Effect of alveolar ridge preservation on clinical attachment level at adjacent teeth: A randomized clinical trial
Bibliographic record
Abstract
PURPOSE: To test whether or not alveolar ridge preservation (ARP) changes the clinical attachment level (CAL) at adjacent teeth of extraction sockets after 6 months. MATERIAL AND METHODS: Seventeen patients requiring bilateral tooth extractions of the upper molars were recruited. After tooth extraction, the sockets were randomly allocated to two groups applying a split-mouth design: (1) ARP using deproteinized bovine bone mineral containing 10% collagen (DBBM-C) covered by a collagen membrane and (2) spontaneous healing (control). CAL, probing pocket depth (PD), bleeding on probing (BOP), gingival recession (REC), and bone levels were evaluated at the adjacent teeth of the extraction sockets at baseline and after 6 months of follow-up. RESULTS: A total of 14 patients were available for reexamination. From baseline to 6 months of follow-up mean CAL changes of all six sites at adjacent teeth of the extraction sockets amounted to -0.23 ± 0.65 mm (gain) in ARP group and 0.05 ± 0.86 mm (loss) in the control group with significant differences in favor of ARP (p = 0.04). The CAL gain was significantly more favorable at mesiopalatal sites (p = 0.01). Consistently, the mean reduction of PD of all six sites amounted to -0.68 ± 0.84 mm in ARP and -0.34 ± 0.74 mm in the control group (intergroup p = 0.02). The PD reduction was significant (p = 0.001) at the mesiopalatal sites in ARP. BOP, REC, and bone levels showed no significant differences between the groups (intergroup p > 0.05). CONCLUSION: Although ARP with DBBM-C revealed a trend toward CAL gain and PD reduction at adjacent teeth of extraction sites, these adjunctive benefits seem to be clinically negligible.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".