Impact of jaw location on clinical and radiological status of dental implants placed in cigarette‐smokers and never‐smokers: 5‐year follow‐up results
Bibliographic record
Abstract
PURPOSE: The aim of this 60 months follow-up investigation was to investigate the impact of jaw location on clinical and radiological status of dental-implant therapy in cigarette-smokers and never-smokers. MATERIALS AND METHODS: Twenty-nine self-reported cigarette-smokers and 27 nonsmokers were assessed. All implants were categorized into three regions with reference to their location in the maxilla or mandible: (a) Anterior zone: implants located in anterior teeth; (b) Middle zone: Implants located in the premolar region; and (c) posterior zone: implants located in the molar region. Peri-implant crestal bone loss (CBL), bleeding-on-probing (BOP) and probing-depth (PD) ≥ 4 mm and were assessed. Level of statistical significance was set at P < .05. RESULTS: Mean age of cigarette-smokers (n = 29) and never-smokers (n = 27) was 44.5 years (39-51 years) and 43.6 years (35-49 years), respectively. The average duration of cigarette-smoking was 20.3 years (17-26 years). The mean periimplant PD (P < .05) and CBL (P < .05) were significantly higher in cigarette-smokers in contrast to never-smokers in all zones. No statistically significant differences in CBL, PD, and BOP were observed in the three zones of implant location among cigarette-smokers and never-smokers. CONCLUSION: Smoking enhanced PD and CBL around dental implants and this relationship was independent of site of implant placement and jaw location.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".