Impact Fracture Resistance of Two Titanium‐Abutment Systems Versus a Single‐Piece Ceramic Implant
Bibliographic record
Abstract
BACKGROUND: The number of patients with oral implants has increased significantly. However, the literature addressing the effect of impact force on titanium and/or ceramic implants is inconclusive. This study sought to determine the fracture resistance to impact load of titanium and ceramic endosseous oral implants. MATERIALS AND METHODS: Endosseous oral implants were vertically positioned in two different mounting media: brass and a bone-simulation material. The implant configurations tested included an experimental one-piece Y-TZP implant and a commercially available titanium implant (external hex) with both titanium and zirconia abutments. The specimens were subjected to an impact load using a pendulum impact tester with tup weights varying from 0.9 to 4.5 kg delivered at a radius of 40.64 mm. Loads were delivered to the abutment at a point 4.27 mm above the implant fixture and block junction. Statistical differences (p < .05) were established using the F-test for variances and, when different, t-test assuming unequal variances. RESULTS: For implants clamped in brass, the titanium implant with titanium abutment required the greatest energy to fracture the implant-abutment system (only the abutment screw failed). The ceramic implant and ceramic abutment on titanium implant presented the lowest fracture energy (p < .01). No significant differences were observed when different systems were inserted into the foam blocks of the bone substitute (p > .25). CONCLUSION: This investigation showed that the fracture energy of two titanium-abutment systems versus a single-piece Y-TZP implant in foam blocks simulating bone elastic modulus was not different, and that differences occurred when the embedding material elastic modulus was increased an order of magnitude.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".