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Record W7122720290 · doi:10.5336/anesthe.2025-114827

Retrospective Evaluation of the Effectiveness of Intra-Articular Steroid, Hyaluronic Acid and Ozone Injection in the Treatment of Chronic Hip Pain Due to Osteoarthritis

2025· article· en· W7122720290 on OpenAlexaboutno aff
Dostali ALİYEV, Ümit Akkemik

Bibliographic record

VenueTurkiye Klinikleri Journal of Anesthesiology Reanimation · 2025
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Ozone Research
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACOsteoarthritisVisual analogue scaleHyaluronic acidChronic painRetrospective cohort study

Abstract

fetched live from OpenAlex

Objective: The treatment of chronic hip pain due to osteoarthritis is usually symptomatic, and a wide variety of treatment methods can be used. Intra-articular drug injections are frequently used among the treatment methods. This study aims to compare the effectiveness of intra-articular steroid hyaluronic acid and ozone injections in the treatment of hip osteoarthritis, retrospectively. Material and Methods: Clinical data of 119 patients treated with intra-articular steroid (n=40, Group I), hyaluronic acid (n=39, Group II), and ozone (n=40, Group III) were retrospectively analyzed. Demographic data of the patients, Visual Analog Scale (VAS) before and 1st and 3rd month after the procedure, the Western Ontario and McMaster Universities Arthritis Index (WOMAC) scales were recorded. Results: The patients' pain scores before and after the procedure (month 1 and month 3) are as follows: VAS (Group I: 8.10→3.43→2.23), (Group II: 7.05→4.08→3.46), (Group III: 7.08→3.75→3.00). WOMAC (Group I: 45.83→22.39→16.34), (Group II: 46.29→28.11→27.74), (Group III: 46.42→26.71→26.06). Conclusion: It was observed that the applied treatment methods were effective and a significant reduction was found in the VAS and WOMAC scores of the patients in all 3 groups. In the comparison between the groups, it was seen that steroid injection provided better pain control than other methods (p<0.042).

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.278

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.314
Teacher spread0.291 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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