Association between Periodontal Disease and cognitive impairment in Adults
Bibliographic record
Abstract
Introduction: Periodontitis is a severe oral infection that can contribute to systemic inflammation. A large body of evidence suggests a role for systemic inflammation in the initiation of neurodegenerative disease. This systematic review synthesized data from observational studies to investigate the association between periodontitis and neuroinflammation in adults. Methods and materials: A systematic literature search of PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) was performed for studies published from the date of inception up to September 2021. Search terms for the exposure “oral disease” and outcome “dementia”, “neuroinflammation” and “cognitive decline” were used. Study selection and data extraction were independently undertaken by two reviewers. The final eligible articles were included only if the exposure is periodontitis and the outcome is cognitive impairment or dementia or a topic related to this condition, and if the study was conducted in an adult population. The quality and risk of bias were assessed by Newcastle Ottawa Scale (NOS). Qualitative synthesis was used to narratively synthesize the results. Six cohort studies, three cross-sectional studies, and two case-control studies met the inclusion criteria. These eleven studies were only narratively synthesized. Meta-analysis was not performed due to the methodological heterogeneity of the studies. Results: All the included studies show evidence of an association between periodontitis and cognitive im-pairment or dementia and Alzheimer’s disease pathology. Conclusion: Nonetheless, the mechanisms responsible for the association between periodontitis and dementia are still unclear.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".