Does Timing of Implant Placement Affect Implant Therapy Outcome in the Aesthetic Zone? A Clinical, Radiological, Aesthetic, and Patient‐Based Evaluation
Bibliographic record
Abstract
PURPOSE: To compare five different implant treatment protocols in the anterior maxilla, including immediate, early, and delayed implant placement, as well as implant placement in conjunction with simultaneous guided bone regeneration and implant placement 3 months following horizontal autologous bone block grafting. MATERIAL AND METHODS: Aesthetic indices used included the Pink Esthetic Score (PES), Papilla Index (PI), Subjective Esthetic Score (SES), and White Esthetic Score (WES). Subjective evaluation of implant aesthetics was performed using a visual analogue scale (VAS). The VAS consisted of a 10 cm-long line representing the degree of discontent (0%) or satisfaction (100%). RESULTS: A total of 153 implants in 153 patients (80 women, 73 men) were evaluated after a mean follow-up of 4.5 ± 2.9 years. Mean peri-implant bone loss was 1.6 ± 0.9 mm and not affected by treatment protocol, time after implant placement, or crown length. Papilla presence, by contrast, differed significantly between the protocols: Papilla formation was more pronounced following delayed and immediate implant placement. No statistical significance was found among treatment modalities with regard to PES, SES, or WES. Longer crowns were associated with lower PES and PI ratings and correlated with greater midfacial recession. SES was also influenced by time after implant placement and keratinized mucosa. Patient satisfaction differed significantly among treatment protocols, favoring immediate implant placement. Agreement between objective and subjective aesthetic ratings was low. CONCLUSION: The present study suggests that comparable clinical, radiological, and aesthetic results can be achieved with all treatment protocols. Gingival recession, however, seems to occur in the long term irrespective of the technique used.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".