Efficacy of metformin in the management of periodontitis: A systematic review and meta-analysis
Bibliographic record
Abstract
Periodontitis is characterized by inflammation of the periodontium and leads to loss of teeth if untreated. Although a number of surgical and pharmacological options are available for the management of periodontitis, it still affects a large proportion of population. Recently, metformin (MF), an oral hypoglycemic, has been used to treat periodontitis. The aim of this review is to systematically evaluate the efficacy of MF in the treatment of periodontitis. An electronic search was carried out using the keywords 'metformin', 'periodontal' and 'periodontitis' via the PubMed/Medline, ISI Web of Science and Google Scholar databases for relevant articles published from 1949 to 2016. The addressed focused question was: 'Is metformin effective in reducing bone loss in periodontitis? Critical review and meta-analysis were conducted of the results obtained in the selected studies. Following the removal of the duplicate results, the primary search resulted in 17 articles and seven articles were excluded based on title and abstract. Hence, 10 articles were read completely for eligibility. After exclusion of four irrelevant studies, six articles were included. The topical application of MF resulted in improved histological, clinical and radiographic outcomes. Additionally, results from the meta-analysis indicated that application of metformin improved the clinical and radiographic outcomes of scaling and root-planing, but at the same time heterogeneity was evident among the results. However, because of a lack of histological and bacterial studies, in addition to short follow-up periods and risk of bias, the long-term efficacy of MF in the treatment of bony defects is not yet ascertained. Further studies are needed to envisage the long-term efficacy of MF in the management of periodontitis.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".