Regenerative Medicine for Knee Osteoarthritis – The Efficacy and Safety of Intra-Articular Platelet-Rich Plasma and Mesenchymal Stem Cells Injections: A Literature Review
Bibliographic record
Abstract
The prevalence of osteoarthritis (OA) has been rising exponentially in recent years. As the disease progresses, patients may eventually require surgical intervention to restore the functionality of the affected knees. The current literature review aims to explore two treatment options in regenerative medicine for OA by analyzing the efficacy and safety of platelet-rich plasma (PRP) and mesenchymal stem cells (MSCs) use, as well as determining which population will benefit from these treatments. A total of 1093 patients who were diagnosed with unilateral or bilateral knee osteoarthritis (KOA) were recruited in 23 studies. The experimental groups received either PRP or MSCs injections in comparison to the control groups receiving either hyaluronic acid (HA) or placebo (saline or dextrose) injections. Western Ontario and McMaster Universities Arthritis Index (WOMAC) was used to evaluate all participants at different time intervals of the studies. Medical imaging evaluations (X-ray or MRI) were used to look for structural improvements. In conclusion, both PRP and MSCs treatments were well tolerated, effective and safe to use. Repeated administrations and higher concentrations resulted in superior clinical improvements. A decrease in cartilage loss was observed in some MSCs trials. No severe adverse effects were documented. PRP treatment proved to be more efficacious among patients with KOA Kellgren-Lawrence (KL) grade I-II, while MSCs treatment proved to be more beneficial among the KOA KL grade II-III group.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| 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".