Periodontal Health and Chronic Obstructive Pulmonary Disease (COPD) Exacerbations: A Systematic Review
Bibliographic record
Abstract
Abstract BackgroundA growing body of evidence suggests a role for oral bacteria in lung infections. This systematic review aimed to analyse the association between poor periodontal health and the frequency of chronic obstructive pulmonary disease (COPD) exacerbations. MethodsPubMed, Embase, Web of Science, CINAHL and Medline were searched for studies published until May 2020, with no language restriction. Studies reporting periodontal condition, or periodontal treatment outcomes, with data on the frequency of exacerbations of COPD, were identified. The primary outcome was the frequency of exacerbations and secondary outcomes included quality of life and hospitalisation. Studies were assessed for eligibility and quality by two assessors independently.Results Searches identified 532 records and 8 met the inclusion criteria. The data from intervention studies showed reduction in the frequency of exacerbations following periodontal treatment. Data from observational studies suggest association of worse plaque scores with exacerbation but not pocket depth or clinical attachment loss. Better periodontal health was also associated with reduced frequency of COPD exacerbations, hospitalisations and improved quality of life in COPD patients. Due to the high heterogeneity no meta-analysis was performed. The quality of some of the included studies was low and there was evidence of high risk of bias.ConclusionThe data supports possible association between poor periodontal health, the frequency of exacerbations and quality of life in COPD patients. The evidence is limited by high risk of bias suggesting need for well-designed and adequately powered randomised control trials.The PROSPERO registration number CRD42020180328
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".