Autologous adipose tissue injection versus platelet-rich plasma (PRP) injection in the treatment of knee osteoarthritis: a randomized, controlled study – study protocol
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (OA) is a common, chronic, progressive and degenerative disease which affects patients' quality of life and may cause disability and social isolation. OA is a huge economic burden for the patient and a large strain for the whole healthcare system. Articular cartilage has a small potential to repair, with progressively more clinicians emphasizing cellular therapy. Subcutaneous fat tissue in human body is a large reservoir of mesenchymal stem cells (MSCs) and is been harvested in minimally invasive, simple procedure. Up to date there is no prospective randomized controlled studies demonstrating effectiveness and role of adipose tissue injections in OA treatment. The purpose of this study is to assess functional and clinical changes among patients with symptomatic knee OA treated with intra-articular injections of autologous adipose tissue or platelet rich plasma (PRP) and to compare efficacy of both therapeutic methods. METHODS: This is a prospective, randomized, controlled study. Patients who meet inclusion criteria will be allocated to Fat Tissue group or PRP group randomly. Subjects will receive an intra articular injection with autologous adipose tissue and PRP respectively. Patients will be assessed five times: before treatment and 1, 3, 6 and 12 months after the treatment. The assessment consists of patient reported outcome measures (The Knee injury and Osteoarthritis Outcome Score, International Knee Documentation Committee 2000, the Western Ontario and McMaster Universities Osteoarthritis Index, the Health Questionnaire EQ- 5D- 5 L), three functional tests (The Timed Up and Go Test, The 5 Times Sit to Stand Test, The 10 m Walk Test) and Maximal Isometric Voluntary Contraction. DISCUSSION: This study protocol has several strengths and weaknesses. One of strongest point of this study is the wide, multidimensional functional assessment which will give a large amount of objective data. On the other hand, lack of blinding has to be considered as a risk of both subject and investigator bias. TRIAL REGISTRATION: name of registry: ClinicalTrials.gov, trial registration number: NCT04321629, retrospectively registered on date of registration.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".