A prospective case series on the efficacy of a cross‐linked collagen matrix to increase buccal soft tissue thickness at large edentulous gaps: One‐year results
Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to assess profilometric changes following soft tissue augmentation with a cross-linked porcine-derived collagen matrix (CMX) at large edentulous gaps of at least two units. MATERIALS AND METHODS: Systemically healthy, nonsmoking patients with a large edentulous gap of at least two units demonstrating a horizontal soft tissue defect, were enrolled in a prospective case series. Soft tissue augmentation was performed in a one-stage approach with a 6 mm thick CMX at the time of implant placement. The primary outcome was the change in buccal soft tissue profile (BSP) at a mesial, central, and distal area of interest (AOI) up to 1 year when compared to the preoperative situation based on superimposed digital surface models. Secondary outcomes included the horizontal dimension of the soft tissue defect, complications, and marginal bone loss (MBL). RESULTS: Fifteen patients (eight females; mean age 58.73 years) were enrolled and 13 could be re-assessed at 1-year follow-up. The mean linear increase in BSP at 1 year was 0.66 mm (98.3% CI: 0.37-0.94), 0.80 mm (98.3% CI: 0.39-1.22), and 0.69 mm (98.3% CI: 0.32-1.06) at the mesial, central, and distal AOI, respectively. Substantial shrinkage of about 75% was observed in all areas between augmentation and 1-year follow-up. Even though 11 of 13 sites were fully augmented immediately postoperative, a soft tissue defect recurred in all sites at 1-year follow-up with a mean deficit of 2.30 mm. Altogether, 25% of the original soft tissue defect was eliminated by soft tissue augmentation. CMX was safe since no postoperative complications occurred and MBL was limited (0.70 mm). CONCLUSION: CMX is efficacious for horizontal soft tissue augmentation at large edentulous gaps. However, considerable graft resorption may be expected, and the clinical relevance of the augmentation may be questionable since all patients demonstrated a recurring and considerable soft tissue defect 1 year after 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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".