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Record W2472390870 · doi:10.1055/s-0036-1584560

The Effect of Synovectomy in Total Knee Arthroplasty for Primary Osteoarthritis: A Meta-Analysis

2016· review· en· W2472390870 on OpenAlexaff
Marcia Clark, Sahil Kooner

Bibliographic record

VenueThe Journal of Knee Surgery · 2016
Typereview
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineOsteoarthritisSynovectomyPerioperativeRandomized controlled trialConfidence intervalArthroplastySurgeryMeta-analysisRange of motionTotal knee arthroplastyInternal medicineRheumatoid arthritis

Abstract

fetched live from OpenAlex

The objective of this study is to assess pain, function, and morbidity in patients undergoing synovectomy during primary total knee arthroplasty (TKA) for osteoarthritis (OA). A meta-analysis, which included randomized controlled trials comparing TKA with and without synovectomy for OA, was completed. The primary outcome was postoperative knee pain. Secondary outcomes included performance, perioperative complications, validated functional scores, operation length, and hospitalization length. A literature search produced 487 unique references, of which 3 randomized controlled trials were selected for inclusion. A total of 304 patients (354 knees) were included, with an average age of 67 years. Follow-up intervals between studies ranged from 26 weeks to 12 months. Included studies were of moderate- to high-quality evidence with low risk of bias. There was no significant difference between the two groups in regard to postoperative pain, Knee Society Score, or postoperative range of motion. Postoperative blood loss was significantly lower in synovium-retaining TKA group (MD = 99.41 mL; 95% confidence interval, 45.08-153.75). Based on these results, there is currently no evidence to support the use of synovectomy in TKA for primary OA, as it provides no clinical benefit and increases postoperative blood loss.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0110.013
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.308
Teacher spread0.273 · 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 designOther design
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

Citations13
Published2016
Admission routes1
Has abstractyes

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