Delay to TKA in Patients Treated with a Multimodal Approach Using High Molecular Weight, Biologically Derived Hyaluronic Acid
Bibliographic record
Abstract
BACKGROUND: The primary objective of this study was to determine the effect of single versus multiple rounds of intra-articular hyaluronic acid (IA-HA) in delaying the need for total knee arthroplasty (TKA) in patients with knee OA, and if additional benefits were seen when used in conjunction with other multimodal treatment options. METHODS: This study was a retrospective claims analysis of a large commercial database containing more than 100 million patients with continuous coverage from October 1, 2010 through September 30, 2015. Time to TKA for patients who received one course of Euflexxa (IA-BioHA) were compared to patients who received two or more courses of IA-BioHA and patients who received no IA-HA. Assessment of multimodal treatment effects was done between the following groups: IA-BioHA injections alone, IA-BioHA and bracing, IA-BioHA and corticosteroid injection, and IA-BioHA with both corticosteroids and bracing. RESULTS: A total of 26,727 patients were included in the analysis of treatment courses, and 31,034 in the analysis of multimodal treatment combinations. The use of IA-BioHA demonstrated a delay of TKA that was prolonged with repeated courses of treatment (1.411 years, interquartile range [IQR]: 1.44). The greatest delay to TKA was observed for the patients who had received all three treatment options (1.5 years, IQR: 1.52) in the multimodal analysis. CONCLUSIONS: These results confirm that treatment of knee OA should consider the use of multimodal therapy instead of focusing on individual treatment options. Additionally, the use of repeated courses of IA-BioHA should be considered for prolonged benefit for patients with symptomatic knee OA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".