Prognostic value of cervical length for spontaneous preterm birth in asymptomatic women with twin pregnancy: meta-analysis of individual participant data
Bibliographic record
Abstract
Objective: To quantify the prognostic value of mid-trimester cervical length for spontaneous preterm birth in asymptomatic women with twin pregnancy and to assess whether other factors may modify any association. Designs: A two stage meta-analysis of individual participant data in a Cox proportional hazard model was performed using cervical length as a continuous variable. Data sources: Medline, Embase, Cochrane, and LILACS, among others, were searched to identify eligible studies; the search was from 1 January 2000 to 30 September 2020. Risk of bias was assessed with the QUIPS tool. Studies were from eight countries between 2001 and 2018. Eligibility criteria: Individual participant data were sought for eligible studies that reported mid-trimester (defined between 16 and 26 weeks) transvaginal sonographic cervical length and also gestational age at birth in asymptomatic women with twin pregnancy. The primary outcome was spontaneous preterm birth before 37 weeks. Results: Among 29 eligible studies, authors of 17 studies provided individual participant data for 6437 women with a twin pregnancy (69.1% of individual participant data). Mean cervical length measurement was 39 mm (SD=9, range 1-74 mm). 2889 women (44.9%) delivered before 37 weeks' gestation, and 934 (14.9%) delivered before 34 weeks. Each 1 mm increase in cervical length was associated with a 4.0% reduction in the rate of spontaneous preterm birth before 37 weeks (hazard ratio 0.96 (95% confidence interval 0.95 to 0.97)), and a 6.8% reduction in the rate of spontaneous preterm birth before 34 weeks' gestation (0.93 (0.92 to 0.95)). The prognostic value remained stable in models adjusting for different sets of variables. Conclusion: The prognostic value of cervical length for spontaneous preterm birth in twin pregnancy is on a continuous scale. No specific cervical length has been identified that can reliably predict or exclude all spontaneous preterm births. Study registration: CRD42020146987.
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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 | 0.026 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.058 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".