Reproductive outcomes in women with congenital uterine anomalies: a systematic review
Bibliographic record
Abstract
OBJECTIVE: Congenital uterine anomalies are common but their effect on reproductive outcome is unclear. We conducted a systematic review to evaluate the association between different types of congenital uterine anomaly and various reproductive outcomes. METHODS: Searches were performed using MEDLINE, EMBASE, the Cochrane Library and Web of Science. The Newcastle-Ottawa Quality Assessment Scale was used for quality assessment. Uterine defects were grouped into arcuate uteri, canalization defects (septate and subseptate uteri) and unification defects (unicornuate, bicornuate and didelphys uteri). Pooled risk ratios (RR) with 95% confidence intervals (CI) were computed using random effects models. RESULTS: We identified nine studies comprising 3805 women. Meta-analysis showed that arcuate uteri were associated with increased rates of second-trimester miscarriage (RR, 2.39; 95% CI, 1.33-4.27, P = 0.003) and fetal malpresentation at delivery (RR, 2.53; 95% CI, 1.54-4.18; P < 0.001). Canalization defects were associated with reduced clinical pregnancy rates (RR, 0.86; 95% CI, 0.77-0.96; P = 0.009) and increased rates of first-trimester miscarriage (RR, 2.89; 95% CI; 2.02-4.14; P < 0.001), preterm birth (RR, 2.14; 95% CI, 1.48-3.11; P < 0.001) and fetal malpresentation (RR, 6.24; 95% CI, 4.05-9.62; P < 0.001). Unification defects were associated with increased rates of preterm birth (RR, 2.97; 95% CI, 2.08-4.23; P < 0.001) and fetal malpresentation (RR, 3.87; 95% CI, 2.42-6.18; P < 0.001). CONCLUSIONS: Canalization defects reduce fertility and increase rates of miscarriage and preterm delivery. None of the unification defects reduces fertility but some are associated with miscarriage and preterm delivery. Arcuate uteri are specifically associated with second-trimester miscarriage. All uterine anomalies increase the chance of fetal malpresentation at delivery.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".