Effects of Yunnan Baiyao on blood coagulation parameters in beagles measured using kaolin activated thromboelastography and more traditional methods
Bibliographic record
Abstract
Yunnan Baiyao is anecdotally widely used in veterinary medicine for its pro-coagulation properties. There are no studies determining its effect on clotting tests. The purpose of this study was to determine the effect of oral Yunnan Baiyao (YB) on hemostasis by measuring coagulation via kaolin activated citrated whole blood thromboelastography (TEG), prothrombin time (PT), activated partial thromboplastin time (aPTT), fibrinogen, and d-dimers. The study was a prospective, randomized controlled crossover trial. Eight healthy University of Calgary owned beagles were treated orally with either Yunnan Baiyao or placebo every 12 h for 5 treatments. Blood was collected immediately before treatment, 2 h after the last treatment, and 24 h after the last treatment. TEG analysis was run 30 ± 5 min after blood collection. All other coagulation analyses were sent to a reference laboratory for further analysis. No treatment adverse effects were observed. Oral YB increased R-time significantly within the YB group, but the increase was still within canine reference ranges. No other changes were observed. Oral YB at the dosage and frequency administered in this study did not produce any significant improvement in hemostatic parameters. There is a need for further research and scientific evidence for YB use and dosage.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".