Risk of recurrent spontaneous preterm birth: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To determine the risk of recurrent spontaneous preterm birth (sPTB) following sPTB in singleton pregnancies. DESIGN: Systematic review and meta-analysis using random effects models. DATA SOURCES: An electronic literature search was conducted in OVID Medline (1948-2017), Embase (1980-2017) and ClinicalTrials.gov (completed studies effective 2017), supplemented by hand-searching bibliographies of included studies, to find all studies with original data concerning recurrent sPTB. STUDY ELIGIBILITY CRITERIA: Studies had to include women with at least one spontaneous preterm singleton live birth (<37 weeks) and at least one subsequent pregnancy resulting in a singleton live birth. The Newcastle-Ottawa Scale was used to assess study quality. RESULTS: Overall, 32 articles involving 55 197 women, met all inclusion criteria. Generally studies were well conducted and had a low risk of bias. The absolute risk of recurrent sPTB at <37 weeks' gestation was 30% (95% CI 27% to 34%). The risk of recurrence due to preterm premature rupture of membranes (PPROM) at <37 weeks gestation was 7% (95% CI 6% to 9%), while the risk of recurrence due to preterm labour (PTL) at <37 weeks gestation was 23% (95% CI 13% to 33%). CONCLUSIONS: The risk of recurrent sPTB is high and is influenced by the underlying clinical pathway leading to the birth. This information is important for clinicians when discussing the recurrence risk of sPTB with their patients.
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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 | 0.022 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.050 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".