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Record W2018364660 · doi:10.2340/16501977-0216

A randomized controlled trial of acupuncture added to usual treatment for fibromyalgia

2008· article· en· W2018364660 on OpenAlexaff
RA Targino, Marta Imamura, HHS Kaziyama, LPM Souza, WT Hsing, Andrea D Furlan, ST Imamura, RS Azevedo Neto

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsInstitute for Work & Health
Fundersnot available
KeywordsFibromyalgiaAcupuncturePhysical therapyMedicineRandomized controlled trialQuality of life (healthcare)Visual analogue scaleInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the effectiveness of acupuncture for fibromyalgia. METHODS: Fifty-eight women with fibromyalgia were allocated randomly to receive either acupuncture together with tricyclic antidepressants and exercise (n=34), or tricyclic antidepressants and exercise only (n=24). Patients rated their pain on a visual analogue scale. A blinded assessor evaluated both the mean pressure pain threshold value over all 18 fibromyalgia points and quality of life using SF-36. RESULTS: At the end of 20 sessions, patients who received acupuncture were significantly better than the control group in all measures of pain and in 5 of the SF-36 subscales. After 6 months, the acupuncture group was significantly better than the control group in numbers of tender points, mean pressure pain threshold at the 18 tender points and 3 subscales of SF-36. After one year, the acupuncture group showed significance in one subscale of the SF-36; at 2 years there were no significant differences in any outcome measures. CONCLUSION: Addition of acupuncture to usual treatments for fibromyalgia may be beneficial for pain and quality of life for 3 months after the end of treatment. Future research is needed to evaluate the specific effects of acupuncture for fibromyalgia.

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)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.356
Teacher spread0.323 · 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 designRandomized trial
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

Citations84
Published2008
Admission routes1
Has abstractyes

Explore more

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