Comparison of two different molecular weight intra-articular injections of hyaluronic acid for the treatment of knee osteoarthritis.
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (OA) is an incurable joint disorder, representing a major public health issue. Among options for symptom control, viscosupplementation with hyaluronic acid (HA) had established usefulness in pain and function improvement of the knee. However, it is not clear which form of HA yields better results. MATERIAL AND METHODS: We compared two HA preparations with high (HMW) or low molecular weight (LMW) in terms of pain control and function improvement using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the visual analog scale (VAS) score in patients with knee OA. During 2013, 80 patients were enrolled in this prospective, double-blind, randomized study. Each patient received a weekly injection of either preparation with a total of five injections for the LMW group and three for the HMW group. They were evaluated at baseline, five weeks, three months and one year after treatment. RESULTS: In both groups, HA treatment resulted in significant improvement in pain and function that begun immediately after treatment and lasted for one year. However when compared with each other, HMW and LMW groups were comparable in mean WOMAC, and VAS score at each time point. Neither preparation can interrupt disease progression as radiological findings remained constant during follow-up. CONCLUSIONS: Intra-articular injections using HMW or LMW HA can improve stiffness, joint function and pain in patients suffering from knee OA. However, no clear benefit seems to exist between the two preparations and neither can slow disease progression. Hippokratia 2016, 20(1): 26-31.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".