The effect of smoking on osseointegrated dental implants. Part II: Peri-implant bone loss.
Bibliographic record
Abstract
PURPOSE: The detrimental effect of cigarette smoking on implant survival has been previously demonstrated. The purpose of this study was to retrospectively investigate the effect of smoking on marginal bone loss around endosseous dental implants. MATERIALS AND METHODS: The sample consisted of 767 Brånemark implants placed in 235 patients between 1979 and 1999. Bone level changes were determined using periapical radiographs taken at annual recall visits for 1 to 20 years following prosthesis insertion. Nonparametric tests and multiple linear regression were used to determine the influence of various factors on peri-implant bone loss during the first year of clinical loading and for all subsequent years. RESULTS: The mean annual bone loss was 0.178 mm +/- 0.401 during the first year of clinical loading and 0.066 mm +/- 0.227 per year thereafter. A positive smoking history was associated with a higher rate of peri-implant bone loss, and the majority of implant failures were observed in this group of patients. Smoking at the time of stage 1 surgery did not appear to predispose implants to more marginal bone loss. CONCLUSION: Cigarette smoking should not be an absolute contraindication for implant therapy; rather, long-term heavy smokers must be informed that they are at a slightly higher risk of late implant failure and are susceptible to more marginal bone loss over the long-term, irrespective of their smoking status at the time of implant placement.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".