Hyaluronic Acid Injections of the Knee: Predictors of Successful Treatment
Bibliographic record
Abstract
Objectives: Knee viscosupplementation yields variable results for osteoarthritis. Establishing patient and treatment factors that predict a favorable response to intra-articular hyaluronic acid (HA) treatment will better guide patient and treatment selection. Methods: This prospective study evaluated patients presenting with Kellgren-Lawrence grade 1-3 painful, primary knee osteoarthritis. The primary outcome measures were the Western Ontario and McMaster Universities Arthritis Index/ Knee Injury and Osteoarthritis Outcome Score (WOMAC/KOOS) and a standardized visual analog scale (VAS). Surveys were completed at the first and subsequent injections, then at three months post-treatment. Response to treatment was defined according to the Osteoarthritis Research Society International 2004 criteria. Results: We enrolled 135 patients, 102 remained for final analysis. Fifty-seven percent of patients had a positive response to treatment. Factors related to a positive response included those with grade 1 or 2 osteoarthritis (RR=2.17; 95%CI, 1.40-3.37), and those who showed improvement after the first injection (RR=2.22; 95%CI, 1.49-3.31). Seventy-eight percent of people who responded to the first injection had a positive response at follow-up. In multi-variable analysis, those aged 60 or older responded more positively with grade 2 osteoarthritis than those less than 60 years (RR=1.98; 95%CI, 1.18-3.21). Gender, race, BMI, smoking status, HA brand, and initial VAS and KOOS scores were not significant predictors of success in either independent or multivariable analysis. Conclusion: Patients with mild to moderate osteoarthritis (grades 1 and 2), and those who responded positively to the first injection were two times more likely to respond positively to the injection series than those with grade 3 osteoarthritis, or those who did not respond initially. Patients aged 60 or older are twice as likely to respond than those less than 60 years for grade 2 osteoarthritis. Judicious patient selection and counseling may improve outcomes associated with intra-articular HA injections. [Table: see text]
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".