Impact of peri‐implant keratinized mucosa width on the long‐term reconstructive outcomes of peri‐implantitis: A retrospective analysis with a follow‐up up to 10 years
Bibliographic record
Abstract
PURPOSE: To investigate the effect of mid-buccal peri-implant keratinized mucosa width (KMW) ≥2 mm or peri-implant KMW >0 mm and <2 mm on the long-term outcomes of peri-implantitis reconstructive treatment. MATERIALS AND METHODS: Twenty-nine patients (40 implants; mean follow-up: 9.2 ± 1.4 years) with at least one implant affected by peri-implantitis and surgically treated through a reconstructive procedure followed by a submerged healing were included. Patients were categorized according to their initial KMW: Group 1 (KMW ≥2 mm) and Group 2 (KMW >0 mm and <2 mm). Peri-implant clinical and radiographic parameters and a dedicated composite outcome were assessed at different follow-up visits during supportive peri-implant therapy for up to 10 years. Regression analyses were utilized to identify possible risk/predictive indicators for probing pocket depth (PPD) change and treatment success at the latest follow-up. RESULTS: The mean PPD did not exhibit any statistical difference from the baseline to the latest follow-up between the groups at both patient and implant levels. Long-term treatment success was 46.6% (Group 1) and 42.6% (Group 2) at patient level, it was 42.8% (Group 1) and 33.3% (Group 2), respectively, at implant level (p > 0.05). Group 1 demonstrated significantly higher vertical defect depth reduction than Group 2 (p = 0.018). Presence of buccal bony wall and mean PPD at the baseline were found to be associated with mean PPD change, while KMW at 6 months following surgery was identified as the only significant indicator for treatment success (p < 0.05). CONCLUSION: Implants with KMW ≥2 mm did not present significantly better long-term clinical outcomes following reconstructive therapy than those exhibiting KMW >0 mm and <2 mm. However, KMW values at the end of healing phase following a submerged approach had a significant impact on long-term treatment success.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".