Association between periodontitis and dental caries: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Objectives Recent evidence suggested a link between periodontitis (PD) and dental caries, but the trends and nature of this association remained unclear. The overall aim of this study was to critically assess the correlation of two disorders. Methods A comprehensive search was conducted within the PUBMED and EMBASE databases including grey literatures up to July 5th, 2023. The Newcastle–Ottawa scale was used to qualitatively evaluate the risk of bias. Results Overall, 18 studies were included. In terms of caries risk in PD patients, the prevalence of caries was increased by PD (OR = 1.57, 95%CI:1.20–2.07), both in crown (OR = 1.03, 95%CI:1.01–1.05) and root caries (OR = 2.10, 95%CI:1.03–4.29). Odds of caries were also raised by PD severity (OR moderate = 1.38, 95%CI:1.15–1.66; OR severe = 2.14, 95%CI:1.74–2.64). Besides, patients with PD exhibited a higher mean number of decayed, missing and filled teeth (DMFT) and decayed and filled root teeth (DFR) [weighted mean difference (WMD)DMFT = 0.87, 95%CI: -0.03–1.76; WMDDFR = 1.13, 95%CI: 0.48–1.78]. Likewise, patients with caries had an elevated risk of PD (OR = 1.79, 95%CI:1.36–2.35). However, Streptococcus mutans, one of the main pathogens of caries, was negatively correlated with several main pathogens of periodontitis. Conclusions This study indicated a positive correlation between dental caries and periodontitis clinically, while the two disease-associated pathogens were antagonistic. Clinical relevance Further research, including clinical cohort studies and mechanisms of pathogens interaction is needed on this link for better prevention and treatment of PD and caries. In addition, innovative prevention strategies need to be developed and incorporated in dental practices to prevent these two highly prevalent oral diseases.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".