Keratinized mucosa changes around one‐stage implants: A prospective case series
Bibliographic record
Abstract
BACKGROUND: The need of an adequate band of keratinized tissue (KT) to maintain periodontal health around teeth as well as around implants has been a debated topic over many years but still no conclusions have been drawn. OBJECTIVES: This prospective case series evaluates the changes undergone by the keratinized mucosa (KM) and the soft tissue volume around non-submerged implants before the prosthetic rehabilitation. MATERIAL AND METHODS: A total of 40 patients were included. The primary outcome was to analyze the width of the KM at both buccal and lingual aspects compared to the pre-existing KT in the edentulous ridge only in mandibular (pre)molar area. The mucogingival line was marked with a surgical pen and an intra-oral scanner was used to take the impression of the implant area the day of the surgery (T0, baseline) and before the crown placement (T1, 3 months). Buccal soft tissue volume was measured at 1, 3, and 5 mm apical to the healing abutment position and a comparison between T0 and T1 was performed. Student t-test was used according to the distribution of the data (Shapiro-Wilk). RESULTS: The mean KT width at baseline was 4.54 ± 1.31 mm at buccal side and 5.04 ± 1.88 mm at lingual side. After 3 months, the mean KM values were 3.15 ± 1.03 mm and 3.72 ± 1.56 mm at the buccal and lingual aspects, respectively. The differences, 30.6% of KM reduction buccally and 26.1% of reduction lingually, were statistically significant for both sides. CONCLUSIONS: Within the limitations of this investigation, it was observed that the KM width from the baseline to the 3 months follow up presented a significant dimensional change in both the buccal and lingual aspects, whereas buccal soft tissue volume showed an increase between baseline and follow up.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".