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Record W1856597536 · doi:10.1111/pme.12800

Efficacy and Safety of Duloxetine on Osteoarthritis Knee Pain: A Meta-Analysis of Randomized Controlled Trials

2015· review· en· W1856597536 on OpenAlexaboutno aff
Zhao Yu Wang, Sheng Ying Shi, Shu Jie Li, Feng Chen, Chen Huang, Hai Lin, Jing Lin

Bibliographic record

VenuePain Medicine · 2015
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersGuangzhou Science and Technology Program key projectsNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsDuloxetineMedicineJadad scaleMeta-analysisRandomized controlled trialPlaceboOsteoarthritisCochrane LibraryAdverse effectRelative riskConfidence intervalPhysical therapyWOMACDuloxetine HydrochlorideMEDLINEInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this meta-analysis was to evaluate the efficacy and safety of duloxetine for management of osteoarthritis knee (OAK) pain. METHODS: A systematic literature search of articles for management of OAK using duloxetine were performed in PubMed, EBSCO, EMBASE, ScienceDirect, MEDLINE, ClinicalTrials.gov, Google Scholar, and Cochrane Central Register of Controlled Trials from the available date of inception until the latest issue (October 2013). Potentially relevant randomized controlled trials (RCTs) regarding to comparison of efficacy and safety of duloxetine with placebo for managing OAK pain were included. Also, studies with specific data regarding to pain reductions and response rate, Patient Global Impression of Improvement (PGI-I), functional improvement, Western Ontario and McMaster Osteoarthritis Index (WOMAC), adverse events (AEs), treatment-emergent AEs (TEAEs), mortality were included and analyzed, and those with confounding conditions were excluded. Studies were assessed for quality using the Jadad five-point score for RCTs. Finally, a meta-analysis of all RCTs eligible for inclusion criteria was performed using Review Manager 5.1 meta-analysis software. RESULTS: Three RCTs that enrolled 1,011 patients were included in our meta-analysis. There were statistically significant differences between patients taking duloxetine and those taking placebo with regard to the reductions in pain intensity (992 patients, mean difference [MD] = -0.88, 95% confidence interval [CI] -1.11--0.65, P < 0.0001), a moderate improvement in pain intensity (>= 30% response rate; 989 patients, risk ratio [RR] = 1.49, 95% CI 1.31-1.70, P < 0.0001), a substantial improvement in pain intensity (>=50% response rate; 989 patients, RR = 1.69, 95% CI 1.27-2.25, P = 0.0004). Statistically significant differences in PGI-I (976 patients, MD = -0.47, 95% CI -0.63 to -0.30, P < 0.0001) and WOMAC-physical function subscale (977 patients, MD = -4.25, 95% CI -5.82 to -2.68, P < 0.0001) were observed. Similarly, more AEs, TEAEs, and discontinuations for any reason were associated with the use of duloxetine than with placebo (1,011 patients, RR = 2.15, 95% CI 1.48-3.11, P < 0.0001; 1,011 patients, RR = 1.32, 95% CI 1.16-1.49, P < 0.0001; 1,011 patients, RR = 1.43, 95% CI 1.14-1.78, P = 0.002, respectively). However, differences in serious AEs were not significantly statistically different. Moreover, no deaths occurred during these three studies. CONCLUSION: This analysis suggests duloxetine (60/120 mg quaque die (QD)), compared with placebo control, resulted in a greater reduction in pain, improved function and patient-rated impression of improvement, and acceptable adverse effects for the treatment of OAK pain after approximately 10-13 weeks of treatment.

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)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.043
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0260.074
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.116
GPT teacher head0.376
Teacher spread0.260 · 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 designMeta-analysis
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

Citations104
Published2015
Admission routes1
Has abstractyes

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