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Record W1960216402 · doi:10.1186/s13063-015-0961-1

Nortriptyline in knee osteoarthritis (NortIKA Study): study protocol for a randomised controlled trial

2015· article· en· W1960216402 on OpenAlexaboutno aff
Ben Hudson, Jonathan Williman, Lisa K. Stamp, John Alchin, Gary J. Hooper, Dee Mangin, Bronwyn F. Thompson, Les Toop

Bibliographic record

VenueTrials · 2015
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersHealth Research Council of New Zealand
KeywordsMedicineNortriptylinePlaceboOsteoarthritisPhysical therapyClinical trialRandomized controlled trialWOMACTricyclic antidepressantAdverse effectAnalgesicAlternative medicineAmitriptylineAnesthesiaAntidepressantInternal medicinePsychiatryAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: Osteoarthritis (OA) is a common cause of pain and disability. Currently available analgesics are often insufficiently effective or have unacceptable adverse effects. Tricyclic antidepressants may offer a useful centrally-acting analgesic. Nortriptyline is a readily-available, cheap and comparatively well-tolerated tricyclic antidepressant. METHODS/DESIGN: We will conduct a parallel group, two-arm, participant and investigator-blinded, randomised controlled superiority trial comparing nortriptyline with placebo. Two hundred participants with primary knee OA will be enrolled. Participants will take study medication for 14 weeks. The primary outcome is difference between treatment arms in mean pain score measured on the Western Ontario and McMaster Universities (WOMAC) pain scale at 14 weeks. DISCUSSION: This protocol describes the first randomised controlled trial of a tricyclic antidepressant in the treatment of OA. The results of the study may have significant implications for the management of this common and painful condition. TRIAL REGISTRATION: The trial was registered with the Australian New Zealand Clinical Trials Registry on 27 June 2014. The trial registration number is: ACTRN12614000683639 .

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)0.010
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.133
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
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 head0.143
GPT teacher head0.424
Teacher spread0.281 · 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
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
Published2015
Admission routes1
Has abstractyes

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