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Record W4399927959 · doi:10.1136/bmjopen-2024-087180

PRECISE trial (Pain RElief Combination Intervention StratEgies): protocol for the clinical trial of a pregabalin–melatonin combination for fibromyalgia

2024· article· en· W4399927959 on OpenAlexafffundabout
Ian Gilron, Chris DeBow, Hala Elkerdawy, James S. Khan, Tim V. Salomons, D. W. Scott, Dongsheng Tu, Ronald R. Holden, Roumen Milev, D. Norman Buckley, Dwight E. Moulin

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsWestern UniversityMount Sinai HospitalKingston Health Sciences CentreQueen's UniversityMcMaster UniversityProvidence Health Care
FundersInstitute of Musculoskeletal Health and ArthritisQueen's University
KeywordsMedicineFibromyalgiaPregabalinMelatoninClinical trialPhysical therapyAlternative medicineIntervention (counseling)Randomized controlled trialProtocol (science)PsychiatryInternal medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Fibromyalgia is associated with chronic widespread pain and disturbed sleep. Multidisciplinary, multimodal management often includes pharmacotherapy; however, current drugs used to treat fibromyalgia provide meaningful benefit to only 30-60% of treated individuals. Combining two or more different drugs is common in clinical practice with the expectation of better efficacy, tolerability or both; however, further research is needed to identify which combinations actually provide added benefit. Thus, we are planning a clinical trial to evaluate melatonin (MLT)-pregabalin (PGB) combination in participants with fibromyalgia. METHODS AND ANALYSIS: This will be a single-centre, double-blind, randomised, double-dummy, three-period, crossover trial comparing a MLT-PGB combination to each monotherapy in 54 adult participants satisfying the 2016 American College of Rheumatology criteria for fibromyalgia. Participants will receive maximally tolerated doses of MLT, PGB and MLT-PGB combination for 6 weeks. The primary outcome will be daily pain intensity (0-10); secondary outcomes will include the Fibromyalgia Impact Questionnaire, SF-36 survey, Medical Outcomes Study Sleep Scale, Beck Depression Inventory (BDI-II), adverse events and other measures. Analysis of the primary and secondary outcomes will involve a linear mixed model with sequence, period, treatment, the first-order carryover and baseline pain score as fixed effects and participant as a random effect to test whether there are any treatment differences among three treatments and to estimate the least square mean of the mean daily pain intensity for each treatment, adjusting for carryover as well as period effects (ie, stability of pain levels). ETHICS AND DISSEMINATION: This trial has been registered with the International Standard Randomised Controlled Trial Number Registry, ISRCTN #18278231, has been granted ethical approval by the Queen's University Health Sciences Research Ethics Board (Queen's HSREB Protocol #6040998) and is currently under review for a Clinical Trial Application to Health Canada Natural and Non-prescription Health Products Directorate. All participants will provide written informed consent prior to trial participation. Following trial completion, results will be disseminated in one or more biomedical journal publications and presented at one or more scientific meetings. TRIAL REGISTRATION NUMBER: This trial has been registered with the International Standard Randomised Controlled Trial Number Registry, ISRCTN18278231.

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)0.024
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.149
Threshold uncertainty score0.497

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.022
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0090.005
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.1490.031

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 head0.211
GPT teacher head0.538
Teacher spread0.326 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations5
Published2024
Admission routes3
Has abstractyes

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