Accuracy of navigation guided implant surgery for immediate loading complete arch restorations: Prospective clinical trial
Bibliographic record
Abstract
OBJECTIVES: To assess navigation accuracy for complete-arch implant placement with immediate loading of digitally prefabricated provisional. MATERIALS AND METHODS: Consecutive edentulous and terminal dentition patients requiring at least one complete-arch FDP were treated between December 2020 and January 2022. Accuracy was evaluated by superimposing pre-operative and post-operative cone beam computed tomography (CBCT), recording linear (mm) and angular (degrees) deviations. T-tests were performed to investigate the potential effect of the registration algorithm (fiducial-based vs. fiducial-free), type of references for the fiducial-free algorithm (teeth vs. bone screws), site characteristic (healed vs. post-extractive), implant angulation (axial vs. tilted), type of arch (maxilla vs. mandible) on the accuracy with p-value <0.05. RESULTS: Twenty-five patients, 36 complete-arches, and 161 implants were placed. The overall mean angular deviation was 2.19° (SD 1.26°). The global platform and apex mean deviations were 1.17 mm (SD 0.57 mm), and 1.30 mm (SD 0.62 mm). Meaningful global platform (p = 0.0009) and apical (p = 0.0109) deviations were experienced only between healed and post-extraction sites. None of the analyzed variables significantly influenced angular deviation. Minor single-axis deviations were reported for the type of jaw (y-axis at implant platform and apex), registration algorithm (y-axis platform and z-axis deviations), and type of references for the fiducial-free algorithm. No statistically significant differences were found in relation to implant angulation. CONCLUSIONS: Within the study limitations navigation was reliable for complete-arch implant placement with immediate loading digitally pre-fabricated FDP. AI-driven surface anatomy identification and calibration protocol made fiducial-free registration as accurate as fiducial-based, teeth and bone screws equal as references. Implant site characteristics were the only statistically significant variable with healed sites reporting higher accuracy compared to post-extractive. Live-tracked navigation surgery enhanced operator performance and accuracy regardless of implant angulation and type of jaw. A mean safety room of about 1 mm and 2° should be considered.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".