Cervical assessment in women with hysteroscopic uterine septum resection: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To estimate whether cervical length measured by transvaginal ultrasonography in women with a history of hysteroscopic uterine septum resection predicts spontaneous preterm birth <35 weeks' gestation. METHODS: This retrospective cohort study compared women who had undergone hysteroscopic metroplasty, and were subsequently pregnant with singleton gestations delivered January 2003 to December 2012, to a low-risk control group. Transvaginal ultrasonographic cervical lengths were measured 16-30 weeks' gestation. The primary outcome was spontaneous preterm birth <35 weeks' gestation and the primary exposure variable of interest was cervical length. RESULTS: Women with a uterine septum resected (N = 24) had a shorter cervical length (2.90 cm) than the low-risk control group (N = 141, 4.31 cm, p < 0.0001); and were more likely to have a cervical length <3.0 cm (41.7% versus 1.4%, p < 0.0001), <2.5 cm (33.3% versus 0%, p < 0.0001), <2.0 cm (16.7% versus 0%, p < 0.0001) and <1.5 cm (12.5% versus 0%, p = 0.003). Women with septum resected were more likely to receive corticosteroids (33.3% versus 11.3%, p = 0.010), but were not more likely to have a spontaneous preterm birth <35 weeks (4.2% versus 0.7%, p = 0.27). There were no differences noted in secondary outcomes including neonatal morbidity. CONCLUSION: Pregnant women with a history of a hysteroscopic uterine septum resection have shorter cervical lengths than low-risk controls but may not be at a higher risk of spontaneous preterm birth <35 weeks' gestation. Further research with a larger sample size is needed to evaluate this group of women to determine if transvaginal ultrasonographic cervical length assessment is of benefit.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".