Immediate Loading of Fixed Complete Denture Prosthesis Supported by 4–8 Implants Placed Using Guided Surgery: A 5‐Year Prospective Study on 66 Patients with 356 Implants
Bibliographic record
Abstract
BACKGROUND: High primary implant stability is considered one of the main factors necessary for achieving predictable treatment outcomes with immediately loaded implant-supported screw-retained fixed complete denture prosthesis (FCDP). PURPOSE: To evaluate the 5-year clinical and radiographic outcomes of immediately loaded implants placed in edentulous patients using computer-assisted template-guided surgery to support a FCDP. MATERIALS & METHODS: Patients in need to be restored with a FCDP in the mandible or maxilla were included in this prospective study/ and treated using computer-assisted template-guided surgery. Implant sites were prepared in order to achieve an insertion torque ranging between 35-45 Ncm in the mandible and 45-55 Ncm in the maxilla. A prefabricated screw-retained provisional prosthesis was delivered the day of the surgery. Outcomes were: implant and prosthesis cumulative survival rate (CSR), any complications, and peri-implant marginal bone loss (MBL). RESULTS: Sixty-six patients received 356 implants to support 68 FCDPs. Each patient received 4-8 implants. Seven implants failed in six patients, resulting in a CSR of 98.1%. Two definitive prostheses failed resulting in CSR of 97.1%. Mean MBL of 1.62 ± 0.41 mm was reported at the 5-year follow-up. Five implants (1.4%) showed a mean mesio-distal peri-implant bone loss greater than 3.0 mm and received nonsurgical therapy. CONCLUSIONS: immediately loaded implants placed in edentulous patients using computer-assisted template-guided surgery to support a FCDP is a valid treatment concept in the medium term follow-up, for edentulous patients.
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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 | 0.001 |
| 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".