Fertility after recurrent miscarriages: results of an observational cohort study
Bibliographic record
Abstract
Recurrent pregnancy losses (RPL) are considered a pathological condition associated with heterogeneous laboratory and clinical findings, and are also linked to subfertility. We attempt to rank parameters derived from past history and diagnostic results with regard to the prognosis. Observational trial on 719 consecutive couples who were referred to a tertiary immunological care centre (2006–2014) after three or more primary miscarriages. Information on past obstetric history and diagnostic procedures at baseline were correlated with cumulative pregnancy and delivery rates using Kaplan–Meier estimation, logistic regression and multivariate analysis. At baseline, median female age was 34.1 years, waiting time 3 years (1–17), number of preceding miscarriages 3 (3–9), 147 women (20.4%) had conceived at least once in ART or AIH cycles. After a median follow-up of 33.7 (1.7–123.0) months, 5-year pregnancy and delivery rates were 86.1 and 64.5%. Female age (< 35 years), waiting time (< 3 years) until baseline, tubal competence, and male factor fertility significantly correlated with favourable outcome ( p < 0.001), while body mass index (> 29 kg/m 2 ), number of preceding miscarriages (> 4), late miscarriages, preclinical losses and smoking revealed non-significant negative trends. Mode of conception until baseline (spontaneously or ART/AIH) and classification into idiopathic and non-idiopathic RPL showed no prognostic relevance. Although in general, chances to conceive a child are retained after three or more miscarriages, factors related to subfertility of both partners have an important impact on the outcome. Therefore, prolonged time to pregnancy (> 6–9 months) should result in preventive gynaecological care from the first miscarriage on, so that fertility can be preserved as best as possible.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".