Progression of Periodontal Disease in a Maintenance Population of Smokers and Non‐Smokers: A 3‐Year Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Cigarette smoking is accepted as an important factor that increases the risk for the initiation and progress of chronic periodontitis. However, the effect of cigarette smoking on the recurrence of disease in patients undergoing regular maintenance therapy is less understood. Therefore, we set out to assess disease progression longitudinally in smoking and non-smoking subjects with chronic periodontitis undergoing periodontal maintenance therapy every 3 to 4 months. METHODS: A total of 108 subjects undergoing regular maintenance therapy for chronic periodontitis were followed over a 3-year period. Self-reports of smoking status were confirmed by analysis of exhaled carbon monoxide concentrations. Clinical parameters (plaque index [PI], bleeding on probing [BOP], clinical attachment loss [CAL], probing depth [PD], and tooth loss) were recorded at yearly reevaluation visits. The study was carried out in a university hospital setting. RESULTS: Longitudinal measurements were obtained from 81 (75%) subjects. There were no differences in inflammatory indices at baseline or over time (PI and BOP; both P >0.05) between smokers (N = 16; age: 54 +/- 6 years) and non-smokers (N = 65; age: 59 +/- 14 years). Likewise, there was no difference between the smoking groups with respect to disease progression (measured as changes in prevalence [number] and proportion [percentage] of progressing sites and as mean CAL, PD, and tooth loss; all P >0.05). CONCLUSION: In this small population, regular maintenance treatment in a cross-section of highly motivated subjects with chronic periodontitis seemed to be equally successful in preventing progressive periodontal tissue destruction in current smokers and current non-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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".