Biologie Outcome of Single‐Implant Restorations as Tooth Replacements: A Long‐term Follow‐up Study
Bibliographic record
Abstract
BACKGROUND: The replacement of a single tooth or several teeth by means of single-implant restorations is an increasingly used method that needs long-term validation. PURPOSE: The goal of this study was to evaluate the outcome of single-implant restorations by means of fixed restorations and to define the prognosis through marginal bone level estimations. MATERIALS AND METHODS: From November 1986 to June 1998, 270 Brånemark implants (215 in the upper jaw) were installed in 219 patients (106 males). Both anterior and posterior sites were involved. Of the 263 single restorations, 28 were placed in private dental offices. The patients were followed until June 1999. RESULTS: Twelve implants failed before or at abutment connection or within 6 months afterward. Only four implants failed later. The cumulative success rates were 93% for the implants and 96.5% for the restorations over a period of 11 years. The marginal bone loss during the first 6 months after abutment connection reached 0.71 mm and then dropped to 0.036 mm annually over a period of 10 years. CONCLUSIONS: Single-implant restorations (Brånemark System) are a reliable treatment with a good long-term prognosis. Failures were concentrated during the healing period and early loading phase.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".