Two Stage Sinus Lifting Using Nanohydroxyapatite Particles Versus Deproteinized Bovine Bone: Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Sinus floor elevation is one of the predictable techniques for augmentation of vertically deficient posterior maxillary alveolar ridges. Several biomaterials were reported to be successful for sinus augmentation, including xenografts and hydroxyapatite. The aim of this study was to compare the quality and quantity of generated bone using xenografts versus nanohydroxyapatite in sinus augmentation. METHODOLOGY: Twenty-four patients/sinuses were randomly assigned into two groups; in the control group, patients underwent sinus floor elevation and augmentation using deproteinized bovine bone (DBB), whereas in the study group, the sinus was augmented using nanohydroxy-apatite bone (NHA). For each patient, the amount of bone height was assessed preoperatively, immediately postoperatively, and 6 months postoperatively. Furthermore, the quality of the newly formed bone was assessed via histological and histomorphometric analyses after 6 months postoperatively. RESULTS: Both biomaterials showed a good level of consolidation. In the study group, the mean bone height after 6 months was 11.72 ± 1.24 compared to 12.01 ± 1.16 mm in the control group which was not statistically significant (p > 0.05). The mean bone area percent of newly formed bone was 29.84% ± 6.7% for NHA group and 34.73 ± 7.9 for DBB group. Moreover, the mean percent of residual grafting material was 32.43% ± 11.53% for NHA group compared to 30.43% ± 8.27% for DBB group. Histologically, there was no significant difference between both groups regarding different parameters (p > 0.05). CONCLUSION: The two-stage sinus floor augmentation using NHA and DBB revealed no statistically significant difference regarding both the quality and the quantity of the regenerated bone. Studies with larger samples and longer follow up are recommended. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03184857.
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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 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".