Radiographic evaluation of the tenting screw technique in horizontal alveolar bone augmentation: A retrospective study
Bibliographic record
Abstract
Abstract Objectives To radiographically analyze the effects of tenting screw technique (TS) and onlay bone grafts (OG) in horizontal bone augmentation. Materials and Methods Patients receiving horizontal bone augmentation by TS or OG were selected. The clinical outcomes and cone beam computed tomography (CBCT) data were documented pre‐grafting, immediately post‐grafting, before and after implantation. The survival rates, clinical complications, alveolar bone width, and volumetric bone augmentation were evaluated and statistically analyzed. Results A total of 25 patients and 41 implants were involved in this study, with no grafting failures observed in either the TS group ( n = 20) or the onlay group ( n = 21). Volumetric bone resorption rate in the TS group (21.34%) was significantly lower than that of the OG group (29.38%). In addition, significant horizontal bone gain was achieved in both groups (TS: 6.15 ± 2.12 mm; OG: 4.86 ± 1.40 mm) during the recovery period, with higher gain in the TS group. No apparent statistical difference in terms of volumetric bone gain was observed between the TS (748.53 mm 3 , 607.47 mm 3 ) and OG group (811.77 mm 3 , 508.49 mm 3 ) immediately post‐grafting or after the recovery period. Conclusion Both TS and OG achieved satisfactory bone augmentation effects, yet TS resulted in more bone augmentation and better stability than OG, with a reduced use of autogenous bone. Overall, the tenting screw technique can serve as an effective alternative to autogenous bone grafts.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".