A Systematic Review of Clinical Efficacy of Adjunctive Antibiotics in the Treatment of Smokers With Periodontitis
Bibliographic record
Abstract
BACKGROUND: The aim of this study is to systematically review the evidence of the efficacy of adjunctive antibiotic therapy to periodontal therapy in smokers with periodontitis. METHODS: A search was conducted for randomized clinical trials (RCTs) with durations ≥6 months that compared periodontal therapy with and without adjunctive antibiotics for the treatment of periodontitis in smokers. Data sources primarily included PubMed with MeSH terms and free text as well as EMBASE, SCOPUS, and the Cochrane Central Register of Controlled Clinical Trials. In addition, a hand search of selected periodontal journals, bibliographies, and review articles was conducted. Independent reviewers were assigned to make independent searches and quality assessments (MA and DB) of the included studies, and disagreements were resolved by discussion. RESULTS: Five RCTs were selected for quantitative and qualitative assessments. Little evidence was found that supported the use of antibiotic therapy in conjunction with surgical periodontal therapy in smokers. With respect to non-surgical therapy, consistent improvements in clinical attachment level (CAL) gain and probing depth (PD) reduction was reported after the use of a 250-mg azithromycin tablet in one study. Adjunctive doxycycline gel and minocycline microspheres statistically improved CAL gain (in one RCT) and PD reduction (in one RCT), respectively. However, the risk of bias in all studies was estimated as high. Also, inadequate and inconsistent data precluded performing meta-analyses. CONCLUSIONS: The present systematic review concludes that the evidence for an additional benefit of adjunctive antibiotic therapy in smokers with chronic periodontitis is insufficient and inconclusive. Additional well-designed RCTs are required to assess the effect of antibiotics in conjunction with periodontal treatments in smokers.
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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 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".