Assessment of VerifyNow P2Y12 Assay Accuracy in Evaluating Clopidogrel-Induced Platelet Inhibition
Bibliographic record
Abstract
The emergence of point-of-care assays enabling bedside testing such as the VerifyNow P2Y12 system might prove useful in clinical settings. The aim of this study was to evaluate the ability of the VerifyNow P2Y12 assay to estimate the inhibition of platelet aggregation provided by clopidogrel in the absence of baseline off-drug aggregation data. Sixty-eight patients with coronary artery disease scheduled to initiate clopidogrel therapy underwent platelet aggregation testing by VerifyNow P2Y12 at baseline and after clopidogrel administration. The inhibition reported by the VerifyNow assay (relative to thrombin receptor activating peptide-induced platelet aggregation, serving as baseline) was compared with that calculated with the actual adenosine diphosphate-induced baseline obtained with the same methodology. The postclopidogrel thrombin receptor activating peptide-induced aggregation showed a great discordance with that induced by adenosine diphosphate before clopidogrel with a bias of 24 units (95% limits of agreement from -142 to 190 units). Moreover, the inhibition reported by the assay overestimated the standard before-and-after testing data by an average of 8% (95% limits of agreement from -49% to 65%), making its use without a true baseline comparator unsatisfactory. The VerifyNow P2Y12 assay fails to accurately quantify platelet inhibition achieved by clopidogrel compared with before-and-after testing. Further studies are required to establish the clinical usefulness of the VerifyNow P2Y12 assay to accurately predict the occurrence of major adverse cardiovascular events in patients with reduced clopidogrel efficacy before it can be implemented in clinical practice. At present, the use of this assay in clinical care cannot be recommended for monitoring clopidogrel therapy.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".