Porcine‐Derived Xenograft Combined with a Soft Cortical Membrane versus Extraction Alone for Implant Site Development: A Clinical Study in Humans
Bibliographic record
Abstract
BACKGROUND: An adequate alveolar crest is essential for implant placement in terms of esthetics and function. The objective of this randomized clinical trial was to compare the preservation of the alveolar ridge dimensions following tooth extraction using porcine-derived xenograft combined with a membrane versus extraction-alone (EXT) sites. METHODS: Fifteen patients who required double extraction of contralateral premolars and delayed implant placement were randomly selected to receive both ridge-preservation procedure and EXT. The test sites (alveolar ridge preservation [ARP]) included 15 sockets treated using a corticocancellous porcine bone xenograft (OsteoBiol® Gen-Os; Tecnoss srl, Giaveno, Italy) associated with a soft cortical membrane (OsteoBiol® Lamina; Tecnoss srl), while the corresponding control sites (EXT) were left without grafting for EXT. Horizontal and vertical ridge dimensions were recorded at baseline and 6 months after extractions. RESULTS: After 6 months, the EXT sites showed a significantly greater reabsorption of the buccolingual/palatal dimension of the alveolar ridge (3.7 ± 1.2 mm) compared with the ARP sites (1.8 ± 1.3 mm). The mean vertical ridge height reduction in the control sockets was 3.1 ± 1.3 mm at the buccal sites and 2.4 ± 1.6 mm at the lingual sites compared with 0.6 ± 1.4 and 0.5 ± 1.3 mm, respectively, in the test sockets. The differences between test and control sockets were not significant for the mesial and distal measurements. CONCLUSIONS: The placement of a porcine xenograft with a membrane in an extraction socket can be used to reduce the hard tissue reabsorption after tooth extraction compared with EXT.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".