The Association Between Periodontal Inflammation and Labor Triggers (Elevated Cytokine Levels) in Preterm Birth: A Cross‐Sectional Study
Bibliographic record
Abstract
BACKGROUND: Periodontitis is considered to be a risk factor for preterm birth. Mechanisms have been proposed for this pathologic relation, but the exact pathologic pattern remains unclear. Therefore, the objective of the present study is to evaluate levels of four major labor triggers, prostaglandin E2 (PGE2), interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α, in gingival crevicular fluid (GCF) and serum samples between women with preterm birth (PTB) and full-term birth (FTB) and correlate them with periodontal parameters. METHODS: PGE2, IL-1β, IL-6, and TNF-α levels were estimated using enzyme-linked immunosorbent assays in GCF and serum samples collected 24 to 48 hours after labor from 120 women (60 FTB, 60 PTB). RESULTS: Women with PTB exhibited significantly more periodontitis, worse periodontal parameters, and increased GCF levels of IL-6 and PGE2 compared with the FTB group; there were no significant differences in serum levels of measured markers. GCF levels of IL-1β, IL-6, and PGE2 and serum levels of TNF-α and PGE2 were significantly higher in women with periodontitis compared with periodontally healthy women. Serum levels of PGE2 were positively correlated with probing depth (PD) and clinical attachment level (CAL) as well as with GCF levels of TNF-α in women with PTB. CONCLUSIONS: Women with PTB demonstrated worse periodontal parameters and significantly increased GCF levels of IL-6 and PGE2 compared with those with FTB. Based on significant correlations among serum PGE2 and PD, CAL, and GCF TNF-α in PTB, periodontitis may cause an overall increase of labor triggers and hence contribute to preterm labor onset.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".