Efficacy of Hyaluronic Acid in Patients with Osteoarthritis of The Knee
Bibliographic record
Abstract
Osteoarthritis (OA) of the knee is the most common chronic degenerative joint disease characterized by pain,stiffness, swelling and progressive functional limitation in elderly. Non-surgical management modalitieslike physical therapy, lifestyle modification and oral non-steroidal anti-inflammatory drugs, are oftenineffective or do not alleviate symptoms adequately. Intra-articular corticosteroid (CS) and hyaluronic acid(HA) injections have been used for long to alleviate the symptoms of knee OA. viscosupplementation hasbeen used as a therapeutic modality for the management of knee OA. The principle of viscosupplementationis based on the physiological properties of the hyaluronic acid (HA) in the synovial joint which helps tissuelubricate, cushion and reduce pain in the joint.Study diagnosed forty patient of knee Osteoarthritis for both gender with age (45-70 years) and observedchange and effectiveness to pre-and post of HA injection, All patients diagnosed by Orthopedists andRheumatologists whose used X-rays were graded as stage I, II and III according to Kellgren and Lawrencescale.All the measurements were used at the time of enrollment in the study before any injection and then measuredagain at the end of three months by using Western Ontario and McMaster University Osteoarthritis Index(WOMAC) .All the patients before therapy were having minimum score of 72.4 & 9.045 for Mean and Standard Deviationrespectively while after the therapy there score reduced to 36.2 & 4.783.The results show improvement significant during four month under study and the effect peaks at around8–12 weeks following administration, This supports the potential use of intra-articular HA as an effectivelong therapeutic option for patients with OA of the knee.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".