Cortico‐Cancellous Collagenic Porcine Bone for Alveolar Ridge Preservation: A Cohort Comparative Study
Bibliographic record
Abstract
OBJECTIVES: The primary aim of this study was to compare the histomorphometric characteristics of two different cortico-cancellous collagenic porcine bone (CCPB) formulations combined with a stabilizing agent used for alveolar ridge preservation (ARP), and the secondary aim was to evaluate and compare clinical and aesthetic outcomes of dental implants placed in augmented sites. MATERIALS AND METHODS: This was a prospective, cohort-comparative study conducted on patients requiring a tooth extraction followed by ARP and subsequent implant placement. Tooth extractions were performed trying to reduce the surgical trauma as much as possible, and then ARP was performed using two different formulations of CCPB combined with a thermogel in different ratios (50:50 hand-mixed and 80:20 pre-mixed). After 4 months of healing, implant placement was performed, and a bone biopsy was retrieved from the surgical site for histomorphometric analyses. Implants were rehabilitated 3 months following placement with screw-retained crowns, then patients were re-evaluated 1 year following prosthetic loading. RESULTS: We report the clinical and histomorphometric outcomes of 20 patients divided into the two study groups (10 patients per group). ARP performed with a hand-mixed biomaterial in a 50:50 ratio had higher percentages of newly formed bone (36.15% vs. 27.18%) when compared to a pre-mixed biomaterial in an 80:20 ratio, even though the difference was not statistically significant (p = 0.064). Implants placed in ARP-treated sites showed a very low mean marginal bone loss at the 1-year follow-up in both experimental groups (0.06 ± 0.15 mm in the 50:50 group and 0.25 ± 0.35 mm in the 80:20 group) with no statistically significant differences (p = 0.42), as well as the aesthetic outcomes assessed through the pink aesthetic score. CONCLUSIONS: Both biomaterials showed effective and favorable outcomes, and the histomorphometric differences observed in our sample did not have any impact on the final clinical and aesthetic outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".