Management of knee osteoarthritis by combined stromal vascular fraction cell therapy, platelet-rich plasma, and musculoskeletal exercises: a case series
Bibliographic record
Abstract
INTRODUCTION: Knee osteoarthritis is associated with persistent joint pain, stiffness, joint deformities, ligament damage, and surrounding muscle atrophy. The complexity of the disease makes treatment difficult. There are no therapeutic drugs available to halt the disease progression, leaving patients dependent on pain medication, anti-inflammatory drugs, or invasive joint replacement surgery. CASE PRESENTATIONS: Four patients with a history of unresolved symptomatic knee osteoarthritis were investigated for the therapeutic outcome of combining an exercise rehabilitation program with intra-articular injections of autologous StroMed (ie, stromal vascular fraction cells concentrated by ultrasonic cavitation from lipoaspirate) and platelet-rich plasma (PRP). The Knee Injury and Osteoarthritis Outcome Score questionnaire (KOOS) was administered along with physical function tests over a 12-month period. The first patient achieved a maximum therapeutic outcome of 100 in all five KOOS subscales (left knee), and 100 for four subscales (right knee). The second patient scored 100 in all five KOOS subscales (left knee), and greater than 84 in all subscales (right knee). Treatment of the third patient resulted in improved outcomes in both knees of >93 for four KOOS subscales, and 60 for the Function in Sport and Recreation subscale. The fourth patient improved to 100 in all five KOOS subscales. In all patients, the physical function "Get-up and Go" test and "Stair Climbing Test" returned to normal (a value of zero). CONCLUSION: This case series indicates that improved outcomes may be obtained when autologous stromal vascular fraction (StroMed) cell therapy is combined with traditional exercise practices and PRP for osteoarthritis. Of the seven joints treated: all patients' scores of pain improved to >96; and quality of life scores to >93. Functional performance measures of mobility returned to normal. This simple treatment appears to be extremely effective for osteoarthritis disorders that have no drug treatment to halt disease progression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".