Antithrombotic Strategy in Cerebral Venous Thrombosis: Differences Between Neurologists and Haematologists in a Canadian Survey (I2.010)
Bibliographic record
Abstract
Objective: To ascertain patterns of practice with regards to anticoagulation for cerebral venous thrombosis. Background: Cerebral venous thrombosis (CVT) is a rare cause of stroke and anticoagulation is the mainstay of treatment. We surveyed Canadian hematologists and neurologists with regards to choice of anticoagulant. Methods: Participants were recruited from two national email lists: the Canadian Stroke Consortium (CSC), which has 125 physician members involved in treatment of stroke, mostly neurologists, and Thrombosis Canada (TC), which has 70 physician members, mostly hematologists. The survey consisted of 13 questions regarding individual patterns of practice in CVT. Results: Fifty-one physicians participated in the survey (27 neurologists, 20 hematologists; the remainder were other specialists). For initial anticoagulation in CVT, neurologists preferred Unfractionated Heparin (UFH) as a first line agent (89[percnt]), compared to 50[percnt] of hematologists (p=0.01). Half of hematologists used LMWH first-line. For maintenance anticoagulation, warfarin was the first choice for neurologists and hematologists (85[percnt] and 70[percnt], respectively; p=0.29). Fifty-seven percent of neurologists reported that they would prescribe LMWH as a second choice for maintenance anticoagulation; 29[percnt] would use a novel anticoagulant (nOAC). For hematologists, 53[percnt] chose LMWH and 16[percnt] nOAC. Conclusions: In this cohort, there are differences between neurologists and hematologists with regards to initial choice of anticoagulant. It is possible that more complex presenting cases of CVT with concurrent venous infarction, hemorrhage or seizure may present to neurologists as compared to hematologists. Thus, an initial preference for UFH may reflect a desire for a reversible agent with a short half-life in the event of bleeding complications in an unstable patient. Our study is limited by response bias, though our response rate of 28[percnt] is comparable to other contemporary web-based physician surveys. The majority of were from academic centres and responses may not reflect patterns of practice in the community.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".