Inherited thrombophilia and pregnancy associated venous thromboembolism
Bibliographic record
Abstract
Pulmonary embolism is the leading cause of maternal mortality in developed countries and accounts for 20% of pregnancy related deaths in the United States.1 2 The risk of pulmonary embolism and deep vein thrombosis, collectively known as venous thromboembolism, is increased during pregnancy and is further increased by the presence of inherited or acquired thrombophilias. We summarise the epidemiology and diagnosis of venous thromboembolism in pregnancy and discuss the anticoagulant management of women with inherited thrombophilia who are at risk of, or who develop, venous thromboembolism during pregnancy and the postpartum period. #### Scenario A 30 year old woman, a known heterozygote for the factor V Leiden mutation, presents at eight weeks' gestation in her first pregnancy wondering whether she should receive prophylactic anticoagulation to prevent recurrent venous thrombosis during pregnancy. Several years ago she developed a deep vein thrombosis of the left leg after an ankle fracture and prolonged immobilisation and was found to have the factor V Leiden mutation. The deep vein thrombosis was treated with anticoagulants for three months, and the woman has had no recurrent thromboembolic events since stopping warfarin. Her mother developed a deep vein thrombosis after surgery but did not undergo testing for thrombophilia. #### Methods We searched Medline and the Cochrane database of systematic reviews for studies evaluating the epidemiology, diagnosis, prevention, and treatment of venous thromboembolism during pregnancy and the postpartum period in women with inherited thrombophilia, using the key words “venous thrombosis”, “deep vein thrombosis”, “pulmonary embolism”, “pregnancy (complications)”, “thrombophilia”, and “anticoagulants.” Venous thromboembolism occurs in 10 per 100 000 women of childbearing age and affects 100 per 100 000 pregnancies.3 Inherited thrombophilia is present in 30%-50% of women with pregnancy associated venous thromboembolism,3w1 with factor V Leiden being the most frequently identified inherited thrombophilia in the white population (table 1⇓). #### Non-inherited conditions that increase the risk of venous thromboembolism in pregnancy ##### General conditionsw2
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".