Inflammation Mediators Related to Periodontal Disease and Pregnancy Outcomes: A Call for Quality of Antenatal Care While Promising Evidences Are Emerging
Bibliographic record
Abstract
Infections may play a significant role in the induction of births and prematurity. Periodontal disease could be a risk factor for pregnancy outcomes such as preterm birth, and low birth weight. Possible mechanisms of this relationship are the production of inflammatory mediators and cytokines like C-reactive protein (CRP), prostaglandin E2 (PGE2), matrix metalloproteinases, interleukin 1 (IL-1), IL-6, and tumor necrosis factor alfa (TNF-a); the translocation of periodontal pathogens to the feto-placental unit through blood stream, a periodontal reservoir of lipopolysaccharides (LPS); and shared risk factors. Although this knowledge is just emerging, it has important implications for the health services and the healthcare delivery model. Committed health teams to an interprofessional collaborative work within the health services can raise the quality of antenatal care. Population strategies directed to prevent and control periodontal disease can increase the periodontal health of the majority of people and affect positively risk groups. These inexpensive basic measures joined with other actions at different levels could enhance the quality of antenatal care and contribute for favorable pregnancy outcomes. Further researches need to clarify the evidences on those relationships.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".