Radiographic density changes may be associated with overloading and implant loss on short implants: A 5‐year analysis of a randomized controlled clinical trial
Bibliographic record
Abstract
OBJECTIVES: To analyze changes in radiographic bone density around short implants with and without cantilevers at 5 years post-loading. MATERIALS AND METHODS: Thirty-six patients with two adjacent posterior missing teeth participated in this randomized controlled clinical trial. All patients were randomly allocated to receive either two short implants (6 mm) with single-unit restorations (group TWO) or one single short implant (6 mm) with a cantilever restoration (group ONE-C). Patients were followed up at 6 months, 1, 3, and 5 years. Radiographic analysis was performed, through an arbitrary gray scale value (GSV) of the peri-implant bone, assessing the changes in radiographic density between groups and between time points. Differences in GSV between groups and over time were calculated using a generalized estimating equation to allow for adjustments for the correlation within individuals and between time points. RESULTS: At 5 years, 26 patients remained in the study (15 in group ONE-C; 11 in group TWO). Implant survival rates were 80.4% in group TWO and 84.2% in group ONE-C (p = 0.894). The radiographic analysis revealed that GSVs increased in both groups over time (p < 0.001). The overall radiographic density was higher in group ONE-C than in group TWO in the maxilla (p = 0.030). Conversely, in the mandible, these significant differences between the groups were not found (p > 0.05). Compared to the implants that survived, the implants that failed demonstrated a distinct radiographic density pattern (p < 0.05). CONCLUSION: Within the limitations of the present study, the radiographic bone density in the maxilla appears to increase distinctly around short implants when cantilevers are used. In contrast, the radiographic density in the mandible appears to be unaffected by the use of a cantilever, suggesting a lower threshold of adaptation to occlusal forces and thus a higher susceptibility to overload and implant loss at earlier time points.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".