Cervical length in asymptomatic twin pregnancies: prospective multicenter comparison of predictive indicators
Bibliographic record
Abstract
UNLABELLED: Abstract Objective: To determine whether cervical shortening between 22 and 27 weeks predicts spontaneous preterm delivery before 34 weeks better than a single cervical length (CL) measurement at 22 or 27 weeks in asymptomatic twins. METHODS: Prospective 13-center study over a 2-year-period. CL was measured in 120 asymptomatic twin pregnancies. The area under the ROC curve was calculated for each parameter and the cutoff point providing the best diagnostic performance, sensitivity and specificity for predicting spontaneous delivery<34 weeks was defined too. RESULTS: About 13/116 women gave birth before 34 weeks. The three ROC curves differed significantly at the 0.05 level. The best cutoff points were CL≤35 mm at 22 weeks, CL≤25 mm at 27 weeks and cervical shortening≥20%. For equal sensitivity values for each, specificity for CL≤25 mm at 27 weeks was 87.5%, significantly better. CONCLUSIONS: The performance of cervical shortening for the prediction of preterm delivery of asymptomatic twins before 34 weeks does not differ from that of CL measurements at 22 or 27 weeks. The modest predictive value of CL at 22 weeks and of cervical shortening is an argument against recommending routine CL measurements.
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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 | 0.002 | 0.011 |
| 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 | 0.001 | 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".