Esthetic evaluation of single implant restorations, adjacent single implant restorations, and implant‐supported fixed partial dentures: A 1‐year prospective study
Bibliographic record
Abstract
BACKGROUND: Peri-implant soft tissues esthetics varies and depends on the restoration type such as implant-supported single crowns, adjacent multiple single crowns, and fixed partial dentures (FPD). PURPOSE: The aim of this prospective study was to assess the esthetic outcome of the peri-implant soft tissues of (NobelBiocare™) implant-supported single crowns, adjacent multiple single crowns, and FPD. A potential association between the esthetic risk profile and the esthetic outcome was assessed. MATERIALS AND METHODS: Between 03/11 and 03/17, 300 NobelActive implants were installed in 153 partially edentulous patients. Prior to the fabrication of the final restoration, the esthetic risk profile (ERP) of the patient was determined. The pink esthetic score (PES) and white esthetic score (WES) were assessed by three investigators at 6 and 12 months post-insertion of the final restoration. Patients' appreciation was assessed on a visual analogue scale (VAS) at the 1-year follow-up. RESULTS: The clinical acceptable limit for PES (≥6) was achieved in 56% to 68% of the single crowns at 6 and 12 months, respectively. Clinically unacceptable PES scores were recorded for 48% of the adjacent multiple single crowns and 63% of the FPDs at both time points. The association of a high ERP with WES and PESWES was noticed for single implant-supported crowns. For the latter restoration type, a ≤5 mm distance between the crestal bone level and the proximal contact positively influenced the PES and combined PESWES scores. No correlation was found between PES or WES and patient satisfaction. Mesial papilla formation was more pronounced compared to the distal one for the single implant crowns and for implant-supported FPD. CONCLUSION: When high esthetic demands are expected, assessment of ERP prior to implant treatment is advised in order to estimate a realistic outcome.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".