A Comparison Between Rheological Properties of Intra-articular Hyaluronic Acid Preparations and Reported Human Synovial Fluid
Bibliographic record
Abstract
INTRODUCTION: This study aims to compare the properties of currently available intra-articular hyaluronate (IA-HA) products widely available in the USA to those of healthy knee synovial fluid with respect to their bulk rheological properties. We hypothesize that products would have differing rheological properties, with some more closely resembling the properties and physiological aspects of healthy joint fluid HA. METHODS: . RESULTS: Differences were seen between the study products across all of the investigated parameters. Hyalgan, Supartz, Orthovisc, and Euflexxa had a linear chain structure, while Synvisc, Synvisc-One, and Monovisc were cross-linked in structure. Molecular weight, shear rates, and crossover frequencies ranged widely across tested products, with values ranging from below to above those reported for healthy knee synovial fluid HA. When compared to healthy knee parameter values reported within the current literature, observed parameters for Euflexxa and Orthovisc were typically seen to be the most similar to healthy knee synovial fluid. When comparing Euflexxa and Orthovisc directly, Euflexxa was more often similar to the properties of healthy knee synovial fluid with respect to the observed parameters of molecular structure, shear rates, and crossover frequency. CONCLUSION: Available IA-HA products vary with respect to molecular weight, presence of cross-linking, shear rate dependency of viscosity, and crossover frequency. Since IA-HA treatment for osteoarthritis aims to restore synovial fluid back to original HA property characteristics, using HA supplements resembling healthy synovial fluid is a logical approach. Our findings demonstrate that Euflexxa is the most similar to healthy synovial fluid with respect to molecular structure, shear rates, and crossover frequency. FUNDING: Ferring Pharmaceuticals, Inc.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".