Diagnosis and management of deep vein thrombosis in pregnancy
Bibliographic record
Abstract
#### What you need to know Venous thromboembolism includes deep vein thrombosis (DVT) and pulmonary embolism. In DVT a blood clot forms in the lower extremities that may break off and travel to the lungs causing a pulmonary embolism. DVT is more common than pulmonary embolism during pregnancy1 and will constitute the focus of this clinical update. However, the prevalence, risk factors, and therapeutic options for DVT and venous thromboembolism in pregnancy are closely linked, and thus information regarding venous thromboembolism in pregnancy has also been covered where appropriate or when data regarding DVT are unavailable. Among pregnant women, pulmonary embolism is the most serious complication of DVT and remains one of the leading causes of maternal death in the developed world.2 Pregnancy related DVT is associated with a higher risk of embolic complications and of the post-thrombotic syndrome (chronic leg pain, intractable oedema, leg ulcers) than DVT in non-pregnant women.13 This article provides an update on the diagnosis and management of pregnant women with DVT. The risk of venous thromboembolism in pregnancy is about four times the risk among non-pregnant women of childbearing age4; it is highest in the third trimester …
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".