A DISBIOSE DA MICROBIOTA SUBGENGIVAL E O PARTO PREMATURO: UMA REVISÃO SISTEMÁTICA
Bibliographic record
Abstract
The mechanism of association between periodontitis and increased risk of adverse pregnancy outcomes is still a gap in scientific knowledge. The objective of this systematic review was to systematize knowledge about the association between the level of dysbiosis of the subgingival microbiota and prematurity. This is a cross-sectional, case-control or cohort study were eligible in this systematic review, searched in PubMed / MEDLINE, Web of Science, SCOPUS, Scielo, Lilacs, published until April 2020. This search was conducted using the descriptors: " Periodontitis", "Periodontal Disease", "Oral Dysbiosis", "Oral Microbiome", "Prematurity" and "Preterm". The outcomes were premature birth or premature rupture of membranes. The Newcastle - Ottawa scale was used by two independent reviewers to assess the quality of the studies. As a result, 266 studies were relevant in this systematic review. 59 articles were selected to read the full text. The inclusion criteria were met by seventeen studies: nine case-control studies, three cross-sectional studies and five cohort studies. The findings showed that the increased risk of premature birth may be associated with the degree of periodontal dysbiosis, with the main action being the green complex periodontopathogens, as long as they are grouped with the red and orange complexes. This systematic review indicates that there may be an association between dysbiosis in the subgingival microbiota and prematurity outcomes, highlighting the non-exclusive contribution of traditional key pathogens of periodontitis.
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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 | 0.014 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".