Thrombophilia testing in pregnancy: should we agree to disagree?
Bibliographic record
Abstract
The value of testing for inherited thrombophilia in pregnancy has been debated in literature with regard to its utility in preventing adverse obstetrical outcomes or identifying women at risk for it. In this commentary, an evidence based approach is used to investigate the strength of association between thrombophilias and recurrent pregnancy loss and stillbirth. Several studies and meta-analyses have shown that there is only a weak association with recurrent pregnancy loss. However, many of these studies were underpowered, and there was significant heterogeneity-issues that are addressed in this paper. The evidence for association with stillbirth is lacking, but the few studies that are available seem to suggest a stronger correlation than for recurrent pregnancy loss. Further, the benefit of treating thrombophilias with anticoagulation in order to prevent these outcomes is discussed. While there is a lack of evidence looking at whether anticoagulation prevents stillbirth, there is strong evidence to show that anticoagulation does not prevent recurrent pregnancy loss. Finally, guidelines put out by various obstetrical and hematological societies regarding this topic are summarized.
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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 | 0.072 | 0.305 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.030 | 0.042 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".