Retrospective radiographic observational study of 1692 Straumann tissue‐level dental implants over 10 years. II. Marginal bone stability
Bibliographic record
Abstract
BACKGROUND: Despite accumulating evidence for the longitudinal stability of the marginal bone level around an implant, there is limited evidence of predisposing risk factors for marginal bone loss based on some implants in a relatively large patient population. PURPOSE: The aim of this study was to retrospectively determine the marginal bone loss around Straumann tissue-level dental implants during follow-up periods among which the maximum lasts up to 10 years, as well as the predisposing risk factors for peri-implant marginal bone loss. MATERIALS AND METHODS: This study analyzed 1692 Straumann tissue-level dental implants in 881 patients, and relevant data were collected. The peri-implant marginal bone level was measured on periodic radiographs, and the changes in bone level were analyzed cumulatively from surgery until up to 10 years later. The log-rank test was used to select candidate critical risk factors for marginal bone loss, and multivariate analysis using Cox regression with the shared frailty model was performed. RESULTS: The overall peri-implant bone loss was 0.07 ± 0.21mm, 0.09 ± 0.26mm, 0.14 ± 0.41mm, and 0.17 ± 0.45mm at 3, 5, 7, and 9 years, respectively. Only 14 implants showed pathologic marginal bone loss exceeding 2mm during the follow-up period. While 2 implants were removed with continuous progressive marginal bone loss, 5 of the 14 implants showed early bone loss exceeding 1mm within the first year but then subsequently tended to show a stable marginal bone level. In the other seven implants, bone loss started after the first year and progressed continuously. Multivariate analysis revealed that diameter of the implant affected the peri-implant marginal bone loss. CONCLUSIONS: Straumann tissue-level dental implants showed only slight peri-implant marginal bone loss, with a very low incidence of pathologic marginal bone loss exceeding 2mm.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.001 |
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".