Alveolar ridge preservation and its impact on marginal bone level changes around dental implants: A retrospective, cohort comparative study
Bibliographic record
Abstract
OBJECTIVES: This retrospective study compared the outcomes of implants placed in alveolar ridge preservation (ARP) treated sites with those in spontaneously healed (SH) sites. MATERIALS AND METHODS: The study included patients presenting with one implant placed in an ARP-treated socket and one in an SH site. The primary outcome was the comparison of Marginal Bone Level Changes (MBLC). Statistical analysis was performed to identify factors influencing MBLC, including age, gender, smoking, parafunctional habits, and prosthetic emergence angle. RESULTS: Of these, 28 patients (23 females, 82.1%) were included in this analysis. Sockets in the SH group were classified as type I, whereas type II sockets were more common in the ARP group. The SH group exhibited significantly higher MBLC than the ARP group (p = 0.032), with values, respectively, of 1.00 [0.25; 1.62] and 0.40 [0.00; 1.00] mm. Among all evaluated parameters, the performance of ARP was the only factor significantly affecting MBLC (β = -0.72, SE: 0.32, p = 0.026). Age, gender, smoking, parafunctional habits, and prosthetic emergence angle did not significantly affect MBLC. CONCLUSIONS: The study shows the potential role of ARP in maintaining stable marginal bone levels around implants. In our sample, ARP significantly reduced MBLC compared with spontaneous healing, highlighting its possible impact in clinical practice for better peri-implant bone stability.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".