Treatment outcomes of early functional loading of a Toronto prosthesis after placement of postextractive dental implants : a case report
Bibliographic record
Abstract
Aim To report a case of early functional loading of a Toronto prosthesis after the placement of postextractive implants, analyzing aesthetic and functional outcomes; moreover an investigation of the recent literature is performed about the outcomes of immediately loaded Toronto prostheses, in order to provide information about success rates of this treatment and to define remaining questions for future research. Materials and methods A case of immediate functional loading of a Toronto prosthesis after the placement of dental implants is reported. Teeth extractions and dental implants positioning were performed at the same time. The prosthetic procedures with dental implants loading have been completed after 24 hours. Results The 18 months follow up radiograph showed no bone loss around the implants and the patient was satisfied with both the aesthetic and functional conditions. Clinical trials show that the respective overall implant survival and success rates are influenced by implant design, surface characteristic, bone properties, implant area placement (upper or lower jaw) and postextraction conditions. Before early loading of dental implants for Toronto prostheses all these parameters have to be considered. Conclusion This case report and the literature review confirm that the influence of timing of loading on implant survival is rather debated. There are not yet clinical guidelines in order to obtain predictable results, though factors such as bone quality and post-extraction conditions should be analyzed before treatment. Future researches should analyze how immediate loading can influence the implant rehabilitation success.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".