Patients with inflammatory bowel disease have a higher chance of developing periodontitis: A systematic review and meta-analysis
Bibliographic record
Abstract
Background and objective Periodontitis affects up to one billion people worldwide, and has been proven to be associated with several systemic inflammatory conditions. This study investigates the specific relationship between two multifactorial diseases: Inflammatory bowel disease (IBD) and periodontitis. To thoroughly explore this issue, we investigated separately whether IBD patients have a higher chance of developing periodontitis, and equally, whether patients with periodontitis have a higher chance of developing IBD. Methods The systematic search was performed in three databases: MEDLINE, Cochrane Trials, and Embase, up to 26 October 2021. The protocol was registered in PROSPERO. All eligible studies investigating the association between IBD and periodontitis from either direction were included. The Newcastle-Ottawa Scale was used to assess the risk of bias. As a primary outcome, we investigated the prevalence of IBD and periodontitis, and calculated the odds ratio (OR). Our secondary outcomes involved comparing the clinical periodontal outcomes of IBD patients to those of IBD-free patients. Results The systematic search resulted in 1,715 records, 14 of which were eligible for qualitative synthesis and 8 for quantitative synthesis. On the basis of the results of the primary outcome, IBD diagnosis was associated with significantly higher odds of periodontitis: OR = 2.65 (CI: 2.09-3.36, I2 = 0 (CI: 0-0.75)). For subgroup analysis, we investigated separately the odds in Crohn’s disease (CD) patients: OR = 2.22 (CI: 1.49-3.31, I2 = 0.05 (CI: 0-0.76)) and in ulcerative colitis (UC) patients: OR = 3.52 (CI: 2.56 to 4.83, I2 = 0 (CI: 0-0.75)); the odds were significantly higher in all cases. Two studies investigated whether patients with periodontitis were more susceptible to IBD, and both found that periodontitis was significantly associated with the risk of subsequent UC, but not with subsequent CD. However, more studies are needed to prove an association. Conclusion Our analysis confirmed that IBD patients have a higher chance of developing periodontitis, and are a higher risk population in dentistry. Both dentists and gastroenterologists should be aware of this relationship and should emphasize the importance of prevention even more than in the healthy population. Systematic review registration [ https://www.crd.york.ac.uk/prospero/ ], identifier [CRD42021286161].
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.036 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".