The application of a newly designed L‐shaped titanium mesh for GBR with simultaneous implant placement in the esthetic zone: A retrospective case series study
Bibliographic record
Abstract
BACKGROUND: To our acknowledgment, there were limited clinical studies about the guided bone regeneration (GBR) for both vertical and horizontal augmentation at the same time using titanium mesh (Ti-mesh) with simultaneous implant placement in the esthetic zone. Meanwhile, studies that specially evaluate resorption and long-term stability of the augmented labial bone after loading were also rare. Therefore, this study introduced a newly designed L-shaped Ti-mesh used for GBR with simultaneous implant placement and evaluated the bone augmentation effectiveness, resorption, and long-term stability of peri-implant bone with this newly designed L-shaped Ti-mesh. MATERIALS AND METHODS: Twelve patients (16 implants) who had underwent a GBR procedure using L-shaped Ti-mesh with simultaneous implants placement were reviewed in this study. Complications, implant success, and survival rate were recorded and calculated. Furthermore, the bone gain values, labial bone resorption, and remaining labial bone volume were measured by cone beam CT (CBCT) during 13-41 months follow-up. RESULTS: After GBR using L-shaped Ti-mesh, the average bone gain values were 3.61 ± 1.50 mm vertically and 3.10 ± 2.06 mm horizontally. The implant success and surviving rate were 93.75% and 100%, respectively during the longest 41 months follow-up. The vertical labial bone resorption was -0.81 ± 1.00 mm, horizontal labial bone resorption was -0.13 ± 1.19 mm at the top of the implants. The remaining labial bone thickness was 2.24 ± 1.29 mm at the top of the implants and 2.86 ± 1.08 mm at the 2 mm apically from the implant tops after loading. There was still 1.13 ± 1.18 mm vertical labial bone remaining above the top of implants for approximately 87.5% sites. CONCLUSIONS: GBR using L-shaped Ti-mesh with simultaneous implant placement (one-step surgery) in the esthetic zone could achieve predictable results for vertical and horizontal bone augmentation at the same time. Meanwhile, L-shaped Ti-mesh could preferably reconstruct and reduce the labial bone resorption to achieve long-term esthetics. This newly designed L-shaped Ti-mesh may offer predictable and excellent outcomes for the implant restoration in the esthetic zone.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".