Amniotic Tissue Injections Are an Effective Alternative to Corticosteroid Injections for Pain Relief and Function in Patients With Severe Knee Osteoarthritis: A Double-Blind, Randomized, Prospective Study
Bibliographic record
Abstract
INTRODUCTION: The use of corticosteroid injections for short-term pain relief for knee osteoarthritis can have deleterious adverse effects. Amniotic tissue has shown promise in vitro; therefore, this study compared a morcellized injectable amniotic tissue allograft to corticosteroid injection. METHODS: Eighty-one patients with symptomatic severe knee osteoarthritis (Kellgren-Lawrence grade 3 to 4) were prospectively randomized to either a double-blinded single injection of BioDRestore (Integra LifeSciences; n = 39) or triamcinolone acetonide (n = 42). Knee Injury and Osteoarthritis Outcome Score (KOOS), Single Alpha Numeric Evaluation, visual analog scale (VAS) pain, Lysholm Rating, and Veterans-Rand-12 scales at baseline, 6 weeks, 3, 6, and 12 months were analyzed. RESULTS: No differences were observed in adverse reactions or patient reported outcomes (PROs); however, a notable continued improvement was found in the amnion group from 6 weeks to 1 year for Single Alpha Numeric Evaluation, Lysholm, and KOOS Symptoms, Pain, activities of daily living [ADL], QofL. The minimal clinically important difference (MCID) was met for Lysholm, KOOS ADL, and KOOS pain. DISCUSSION: Both amnion and steroid injections showed an initial improvement in pain relief and function at 6 weeks; however, more patients in the amniotic tissue group maintained pain relief and function at the 1-year follow-up. The mixed results suggest that amniotic tissue injections may be a safe and effective alternative to corticosteroid injections.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".