First-trimester cervical length screening and the risk of preterm birth: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The clinical utility of first-trimester cervical length (CL) measurement remains uncertain. This systematic review and meta-analysis aimed to evaluate the association between first-trimester CL measurement and preterm birth (PTB) risk. METHODS: This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered in PROSPERO (CRD42023462610). A comprehensive search was conducted across four electronic databases (PubMed, Scopus, Web of Science, and Cochrane Library) until January 29, 2024, using MeSH terms and keywords. We included randomized controlled trials, comparative observational studies, and retrospective studies that examined first-trimester CL measurement and reported PTB as a primary or secondary outcome. Two independent reviewers conducted study selection and data extraction, resolving discrepancies through discussion. Risk of bias was assessed using the Newcastle-Ottawa Scale. A meta-analysis using a random-effects model was conducted, with heterogeneity evaluated via I² statistics. RESULTS: Five studies comprising 16,053 pregnancies were included. CL was significantly shorter in individuals delivering before 34 weeks compared to those delivering at or after 34 weeks, with a pooled mean difference of -0.59 mm (95% confidence interval [CI]: -1.14 to -0.04; p = 0.04; I²=72.56%). Similarly, those delivering before 37 weeks had a significantly shorter CL than those delivering at or after 37 weeks, with a pooled mean difference of -0.23 mm (95% CI: -0.43 to -0.03; p = 0.02; I²=76.26%). CONCLUSION: First-trimester CL measurement is significantly associated with PTB risk. However, due to study heterogeneity and physiological variability in early pregnancy, its clinical utility as a predictive tool remains uncertain. Further research with standardized protocols and larger cohorts is needed to assess its role in screening and early intervention strategies for both low- and high-risk pregnancies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".