyses of drug trial data, and observational studies. In the absence of a single gold-standard medication, patients are treated with a variety of drugs from different categories, often with limited evidence. Drug therapy is not mandatory for the management of FMS. Pregabalin, duloxetine, milnacipran, and amitriptyline are the current first-line prescribed agents but have had a mostly modest effect. With only a minority of patients expected to experience substantial benefit, most will discontinue therapy because of either a lack of efficacy or tolerability problems. Many drug treatments have undergone limited study and have had negative results. It is unlikely that these failed pilot trials will undergo future study. However, medications, though imperfect, will continue to be a component of treatment strategy for these patients. Both the potential for medication therapy to relieve symptoms and the potential to cause harm should be carefully considered in their administration.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.122
GPT teacher head0.446
Teacher spread0.324 · 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

Citations180
Published2014
Admission routes1
Has abstractyes

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