Managing Clopidogrel Resistance in Neurointervention: Surveying Current Approaches
Bibliographic record
Abstract
Background: Because of the variability in patient responses to clopidogrel and to reduce the risk of thromboembolic complications, adjusting the antiplatelet regimen based on platelet function testing has become a widespread practice in neurointervention. We aimed to explore current patterns related to this practice. Methods: ) and 2 consortium emailing lists (WovenEndoBridge and Neurointerventional Research Consortia). The data obtained from the responses were analyzed using descriptive statistics. Results: A total of 133 neurointerventionalists, representing 79 institutions within 27 countries, responded to the survey. A total of 62% of respondents tested for clopidogrel resistance before any neurovascular stent placements. A total of 80% used VerifyNow point-of-care P2Y12 assay; other assays included multiplate analyzer, platelet function analyzer, and CYP2C19 genotype assay. Respondents reported 25 different therapeutic thresholds, with the P2Y12 reaction unit range between 60 and 180 most commonly used (16.4%). A total of 61% reported they would switch to ticagrelor in the case of persistent resistance. On the other hand, when patients are supratherapeutic, 48% did not make any changes, whereas 42% reduced clopidogrel dose. Finally, 93% opined that a well-established protocol for management of clopidogrel resistance was needed. Conclusions: Neurointerventional practice patterns around clopidogrel resistance remain heterogeneous. Our results underscore the need for evidence-based guidance on the management of clopidogrel resistance in neurointervention.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".