Histological evaluations and inflammatory responses of different dental implant abutment materials: A human histology pilot study
Bibliographic record
Abstract
BACKGROUND: Improvements of soft tissue to the abutment surface results in more stable peri-implant conditions, however, few human histological studies have compared soft tissue responses around different abutment materials. PURPOSE: To describe the peri-implant tissue around 3 abutment materials; titanium, zirconia, and gold alloy, over an 8-week healing period. MATERIALS AND METHODS: Fifteen edentulous sites were treated with implants. Eight weeks later, peri-implant tissue was harvested and processed using a nonseparation resin embedded technique. The tissue attachment characteristics were assessed at clinical stages using the gingival index (GI) score, surgical stage (surgical score), and histological stage (histological attachment percentage). Additionally, the inflammatory responses were evaluated using inflammatory extent and inflammatory cellularity grades. Nonparametrical statistics were used to describe the GI and surgical scores, and analytical statistics were used to analyze the histological attachment percentages as well as the inflammatory extent and cellularity grades amongst the 3 groups. RESULTS: There were no statistically significant differences among the groups for GI score (P = .071) and surgical score (P = .262). Titanium and zirconia exhibited nearly similar mean histological attachment percentages while gold alloy had a significantly lower percentage (P = .004). For the inflammatory extent and cellularity grades, the odds of being one grade higher for gold alloy abutment was 5.18 and 17.8 times that of titanium abutment, respectively. However, for the zirconia abutment, the odds were 0.87 and 7.5 times higher than the titanium group. CONCLUSIONS: The tissue around the gold alloy abutments resulted in worse attachment conditions compared with the titanium and zirconia abutments. Inflammation tended to be higher in the tissue around the gold alloy abutments than the titanium and zirconia abutments.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".