Prevalence of Thrombophilia in Transient Ischemic Attack and Ischemic Stroke Patients
Bibliographic record
Abstract
Introduction. Screening for inherited thrombophilia has been recommended in patients with cryptogenic ischemic strokes and anticoagulant therapy is frequently indicated based on these results. However, current evidence suggests that thrombophilia screening is over utilized in stroke patients and may provide more risks than benefits. Patients and Methods.We conducted a retrospective cohort study in patients with transient ischemic attack (TIA) or ischemic stroke who had a thrombophilia screen and determined the proportions of each thrombophilia trait, and the proportion of high risk thrombophilia in this population. Pre-specified subgroup analyses were conducted for patients with ischemic stroke and transient ischemic attacks, and for patients with patent foramen ovale. Results.We included 412 patients (152 male and 260 female). The prevalence of thrombophilia was 7.52% (95% CI 5.35-10.48). The proportion of major thrombophilia was 2.18 (95% CI=1.15 - 4.09). The proportion of thrombophilia traits in ischemic stroke patients was lower 4.92% (95% CI 2.61 - 9.08) than that in patients with transient ischemic attacks 9.57% (95% CI = 6.41 - 14.06); Only 2 individuals had both a positive thrombophilia screen and a patent foramen ovale. Discussion. In this study the prevalence of thrombophilia traits in patients with ischemic stroke or transient ischemic attack was low, including high risk thrombophilic traits. Further studies are needed to determine if thrombophilia screening exposes these patients to additional risks without any benefits. Disclosures Sposato: Western University:Other: Kathleen and Dr. Henry Barnett Chair in Stroke Research;Boehringer Ingelheim:Honoraria, Research Funding;Pfizer:Honoraria, Research Funding;Gore:Honoraria, Research Funding;Bayer:Honoraria, Research Funding.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".