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Record W4407699927 · doi:10.1201/9781003618140-4

A Case Series on Evaluation of Functional Outcome of Intra Articular Hyaluronic Acid Injection in Early Osteroarthritis of Knee

2025· book-chapter· en· W4407699927 on OpenAlexaboutno aff
Madhukar ., Rajlaxmi Reddy, Venkata Kiran Pillella, Aizel Sherief, H Pushkin Raj, Abraham Antony, Ganesh Ramesh

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsHyaluronic acidSeries (stratigraphy)Intra articularOutcome (game theory)MedicineSurgeryOsteoarthritisMathematicsPathologyAnatomyGeologyAlternative medicineMathematical economics

Abstract

fetched live from OpenAlex

Early-stage OA management focuses on pain relief and improving muscle strength and range of motion. This study evaluates the functional outcomes of intra-articular hyaluronic acid (HA) injection in patients with early-stage knee OA, graded according to the Kellgren-Lawrence system. A total of 27 patients were enrolled and received intra-articular HA injections with proper consent and aseptic measures. The patients were followed up for six months, with functional outcomes assessed using the WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) score. At the end of six months, 19 patients showed significant improvement in pain relief and range of motion, while 5 had moderate pain and functional limitations. The results suggest that hyaluronic acid injections offer superior functional outcomes, reducing pain and improving mobility, and may be a viable option for delaying the progression of knee osteoarthritis.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.039
GPT teacher head0.270
Teacher spread0.231 · 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 designCase report
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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