Impact of amniotic fluid “sludge” on the risk of preterm delivery
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of amniotic fluid "sludge" (AFS) on the risk of preterm delivery and to describe the effect of antibiotic treatment in that situation. METHODS: Case-control study including singleton pregnancies with or without AFS, between 15-32 weeks of gestation. Factors associated with preterm delivery before 32 weeks, 34 weeks and 37 weeks were evaluated with univariate and multivariate logistic regression. Since all women with AFS in this study were treated with antibiotics, a historical comparison was performed with similar patients with AFS found before 2007 and not treated with antibiotics. RESULTS: AFS was observed in 90/1220 patients (7.4%). AFS was associated with shorter cervical length, greater body mass index, cervical cerclage and preterm birth before 28 weeks. However, after adjustment, AFS did not remain associated with preterm delivery before 32 or 34 weeks. The historical comparison suggested that azithromycin could significantly reduce the risk of preterm delivery before 34 weeks (odds ratio: 0.2; 95% CI: 0.04-0.92). CONCLUSIONS: AFS, treated with azithromycin, was associated with a higher risk of prematurity, but not independently after adjustment for cervical length and second trimester vaginal bleeding. Further studies need to evaluate the effect of antibiotics in pregnancies with AFS.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".