Association between metabolic syndrome and periodontitis: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract The aim of the present study was to evaluate the association between metabolic syndrome (MS) and periodontitis (PD), through a systematic review and meta-analysis. Original observational studies assessing the association between MS and PD in adults, published before May 11th (2017), were identified through electronic searches of MEDLINE, EMBASE and Cochrane Library databases. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline was used. For studies to be included, they had to mention the criteria used to diagnose MS and to have used at least one clinical measure to diagnose PD. There was no language restriction. Three reviewers independently identified eligible studies for possible inclusion in the systematic review and meta-analysis. The quality of the studies was evaluated by the Newcastle-Ottawa scale for observational studies. A random model meta-analysis was conducted. The strategies used to investigate heterogeneity were sequential analysis, subgroup analysis, univariate meta-regression and sensitivity analysis. Thirty-three studies met the inclusion criteria for the systematic review, and 26 had enough information to be included in the meta-analysis, totaling 52,504 patients. MS and PD were associated with an odds ratio of 1.38 (95%CI 1.26–1.51; I2 = 92.7%; p < 0.001). Subgroup analysis showed that complete periodontal examination (I2 = 70.6%; p < 0.001) partially explained the variability between studies. The present findings suggest an association between MS and PD. Individuals with MS are 38% more likely to present PD than individuals without this condition. Prospective studies should be conducted to establish cause and effect relations between MS and PD.
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.043 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 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".