The influence of adipose-derived stromal vascular fraction cells on the treatment of knee osteoarthritis
Bibliographic record
Abstract
Abstract Background Adipose-derived stromal vascular fraction (SVF) cells are a mixed cell population that includes cells with multilineage potential, similar to bone marrow-derived mesenchymal stem cells. Our purpose is to investigate the influence of SVF cells in patients with knee osteoarthritis (OA) and the short-term treatment effects. Methods Fifty-seven patients were enrolled and treated with intra-articular injection of 2.5 × 107 SVF cells into the knee joint between September 2017 and March 2018. All patients were followed up for 12 months or longer. Mean age at treatment and follow-up period were 69.4 ± 6.9 years and 13.7 ± 2.0 months, respectively. The mean preoperative hip-knee-ankle angle was 6.7 ± 3.6°. SVF cells were prepared using the Celution®800/CRS system from the patients’ abdominal or breech subcutaneous fat. The mean SVF cell viability was 90.6 ± 2.7%. Clinical evaluations were performed for range of motion, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), visual analog scale (VAS) for pain, and the Knee injury and Osteoarthritis Score (KOOS). Imaging evaluations, which included the hip-knee-ankle angle assessed via radiography, and T2 mapping value using a 1.5-T magnetic resonance imaging unit were also assessed. Both clinical and imaging evaluations were performed preoperatively, 1, 3, 6, and 12 months postoperatively, and compared among all timepoints (p
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".