Immediate implant placement and provisionalization: Aesthetic outcome 1 year after implant placement. A prospective clinical multicenter study
Bibliographic record
Abstract
BACKGROUND: Prospective aesthetic outcomes on a high number of patients after immediate implant placement and provisionalization (IIPP) are lacking. PURPOSE: To analyze the aesthetic outcome after IIPP. MATERIALS AND METHODS: One hundred consecutive patients with a failing maxillary incisor were provided with an immediately placed and provisionalized nonloaded implant using a flapless procedure and palatal implant positioning. The remaining gap buccally was filled with a bone substitute. Preoperatively (T0), 2 weeks postoperatively (T1), direct after placement of the permanent crown (T2), and 1 year after IIPP (T3), standardized light photographs were made. Change in aesthetic score was the primary outcome measure. Both the white aesthetic score (WES) and pink aesthetic score (PES) were used. RESULTS: In the first year postsurgery, the mean total-WES and total-PES scores raised from 4.5 to 8.2, and from 9.9 to 12.1, respectively. The mean PES scores for mesial and distal papilla, soft tissue marginal level, contour, color, and texture, raised significantly (P < .05), while the alveolar process contour, on average, remained stable from T0 to T3. CONCLUSIONS: Within the limitations of this 1-year research, it may be concluded that, following this minimal invasive IIPP procedure, a high aesthetic outcome was achieved.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".