Midtrimester Cervical Length in Low-Risk Nulliparous Women for the Prediction of Spontaneous Preterm Birth: Should We Consider a New Definition of Short Cervix?
Bibliographic record
Abstract
OBJECTIVE: The study aimed to estimate the predictive value of midtrimester cervical length (CL) and the optimal cut-off of CL that should be applied with asymptomatic nulliparous women for the prediction of spontaneous preterm birth (sPTB). STUDY DESIGN: This is a prospective cohort study of asymptomatic nulliparous women with a singleton gestation. Participants underwent CL measurement by transvaginal ultrasound between 20 and 24 weeks of gestation. The participants and their health care providers remained blinded to the results of CL measurement. The primary outcomes were sPTB before 35 weeks and sPTB before 37 weeks. Receiver operating characteristics (ROC) curve analyses were performed. Analyses were repeated by using multiples of median (MoM) of CL adjusted for gestational age. RESULTS: < 0.001). We observed similar results using a cut-off of CL <0.75 MoM adjusted for gestational age. CONCLUSION: A midtrimester CL cut-off of 30 mm (instead of 25 mm), or CL less than 0.75 MoM, should be used to identify nulliparous women at high risk of sPTB. KEY POINTS: · The optimal CL cut-off for the prediction of sPTB is 30 mm in nulliparous women.. · In nulliparous women, a midtrimester CL < 30 mm is highly associated with sPTB before 35 and 37 weeks.. · A midtrimester of CL <30 mm (5th percentile) should define a short cervix in asymptomatic nulliparous 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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".