Blood flow restriction‐enhanced platelet‐rich plasma: A pilot randomised controlled trial protocol
Bibliographic record
Abstract
Purpose: To assess platelet-rich plasma (PRP) changes in platelet and leucocyte count, insulin-like growth factor 1 (IGF-1), and interleukin 6 (IL-6) concentration after bilateral low-load knee extensions under blood flow restriction (BFR). Methods: The present randomised controlled trial protocol will include two groups: the intervention group, which will undergo bilateral knee extensions under BFR, and the control group, which will perform bilateral knee extensions without BFR. Participants will be randomly allocated in a 1:1 ratio. Twenty-two healthy individuals will be enrolled if the predefined inclusion criteria are met: (1) males, (2) ages 18-40, (3) Tegner activity level ≥5 and (4) with no musculoskeletal conditions that would interfere with exercise. Exclusion criteria include (1) individuals with systemic inflammatory diseases, (2) cardiovascular risk factors, (3) any blood dyscrasia, (4) Tegner Activity scale scores <5, (5) under nonsteroidal anti-inflammatory drugs and aspirin treatment within one week before testing or (6) that had previously performed exercises on the testing day. The participant will perform low-load bilateral knee extensions under BFR following a standard protocol of 30-15-15-15 repetitions of consecutive sets with 30-s rest intervals at 80% of limb occlusive pressure and 30% of 1-RM load. PRP platelet and leucocyte count, IGF-1 and IL-6 concentration measurements (via flow cytometry, chemiluminescence testing and immunochromatography, respectively) will be conducted before exercise and 10, 20 and 30 min after the intervention. Results: The expected outcome is that the standard protocol of low-load bilateral knee extensions under BFR will increase the platelet and leucocyte count, IGF-1 and IL-6 in the PRP preparation. Conclusion: The current protocol allows the study of an enhanced PRP formulation for its potential implementation in multiple sports injuries.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 0.007 |
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".