A randomized study protocol comparing the platelet-rich plasma with hyaluronic acid in the treatment of symptomatic knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: In recent years, intra articular injection of platelet rich plasma has attracted increasing attention. The major aim of our current randomized controlled double-blind study was to compare long-term outcomes of intra-articular injection of hyaluronic acid or platelet rich plasma in the treatment of the patients with knee osteoarthritis. METHODS: This is a kind of double-blind, randomized, prospective, and comparative clinical investigation with the allocation ratio of 1:1 and was approved by our institutional review Committee. Between 2020 and 2021, altogether 2 hundred patients will be selected to participate in our present study. We will report the randomized experiments in accordance with the guidelines of Consolidated Standards of Reporting Trials and then offer the Consolidated Standards of Reporting Trials flow chart. The inclusion criteria were: patients aged from 40 to 70 years old, patients with chief complaint history of at least 1 month and knee joint pain for nearly 6 months, need the analgesic drug treatment, and radiology confirmed knee osteoarthritis. The eligible patients would be randomly divided into 2 groups through applying the random numbers generated by computer before surgery. Outcomes after treatment were assessed using the Western Ontario and McMaster University and the scoring systems of visual analogue scale which were recorded through questionnaires accomplished via the patients prior to the first injection and then at three and six months, 1 and 2 years follow-up. Any adverse events occurred within 1 year after surgery were recorded during follow-up. RESULTS: This should suggest whether biological methods can offer more lasting outcomes than the viscosification. TRIAL REGISTRATION: This study protocol was registered in Research Registry (researchregistry6265).
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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 | 0.035 | 0.026 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".