Evaluation of the association between periodontitis and inflammatory bowel disease: A systematic review and Meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Several studies have shown a connection between periodontal diseases and conditions such as heart disease, diabetes, and pregnancy. This study aimed to investigate the relationship between inflammatory bowel disease (IBD), including ulcerative colitis (UC), Crohn's disease (CD), and periodontitis. METHODS: A systematic study was conducted in seven databases (PubMed, Scopus, Web of Science, ProQuest, Embase, Cochrane, and ScienceDirect) from 1960 to December 30, 2024. Articles investigating the relationship between periodontitis and IBD were selected based on established inclusion and exclusion criteria. The quality of the selected articles was assessed using the Newcastle-Ottawa checklist. The prevalence of periodontitis in individuals with and without IBD, as well as in each subgroup (UC and CD), was reported in terms of odds ratio (OR). Data analysis was conducted using Comprehensive Meta Analysis (CMA) software. RESULTS: Eleven studies were included in this systematic review. Statistical analysis of 10 studies revealed that, compared to the control group (without IBD), IBD patients had a significantly higher likelihood of periodontitis (OR: 2.28; 95% confidence interval [CI]: 1.73-3). Within each IBD subgroup, the likelihood of periodontitis was higher compared to the control group. The risk of developing periodontitis in patients diagnosed with UC and CD was found to be (OR: 3.14; 95% CI: 2.11-4.66) and (OR: 1.99; 95% CI: 1.4-2.83), respectively. However, this discrepancy was not statistically significant (P = 0.09). CONCLUSIONS: IBD was associated with a higher likelihood of periodontitis compared to non-IBD patients. However, However, additional longitudinal research studies with larger sample sizes are necessary to validate this association and potentially reveal shared underlying mechanisms.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".