An Up to 12‐Year Retrospective Follow‐Up on Immediately Loaded, Surface‐Modified Implants in the Edentulous Mandible
Bibliographic record
Abstract
PURPOSE: The study aims to evaluate the long-term clinical outcome of immediate loading of implants in the edentulous mandible. MATERIALS AND METHODS: Patients were treated at least 1 year prior to evaluation, with four to five implants and an immediate provisional bridge in the edentulous mandible. They were invited for a clinical examination, which included the removal of the bridge, probing, perio-testing, clinical photographs, and a new radiograph to determine the bone level. Also, patients were requested to answer the OHIP-14 questionnaire to rate their satisfaction with the treatment. RESULTS: Forty-six patients (21 men, 25 women), mean age 60 years (SD 8.5, range 43-77), were treated with 211 implants. One implant failed to integrate, resulting in a survival rate of 99.5%. After a mean follow-up of 90 months (SD 45, range 17-143), the mean bone level was 1.17 mm (SD 0.49, range 0.36-4.88). The mean Periotest value was -5.48 (SD 0.883, range -2 to -7). The mean probing depth was 2.04 mm (SD 0.71, range 1.00-8.25). There were 83.3% of the implants that demonstrated no bleeding at probing. Calculus was observed at 13.9% of the abutments. Around one implant (0.5%), suppuration was seen after probing. There was a highly significant correlation between bone loss and probing depth (p < .001). Overall, patients were very satisfied, with 69.6% scoring their treatment as excellent. CONCLUSION: Immediate loading of surface-enhanced implants is a highly predictable and successful treatment modality in the edentulous mandible.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".