Stock Versus CAD/CAM Customized Zirconia Implant Abutments – Clinical and Patient‐Based Outcomes in a Randomized Controlled Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Single-tooth replacement often requires a prefabricated dental implant and a customized crown. The benefits of individualization of the abutment remain unclear. PURPOSE: This randomized controlled clinical trial aims to study potential benefits of individualization of zirconia implant abutments with respect to preservation of marginal bone level and several clinical and patient-based outcome measures. MATERIAL AND METHODS: Fifty participants with a missing premolar were included and randomly assigned to standard (ZirDesign, DentsplySirona Implants, Mölndal, Sweden) or computer aided design/computer aided manufacturing (CAD/CAM) customized (Atlantis, DentsplySirona Implants, Mölndal, Sweden) zirconia abutment therapy. Peri-implant bone level (primary outcome), Plaque-index, calculus formation, bleeding on probing, gingiva index, probing pocket depth, recession, appearance of soft tissues and patients' contentment were assessed shortly after placement and one year later. RESULTS: No implants were lost and no complications related to the abutments were observed. Statistically significant differences between stock and CAD/CAM customized zirconia abutments could not be demonstrated for any of the operationalized variables. CONCLUSION: The use of a CAD/CAM customized zirconia abutment in single tooth replacement of a premolar is not associated with an improvement in clinical performance or patients' contentment when compared to the use of a stock zirconia abutment.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".