Transvaginal ultrasonography to predict preterm birth in women with bicornuate or didelphus uterus
Bibliographic record
Abstract
OBJECTIVE: To estimate whether cervical length measured by transvaginal ultrasonography (TVUS) in women with uterine anomalies predicts spontaneous preterm birth (SPTB). METHODS: This retrospective cohort study compared women with a uterine anomaly who were pregnant with singleton gestations and delivered August 2000 to April 2008 to a low risk control group. Transvaginal ultrasonographic cervical lengths were measured 16-30 weeks gestation. Primary outcome was cervical length and SPTB less than 35 weeks and the primary exposure variable of interest was cervical length. Secondary outcomes were SPTB less than 37 weeks, less than 32 weeks, low birth weight, maternal and neonatal outcomes. Receiver operating characteristic curves were generated to identify the best cervical length cutoff. RESULTS: Women with a bicornuate uterus (N = 35) had shorter cervical length (3.46 cm) than the low risk control group (N = 122, 4.32 cm, p < 0.0001). Women with a bicornuate or didelphus uterus, compared with low risk women, had higher rates of SPTB less than 35 weeks (8.6% and 30.8% versus 0.8%, p = 0.0007), neonatal intensive care unit admission more than 24 h (26.5% and 41.7% versus 7.5%, p = 0.0021) and composite perinatal morbidity (32.4% and 69.2% versus 8.3%, p < 0.0001). Using a cutoff of 3.0 cm, TVUS cervical length in women with a bicornuate uterus predicted SPTB less than 35 weeks (positive predictive value [PPV] = 37.5% and negative predictive value [NPV] = 100%), birth weight less than 2500 g (PPV = 50.0% and NPV = 96.3%) and respiratory distress syndrome (PPV = 37.5% and NPV = 100%). CONCLUSION Women with a bicornuate uterus have shorter cervical lengths than low risk controls, and are at higher risk of SPTB less than 35 weeks. Transvaginal ultrasonographic cervical length predicts SPTB less than 35 weeks, low birth weight and perinatal morbidity in these women.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".