The <scp>N</scp>obel<scp>G</scp>uide® <scp>A</scp>ll‐on‐4® Treatment Concept for Rehabilitation of Edentulous Jaws: A Prospective Report on Medium‐ and Long‐Term Outcomes
Bibliographic record
Abstract
BACKGROUND: There is a need for long-term studies on complete edentulous flapless rehabilitations. PURPOSE: This study aimed to evaluate the long-term outcomes of the rehabilitation of completely edentulous jaws for immediate function with the All-on-4® treatment concept using a computer-guided surgical protocol (NobelGuide®, Nobel Biocare, Göteborg, Sweden). MATERIALS AND METHODS: This prospective clinical study included 23 totally edentulous patients rehabilitated between February 2005 and May 2006 with 92 implants with the All-on-4 treatment concept using NobelGuide. Outcome measures were implant survival, marginal bone loss at 1, 3, and 5 years, and the incidence of mechanical and biological complications. Survival was calculated using life-table analysis. RESULTS: Two dropouts occurred. The cumulative implant survival rate was 96.6% at 5 years of follow-up. Prosthetic survival was 100%. The average marginal bone loss was 1.7 mm (standard deviation 1.4 mm) at 1 year, 1.7 mm (standard deviation 0.9 mm) at 3 years, and 1.9 mm (standard deviation 1.1 mm) at 5 years. Seven patients experienced fracture of the definitive prosthesis (6 patients were heavy bruxers), and abutment screw loosening occurred in 2 patients. Two implants in 2 patients showed peri-implant pathology. CONCLUSIONS: Within the limitations of this study, it is possible to conclude that this treatment modality for completely edentulous jaws is safe and predictable with good long-term outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".