Single‐Tooth Implants with Different Neck Designs: A Randomized Clinical Trial Evaluating the Aesthetic Outcome
Bibliographic record
Abstract
AIM: To evaluate the aesthetic outcome of single-tooth implants in the aesthetic zone with different neck designs from a professional's and patient's perception. MATERIALS AND METHODS: Ninety-three patients with a missing anterior tooth in the maxilla were randomly assigned to be treated with an implant with a smooth neck, a rough neck with grooves or a scalloped rough neck with grooves. Implants were installed in healed sites. One year after definitive crown placement (18 months post-implant placement), photographs were taken and the aesthetic outcome was assessed according to two objective aesthetic indexes: pink esthetic score/white esthetic score (PES/WES) and implant crown aesthetic index (ICAI). A questionnaire was used to assess the aesthetic outcome and general satisfaction from a patient's perception. standardized radiographs were taken to measure marginal bone level changes. RESULTS: One implant was lost. Although there was a significant difference in marginal bone loss between the different implant neck designs (smooth neck 1.19±0.82mm, rough neck 0.90±0.57mm, scalloped neck 2.01±0.77mm), there were no differences in aesthetic outcome. According to the professional's assessments using PES/WES and ICAI, 79.3% and 62% of the cases showed acceptable crown aesthetics, and 59.8% and 56.5% of the cases showed acceptable mucosa aesthetics. Overall, patients were satisfied about the aesthetics of the mucosa (81.5%) and crown (93.3%), and general patient satisfaction was high (9.0±1.0 out of a maximum of 10). According to the professional's assessment, a pre-implant augmentation procedure was associated with less favorable aesthetics of the mucosa. CONCLUSION: This study shows that the aesthetics of single-tooth implants in the maxillary aesthetic zone appears to be independent of the implant neck designs applied but dependent on the need for pre-implant surgery.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.007 | 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".