Preterm delivery and ultrasound measurement of cervical length in Gran Canaria, Spain
Bibliographic record
Abstract
OBJECTIVE: To study the relationship between cervical length measured by ultrasound and risk of preterm delivery. METHODS: We measured cervical length in 2351 women between the 18th and 22nd week of pregnancy. Preterm delivery was categorized as before 37 weeks, before 34 weeks, and before 30 weeks. RESULTS: Before the 37th week, the odds ratios (ORs) of spontaneous delivery for cervical lengths in the 3rd, 5th, and 10th percentiles were, respectively, 25.47 (95% confidence intervals [CI], 15.5-41.73); 16.98 (95% CI, 11.51-25.05); and 7.55 (95% CI, 5.44-10.5). Before the 34th week the ORs were 28.7 (95% CI, 14.54-41.73); 20.5 (95% CI, 11.51-25.05); and 10.3 (95% CI, 5.44-10.5). And before the 30th week they were 29.8 (95% CI, 15.54-41.73); 23.1 (95% CI, 11.51-25.05); and 19.1 (95% CI, 7.44-31.5). In predicting premature delivery, the sensitivity, specificity, positive predictive value, and negative predictive value of cervical length were 26%, 98%, 63.6%, and 93.57% for the 3rd percentile; 34%, 97%, 51%, and 94% for the 5th percentile; and 39%, 92%, 31%, and 94% for the 10th percentile. CONCLUSION: Transvaginal measurement of cervical length during routine fetal morphological examination between the 18th and 22nd week of pregnancy helps identify asymptomatic women at risk for preterm 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".