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Record W4412039155 · doi:10.1186/s12891-025-08811-9

Efficacy of hydrolyzed collagen injections compared to platelet-rich plasma and hyaluronic acid in the treatment of patients with symptomatic knee osteoarthritis: a retrospective clinical study

2025· article· en· W4412039155 on OpenAlexaboutno aff
Angel Alberto Heredia Sulbaran

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2025
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePlatelet-rich plasmaOsteoarthritisHyaluronic acidWOMACRetrospective cohort studyInternal medicineRheumatologyViscosupplementationSurgeryPlateletPathology

Abstract

fetched live from OpenAlex

BACKGROUND/OBJECTIVES: Hydrolyzed collagen (CHG) is an emerging infiltrative therapy for the treatment of osteoarthritis. The objective of this retrospective study was to compare its effectiveness with that of hyaluronic acid (HA) and platelet-rich plasma (PRP). METHODS: The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores of 72 patients with Kellgren-Lawrence grade 1-4 osteoarthritis were recorded and analyzed over a 12-month follow-up period. Patients received either three CHG injections, a single HA injection, or three PRP injections and the results were compared. Of the participants, 23 were treated with CHG, 25 with HA, and 24 with PRP. RESULTS: Treatment effectiveness was assessed at 3, 6, and 12 months. At the 12-month follow-up, the CHG group showed a 56% improvement in the WOMAC total score, compared to 22.5% for the HA group and 47% for the PRP group. Pain reduction was also greatest in the CHG group, with a 52% decrease at 12 months, versus 16% in the HA group (p < 0.05). CONCLUSIONS: In this retrospective study, CHG demonstrated a more sustained therapeutic effect in terms of pain relief and functional improvement compared to HA and PRP over a one-year period. No side effects were observed in any of the treatment groups.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.304
Teacher spread0.292 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2025
Admission routes1
Has abstractyes

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