Influence of titanium-base and universal abutment heights on the adaptation and fracture of screw-and-cemented-retained lithium disilicate crowns
Bibliographic record
Abstract
PURPOSE: This in vitro study evaluated the adaptation and fracture resistance of screw- and cement-retained implant-supported restorations using lithium disilicate crowns cemented onto titanium bases and universal abutments of different heights. METHODS: Thirty crowns were designed, milled, and divided into three groups: TBA (titanium base abutment - 4.7-mm-height and 4.65-mm-diameter), UA-4 (universal abutment - 4.0-mm-height and 4.5-mm-diameter), and UA-6 (universal abutment - 6.0-mm-height and 4.5-mm-diameter) (n=10). The abutments were placed in a mandibular first premolar model, torqued to 20 Ncm, and scanned using a digital intraoral scanner. The crowns were designed and fabricated using computer-aided design/computer-aided manufacturing technology. Adaptation was assessed using a stereomicroscope before and after ceramic sintering and after cementation with RelyX Ultimate resin cement. Fracture resistance was evaluated using a universal testing machine, and the failure modes were analyzed. The collected data were subjected to statistical analysis using one-way ANOVA and the Tukey least significant difference test (α=0.05). RESULTS: The abutment type influenced restoration adaptation and fracture resistance. No differences in adaptation were found before or after luting (P > 0.05). However, after sintering, the TBA group exhibited smaller marginal gaps than the UA-4 (P = 0.0339) and UA-6 (P = 0.0006) groups. TBA showed a higher fracture resistance than UA-4 (P = 0.0093); no differences were observed between TBA and UA-6 or between UA-4 and UA-6 (P > 0.05). The UA-4 and UA-6 groups showed higher ceramic fracture rates, whereas the TBA group showed increased abutment deformation and ceramic fractures. CONCLUSIONS: The type and height of abutments influenced the fracture of screw-and-cement-retained implant-supported restorations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".