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Record W2002022295 · doi:10.1155/2013/898493

Opioid Use in Fibromyalgia Is Associated with Negative Health Related Measures in a Prospective Cohort Study

2013· article· en· W2002022295 on OpenAlexafffund
Mary‐Ann Fitzcharles, Neda Faregh, Peter A. Ste‐Marie, Yoram Shir

Bibliographic record

VenuePain Research and Treatment · 2013
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsMcGill UniversityUniversité de MontréalMcGill University Health CentreMontreal General Hospital
FundersLouise and Alan Edwards Foundation
KeywordsMedicineFibromyalgiaOpioidTramadolAdverse effectChronic painDiseasePhysical therapyIntensive care medicineInternal medicineAnesthesiaAnalgesic

Abstract

fetched live from OpenAlex

As pain is the cardinal symptom of fibromyalgia (FM), strategies directed towards pain relief are an integral component of treatment. Opioid medications comprise a category of pharmacologic treatments which have impact on pain in various conditions with best evidence for acute pain relief. Although opioid therapy other than tramadol has never been formally tested for treatment of pain in FM, these agents are commonly used by patients. We have examined the effect of opioid treatments in patients diagnosed with FM and followed longitudinally in a multidisciplinary pain center over a period of 2 years. In this first study reporting on health related measures and opioid use in FM, opioid users had poorer symptoms and functional and occupational status compared to nonusers. Although opioid users may originally have had more severe symptoms at the onset of disease, we have no evidence that these agents improved status beyond standard care and may even have contributed to a less favourable outcome. Only a formal study of opioid use in FM will clarify this issue, but until then physicians must be vigilant regarding the multiple adverse consequences of opioid therapy.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.345
Teacher spread0.284 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations63
Published2013
Admission routes2
Has abstractyes

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