Intra‐Articular Injection of Autologous Microfat and Platelet‐Rich Plasma in the Treatment of Knee Osteoarthritis: A Double‐Blind Randomized Comparative Study
Bibliographic record
Abstract
PURPOSE: To compare a single abdominal microfat (MF) injection mixed or not with platelet-rich plasma (PRP) Low Dose (LD) or High Dose (HD) in order to improve MRI parameters, alleviate pain and enhance functional capacity in knee osteoarthritis. METHODS: Patients with symptomatic grade 2 to 4 knee osteoarthritis according to the International Cartilage Repair Society MRI classification were selected. They were prospectively assessed at baseline and at 3 and 6 months of follow-up. The primary endpoint was change in the maximum of value of cartilage relaxation time in T2 mapping sequences (T2max) at 3 months. Secondary endpoints were MRI grade severity and joint space assessment, Western Ontario and McMaster Universities Arthritis Index score, pain evaluation, knee range of motion, and patients' satisfaction. Adverse events were also collected. The complete cell counts and growth factors content of injected products were assessed to analyze their potential relationship with MRI and clinical outcomes. RESULTS: Three groups of 10 patients received a single injection of 10 cc of a mix (1:1) containing MF-Saline, MF-PRP LD or MF-PRP HD. T2max did not change significantly over the time for any of the groups. All treatments significantly improved knee functional status and symptom relief at 3 and 6 months. All patients were responders in the MF/PRP HD at 3 months and significantly higher compared to MF/PRP LD. Half of the injected PRP in the MF/PRP LD group displayed red blood cell contamination of over 8%, which was correlated with an impairment of T2max. CONCLUSION: A single intra-articular injection of MF with or without PRP is safe and may offer a significant clinical improvement in patients with osteoarthritis. LEVEL OF EVIDENCE: 2; randomized double-blind comparative parallel-group trial (RCT No.: NCT04352075).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".