Association of chronic periodontitis with chronic migraine: A systematic review and meta-analysis
Bibliographic record
Abstract
Chronic periodontitis (CP) is a chronic inflammatory disease, primarily caused by microbial infections and characterized by immune system dysfunction. The latter ultimately leads to the progressive destruction of the alveolar bone supporting the teeth in the jawbones. Chronic migraine (CM) is a complex disorder characterized by repetitive episodes of moderate to severe headaches that unfold over hours to days. The episodes are usually unilateral and generally associated with nausea and light and/or sound stimuli sensitivity. The disease is a common cause of disability and loss of working hours, as it significantly burdens the patient's daily life. CP and CM association is clinically relevant as both involve inflammatory mechanisms and immune dysfunction. To systematically review the literature on the epidemiological association between CP and CM in adults. The study protocol followed the PRISMA 2020 statement. The design of the study adhered to the Cochrane methodology. A comprehensive literature search was conducted in PubMed, Scopus, and Cochrane databases, as well as a manual search and evaluation of gray literature sources. The Review Manager (RevMan) 5.4 software was used for the meta-analysis. The effect size of the outcome was expressed as odds ratio (OR) with a 95% confidence interval (CI), providing a measure of the association between CP and CM. The Chi-square test and I2 statistic were employed to assess heterogeneity among the included studies. The inclusion criteria were English language, observational (case-control) design, and report of the diagnostic criteria for CP and CM. Duplicate entries were excluded. The reliability and quality of the included studies were assessed using the Newcastle-Ottawa Scale (NOS) and GRADE tools. Two independent reviewers performed all evaluations and a third resolved discrepancies. The meta-analysis included three observational studies with 522 participants. CM patients were 2.82 times more likely to be diagnosed with CP compared with healthy controls. This association was statistically significant (OR 2.82, 95% CI 1.96–4.05, p<0.0001); however, the external generalizability is limited because of the examination of data originating from populations with specific ethnic backgrounds. A high prevalence of CP was found among patients with CM compared with healthy controls. Healthcare professionals should be aware of the correlation between these pathological conditions to provide patients with high-quality care through an effective and comprehensive diagnostic and therapeutic approach.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.027 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".