The effect of smoking on osseointegrated dental implants. Part I: implant survival.
Bibliographic record
Abstract
PURPOSE: Recent studies implicate smoking as a significant factor in the failure of dental implants. The purpose of this long-term retrospective study was to evaluate the survival of Brånemark endosseous dental implants in relation to cigarette smoking. MATERIALS AND METHODS: The sample consisted of 464 consecutively treated completely and partially edentulous patients who had a total of 1852 implants placed between 1979 and 1999, and who were part of a surgical/prosthodontic prospective treatment outcomes study. The effect of cigarette smoking on implant survival in relation to the time of implant failure, gender, age, surgeon, date and site of implant placement, implant length and diameter, prosthesis design, and occlusal loading considerations was assessed in bivariate and multivariate survival analyses. RESULTS: The overall implant failure rate was 7.72%. Patients who were smokers at the time of implant surgery had a significantly higher implant failure rate (23.08%) than nonsmokers (13.33%). Multivariate survival analysis showed early implant failure to be significantly associated with smoking at the time of stage 1 surgery and late implant failure to be significantly associated with a positive smoking history. Short implants and implant placement in the maxilla were additional independent risk factors for implant failure. CONCLUSION: Cigarette smoking should not be an absolute contraindication for implant therapy; however, patients should be informed that they are at a slightly greater risk of implant failure if they smoke during the initial healing phase following implant insertion or if they have a significant smoking history.
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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".