Platelet function analyzer‐200 closure curve analysis and assessment of flow‐obstructed samples
Bibliographic record
Abstract
BACKGROUND: The Platelet function analyzer-200 can determine the effect of clopidogrel in cats. Flow obstruction is an error that causes uninterpretable results. Closure curves and parameters initial flow rate (IF) and total volume (TV) are displayed by the PFA-200 and may allow interpretation of results in cases of flow obstruction. The primary hemostasis components (PHC) are calculated values that normalize these parameters. OBJECTIVES: To determine if closure curves and research parameters allow detecting the effect of clopidogrel in cases of flow obstruction. METHODS: A review of closure curves identified those with flow obstruction and paired analysis that did not. Non-flow-obstructed curves were used to categorize curves with respect to clopidogrel effects. IF, TV, PHC(1), and PHC(2) were evaluated to determine if these could be used to categorize if a sample exhibited the effects of clopidogrel. Curves were visually analyzed, and characteristics identified that were more common with or without the effect of clopidogrel. Visual analysis of curves was performed by blinded observers to determine if a visual analysis was able to predict the effect of clopidogrel. RESULTS: Analysis of parameters was able to predict closure or non-closure in flow-obstructed curves. TV, PHC(1), and PHC(2) had area under the curve of the receiver operating characteristics of 0.79, 0.79, and 0.87. Visual curve analysis was unable to predict closure, with an average accuracy of only 55%, among three reviewers. Agreement between reviewers was poor (Fleiss' Kappa 0.06). CONCLUSIONS: Visual curve analysis was unable to determine the effect of clopidogrel in flow-obstructed samples. Numerical parameters were able to detect the effect of clopidogrel with a high degree of accuracy in flow-obstructed samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".