CAD/CAM implant crowns in a digital workflow: Five‐year follow‐up of a prospective clinical trial
Bibliographic record
Abstract
BACKGROUND: Implant restorations became the first choice for single-tooth replacement today. PURPOSE: The prospective clinical trial aims to investigate computer-aided-design (CAD)/computer-aided-manufacturing (CAM)-processed implant crowns after 5 years of loading. MATERIALS AND METHODS: Twenty patients were included for cement-retained crowns in posterior sites. Radiographic analysis of bone levels was performed after delivery and follow-up. The Functional Implant Prosthodontic Score (FIPS) was assessed at the final follow-up. Wilcoxon signed-rank tests were used with a level of significance set at α = 0.05. RESULTS: One implant was lost, resulting in a success rate of 95% at 5 years. For 19 crowns, neither technical complications nor biological complications were observed. The mean marginal bone level was 0.6 ± 0.26 mm (range: 0.18-1.12) mesially, and 0.79 ± 0.36 mm (range: 0.23-1.36) distally at 5 years. During the observation period, mean radiographic bone levels increased significantly by 0.23 mm at mesial and by 0.17 mm at distal sites (P < .0001) indicating minor additional bone loss. The mean total FIPS score was 8.2 ± 1.0 (range: 7-10) with the high score of 2.0 ± 0.0 for the variable "bone." CONCLUSIONS: CAD/CAM-processed implant crowns demonstrated promising radiographic and clinical outcomes after 5 years in function. Future large-scale trials are crucial to confirm these initial results in the field of digital implant processing.
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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 | 0.016 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".