Ridge augmentation using autologous concentrated growth factors enriched bone graft matrix versus guided bone regeneration using native collagen membrane in horizontally deficient maxilla: A randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Facial resorption of maxillary alveolar ridges is a challenging situation for implant rehabilitation, which mandates a preparatory surgery of bone augmentation. Guided bone regeneration using a 1:1 mixture of autogenous particulate and anorganic bovine bone mineral (ABBM) showed reliable outcomes in treating horizontally deficient ridges. METHODS: Twenty-eight patients were randomly assigned into two groups; in the control group, the 1:1 mixture of particulate autogenous bone and ABBM was covered with native collagen membrane, while in the study group, it was mixed with autologous fibrin glue (AFG) to make a sticky bone that was covered by concentrated growth factor (CGF) membrane. For each proposed implant site, the average bone width gain was calculated preoperatively, immediately after augmentation and after 6 months. Implants were placed after 6 months and the implant stability quotient (ISQ) was measured after insertion and after 6 more months. RESULTS: The graft consolidation period went uneventful in both groups; however, two cases in the sticky bone group showed total resorption of the graft upon re-entry. The mean horizontal bone width after 6 months was 9 mm ± 0.71 in the guided bone regeneration (GBR) group which was higher than 7.9 mm ± 0.92 for the sticky bone group. The mean primary stability was higher in the GBR group; 67.19 ± 2.23 compared to 66.7 ± 3.22 for the sticky bone group, while the mean secondary stability was higher in the sticky bone group; 72 ± 2.15 compared to 71.7 ± 2.27 for the GBR group. Results of Shapiro-Wilk's for bone width data and model residuals were both statistically not significant (p > 0.05). CONCLUSION: Comparing CGF membrane versus native collagen membrane as barriers for GBR showed no statistically significant difference regarding bone gain. However, from a clinical point of view, CGF membrane is not a predictable barrier for guided bone regeneration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| 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) | 0.005 | 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".