Inflammatory Cytokines and Spontaneous Preterm Birth in Asymptomatic Women
Bibliographic record
Abstract
OBJECTIVE: To estimate the association between inflammatory cytokines and the risk of spontaneous preterm birth in asymptomatic women. DATA SOURCES: We searched electronic databases of the human literature in PubMed, EMBASE, and the Cochrane Library up to February 2010 using the following key words: "preterm/pre-term + (birth/delivery)" and "cytokine" or "inflammation/inflammatory + marker/biomarker." METHODS OF STUDY SELECTION: We included observational studies that reported the association between common inflammatory cytokines and spontaneous preterm birth as an outcome in asymptomatic women. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using fixed and random effects models. TABULATION, INTEGRATION, AND RESULTS: Seventeen primary studies comprising 6,270 participants met the inclusion criteria. Spontaneous preterm birth was strongly associated with increased levels of interleukin-6 (IL-6) in midtrimester cervicovaginal fluid (OR 3.05, 95% CI 2.00-4.67) (number needed to treat=7 for identifying an additional preterm delivery) and amniotic fluid (OR 4.52, 95% CI 2.67-7.65) (number needed to treat=7), but there was no association in plasma specimen (OR 1.5, 95% CI 0.7-3.0). Spontaneous preterm birth was strongly associated with increased C-reactive protein (CRP) levels in midtrimester amniotic fluid (OR 7.85, 95% CI 3.88-15.87) (number needed to treat=3), but the association was weak in plasma specimen (OR 1.53, 95% CI 1.22-1.90). There were insufficient data (fewer than three studies) for meta-analysis in other inflammatory cytokines. CONCLUSION: Inflammatory cytokine IL-6 in cervicovaginal fluid and IL-6 and CRP in amniotic fluid but not in plasma are strongly associated with spontaneous preterm birth in asymptomatic women, suggesting that inflammation at the maternal-fetal interface, rather than systemic inflammation, may play a major role in the etiology of such spontaneous preterm births.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".