Impact of supragingival therapy on subgingival microbial profile in smokers versus non-smokers with severe chronic periodontitis
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to assess subgingival microbiological changes in smokers versus non-smokers presenting severe chronic periodontitis after supragingival periodontal therapy (ST). METHODS: Non-smokers (n=10) and smokers (n=10) presenting at least nine teeth with probing pocket depth (PPD) (≥5 mm), bleeding on probing (BoP), and no history of periodontal treatment in the last 6 months were selected. Clinical parameters assessed were plaque index (PI), BoP, PPD, relative gingival margin position (rGMP) and relative clinical attachment level (rCAL). Subgingival biofilm was collected before and 21 days after ST. DNA was extracted and the 16S rRNA gene was amplified with the universal primer pair, 27F and 1492R. Amplified genes were cloned, sequenced, and identified by comparison with known 16S rRNA sequences. Statistical analysis was performed by Student's t and Chi-Square tests (α=5%). RESULTS: Clinically, ST promoted a significant reduction in PI and PPD, and gain of rCAL for both groups, with no significant intergroup difference. Microbiologically, at baseline, data analysis demonstrated that smokers harbored a higher proportion of Porphyromonas endodontalis, Bacteroidetes sp., Fusobacterium sp. and Tannerella forsythia and a lower number of cultivated phylotypes (p<0.05). Furthermore, non-smokers featured significant reductions in key phylotypes associated with periodontitis, whereas smokers presented more modest changes. CONCLUSION: Within the limits of the present study, ST promoted comparable clinical improvements in smokers and non-smokers with severe chronic periodontitis. However, in smokers, ST only slightly affected the subgingival biofilm biodiversity, as compared with non-smokers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".