Faculty Opinions recommendation of Does free androgen index predict subsequent pregnancy outcome in women with recurrent miscarriage?
Bibliographic record
Abstract
BACKGROUND: Several studies have investigated plasma androgen levels in women with recurrent miscarriage (RM) with conflicting results on whether an association between hyperandrogenaemia and RM exists. However, none of these studies included sensitive androgen measurements using a large data set. We therefore investigated the free androgen index (FAI) in a large number of women with RM in order to ascertain whether hyperandrogenaemia is a predictor of subsequent pregnancy outcome.METHODS: We studied 571 women who attended the Recurrent Miscarriage Clinic in Sheffield and presented with > or =3 consecutive miscarriages. Serum levels of total testosterone and sex hormone-binding globulin were measured in the early follicular phase and FAI was then deduced.RESULTS: The prevalence of hyperandrogenaemia in RM was 11% and in a subsequent pregnancy, the miscarriage rate was significantly higher in the raised FAI group (miscarriage rates of 68% and 40% for FAI > 5 and FAI < or = 5 respectively, P = 0.002).CONCLUSIONS: An elevated FAI appears to be a prognostic factor for a subsequent miscarriage in women with RM and is a more significant predictor of subsequent miscarriage than an advanced maternal age (> or =40 years) or a high number (> or =6) of previous miscarriages in this study. PMID: 18263637
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.317 | 0.129 |
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".