Knee Osteoarthritis Treated with Percutaneous Chondral-Bone Interface Optimization: A Pilot Trial
Bibliographic record
Abstract
Objective: The objective is to evaluate the efficacy of using tibial bone marrow delivered to the chondral-bone interface (CBI) via percutaneous chondral bone interface optimization (PeCaBoo) as a therapy for knee osteoarthritis (OA). Study Design: A series of prospective cases were presented. Participants: Our study included 10 patients with medial or lateral compartment knee OA. Methods: With 1 cc of heparin pre-loaded in the syringe, 5 cc of tibial bone marrow was withdrawn from the proximal tibia. The resultant 6 cc of aspirate in the syringe was injected via PeCaBoo, 2 cc at a time, into the superior CBI and inferior CBI. The remaining 2 cc was injected via needle into the intra-articular joint space. Main Outcome Measurements: Patients had MRIs taken pre-procedure and 3 months post-procedure to measure bone edema and intra-articular matrix thickness. Patient-reported outcomes recorded included the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and the Numeric Paint Rating Scale (NRS), which were both obtained pre-procedure and post-procedure at 3, 6, and 12 months. Use of non-steroidal anti-inflammatories (NSAIDs) was recorded pre- and post-procedure as well. Results: Our study included 4 males and 6 females, with an average age of 63.5 years. The average follow-up time was 14 months, with a range of 13 - 15 months. The mean WOMAC score was 58.2 points pre-procedure and 35.3 points post-procedure (p Boo procedure. The subgroup of patients with tibial edema and knee OA had optimal outcomes. Conclusions: Tibial bone marrow stem cell delivered via PeCaBoo is a novel minimally-invasive treatment for knee OA, with potential to repair cartilage and improve knee pain and function.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".