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Corticosteroid injection versus platelet-rich plasma in the management of knee osteoarthritis: A comparative clinical study

2025· article· en· W7082653381 on OpenAlexaboutno aff

Bibliographic record

VenueInternational Journal of Orthopaedics Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInsurance, Mortality, Demography, Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsCorticosteroidWOMACOsteoarthritisVisual analogue scaleClinical studyTriamcinolone acetonideRandomized controlled trialProspective cohort study

Abstract

fetched live from OpenAlex

Background: Knee osteoarthritis (OA) is a prevalent degenerative joint disorder causing pain and disability. Intra-articular corticosteroid (CS) injections provide short-term relief, while plateletrich plasma (PRP) has emerged as a regenerative option with potentially longer benefits. Objective: To compare the efficacy of intra-articular corticosteroid versus PRP injections in patients with symptomatic knee osteoarthritis. Methods: A prospective randomized comparative study was conducted on 60 patients with Kellgren-Lawrence grade II-III knee OA. Group A (n = 30) received a single intra-articular corticosteroid injection (triamcinolone acetonide 40 mg). Group B (n = 30) received three PRP injections at weekly intervals. Outcomes were assessed using the Visual Analogue Scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at baseline, 6 weeks, 3 months, and 6 months. Results: Both groups showed significant pain reduction at 6 weeks. Group A improved from 7.2± 1.0 to 3.1±1.2, while Group B improved from 7.4±1.1 to 3.4±1.0 (p > 0.05). At 3 and 6 months, PRP maintained superior improvement (VAS 2.1±0.9; WOMAC 34.2±6.5) compared to corticosteroid (VAS 4.5±1.2; WOMAC 51.7±8.3) (p

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.072
GPT teacher head0.428
Teacher spread0.356 · 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 designNon-randomized trial
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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