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Record W2996788002 · doi:10.1177/0300060519895868

The efficacy and safety of Botulinum Toxin Type A in painful knee osteoarthritis: a systematic review and meta-analysis

2019· review· en· W2996788002 on OpenAlexaboutno aff
Shuchao Zhai, Botao Huang, Kai Yu

Bibliographic record

VenueJournal of International Medical Research · 2019
Typereview
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisOsteoarthritisBotulinum toxinSystematic reviewMEDLINEPhysical therapySurgeryAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: A systematic review and meta-analysis was carried out to evaluate the efficacy and safety of Botulinum Toxin Type A in painful knee osteoarthritis. METHODS: The EMBASE and MEDLINE databases were searched to identify randomized controlled trials (RCTs) of Botulinum Toxin Type A in the treatment of painful knee osteoarthritis. The references of included literature were also searched. RESULTS: Five articles involving 5 RCTs including 314 patients were included in this analysis. There was a significant difference between Botulinum Toxin Type A and placebo in the visual analog scale (VAS) pain scale and Western Ontario & McMaster Universities Osteoarthritis Index (WOMAC) questionnaire score in both the short-term (≤4 weeks) and long-term (≥8 weeks) treatment period. There were no serious adverse events in the Botulinum Toxin Type A groups. CONCLUSIONS: This meta-analysis suggests that Botulinum Toxin Type A is effective and safe in the painful knee OA treatment. However, high-quality randomized controlled studies are still needed to further confirm our findings.

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)0.013
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.029
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.146
GPT teacher head0.458
Teacher spread0.312 · 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

Citations24
Published2019
Admission routes1
Has abstractyes

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Same venueJournal of International Medical ResearchSame topicBotulinum Toxin and Related Neurological DisordersFrench-language works237,207