Clinical and radiographic evaluation of implant‐supported single‐unit crowns with cantilever extension in posterior areas: A retrospective study with a follow‐up of at least 10 years
Bibliographic record
Abstract
BACKGROUND: Implant-supported restorations with cantilever extension may display high rates of biological and technical complications. PURPOSE: To report the outcomes of single-unit crowns with cantilever extension (SCCs). MATERIALS AND METHODS: Patients with SCCs were reevaluated after ≥10 years of loading. Radiographic marginal bone levels (mBLs) at baseline (ie, delivery of SCCs) and follow-up were calculated and compared between implant surfaces adjacent to and distant from the cantilever extension. Implant survival and success rates were calculated. RESULTS: Twenty-one patients with 25 SCs supported by 25 implants were reevaluated after a mean of 13.6 ± 3.8 years (range: 10-19 years). No implants were lost. The mean overall mBLs changed from 0.99 mm ± 0.95 at baseline to 0.95 mm ± 0.99 at follow-up (p = 0.853). The mean pocket probing depths changed from 3.39 mm ± 0.62 at baseline to 3.34 mm ± 0.54 at follow-up (p = 0.635). Loss of retention occurred 3× in 2 patients (14.3%). At follow-up, peri-implant health was diagnosed in 10 (48%) and peri-implant mucositis in 11 (52%) patients, respectively. CONCLUSIONS: Within the limitations of the present study, the use of implant-supported SCs with cantilever extension in posterior areas represents a reliable long-term treatment option with a 100% implant survival rate and minimal marginal bone level changes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".