Evaluation of Factors Influencing the Marginal Bone Stability around Implants in the Treatment of Partial Edentulism
Bibliographic record
Abstract
BACKGROUND: The original protocol of Brånemark to achieve predictable osseointegration for oral implants has substantially been modified. One may question whether results are influenced by those modifications, especially for the long-term prognosis. PURPOSE: The goal of the present study was to investigate the impact of those parameters that deviate from the original protocol as defined by P-I Brånemark. MATERIALS AND METHODS: In this study, 246 patients with 263 fixed partial prostheses supported by 668 Brånemark implants were followed from 1 to 15 years (mean: 6.3 yr). Radiographs were taken at the time of abutment connection, at 3 to 6 months, at 12 months, and then every 3 years. The bone level was rated mesially and distally from the implants on a total of 2588 radiographs. RESULTS: A positive relation between abutment length and marginal bone level was found (p > .0001). The maxilla (p = .03), porcelain (p = .007), long abutments (p = .008), and regular-sized diameter implants (p = .001) all exhibited more bone loss in the first 6 months. After 6 months, only long implants showed more bone loss (p = .03). CONCLUSIONS: Overall, the marginal bone level remained stable around Brånemark implants, never surpassing 2.2 mm, even after 15 years. Although longer implants lost more bone over time, this has to be interpreted with respect to higher resorption rates in less resorbed jaws.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".