Periodontal systemic associations: review of the evidence
Bibliographic record
Abstract
AIM: To critically appraise recent research into associations between periodontal disease and systemic diseases and conditions specifically respiratory disease, chronic kidney disease, rheumatoid arthritis, cognitive impairment, obesity, metabolic syndrome and cancer. METHODS: A MEDLINE literature search of papers published between 2002 and April 2012 was conducted. Studies that included periodontitis as an exposure were identified. Cross-sectional epidemiological investigations on large samples, prospective studies and systematic reviews formed the basis of the narrative review. A threshold set for the identification of periodontitis was used to identify those studies that contributed to the conclusions of the review. RESULTS: Many of the investigations were cross-sectional secondary analyses of existing data sets in particular the NHANES studies. There were a small number of systematic reviews and prospective studies. There was substantial variability in the definitions of exposure to periodontitis. A small number of studies met the threshold set for periodontitis and supported associations; however, in some of the chronic diseases there were no such studies. There was strong evidence from randomized controlled trials that interventions, which improve oral hygiene have positive effects on the prevention of nosocomial pneumonias. CONCLUSIONS: There was substantial heterogeneity in the definitions used to identify periodontitis and very few studies met a stringent threshold for periodontitis. Published evidence supports modest associations between periodontitis and some, although not all, of the diseases and conditions reviewed. There is a need to reach a consensus on what constitutes periodontitis for future studies of putative associations with systemic diseases.
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 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".