Inferior Vena Cava Filters for Pulmonary Emboli in the Absence of Residual Deep Venous Thrombosis: A Survey of Current Physician Practices in Nova Scotia, Canada
Bibliographic record
Abstract
Introduction: There is a lack of evidence for the role of inferior vena cava (IVC) filters for pulmonary embolism (PE) in the absence of deep vein thrombosis (DVT). We surveyed physicians in Nova Scotia, Canada, to assess how lower limb ultrasound findings affect the decision to place an IVC filter in patients with pulmonary emboli and a contraindication to anticoagulation.Methods: A web-based survey comprised of five scenarios with fictional patients who had confirmed PE and different contraindications to anticoagulation was sent to 153 physicians who may see patients with venous thromboembolism. Each scenario had four sub-scenarios with different ultrasound findings including DVT, two SVTs varying in length, and no DVT. For each sub-scenario, physicians had to choose if they would insert an IVC filter or not. Results:The survey response rate was 33%. A total of 48 surveys were included, with 2 surveys excluded due to a survey error. Respondents were mostly general internists (n=20), followed by hematologists (n=9). Across total responses for each sub-scenario (n=204 DVT, n=412 SVT, n=207 no DVT), physicians would insert an IVC filter in 87% (n=177) of patients with a DVT, 64% (n=263) of patients with SVT, and 46% (n=96) of patients with no DVT or SVT. Conclusion:The majority of physicians included in this survey would place an IVC filter in patients with a DVT or SVT, whereas the absence of a DVT or SVT is reassuring to slightly over half of physicians. Further studies are required to guide recommendations on placement of IVC filters in patients with an acute PE without DVT or SVT and a contraindication to anticoagulation.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".