Evaluation of the effect of the lateralized inferior alveolar nerve isolation and bone grafting on the nerve function and implant stability. (Randomized Clinical Trial)
Bibliographic record
Abstract
BACKGROUND: The inferior alveolar nerve lateralization (IANL), although allows for an implant full-length mandibular height engagement, coincides with depleting the buccal bone support and sensory deficits. PURPOSE: This study aims to assess whether interposing a bone graft coupled with securing a collagen membrane separation between the inferior alveolar nerve (IAN) and the underlying dental implants would preserve the nerve function, enhance the implant stability, and minimize the radiographic marginal bone loss. MATERIAL AND METHODS: Eighteen patients with 30 atrophic mandibular edentulous ridges were subjected to IANL after being randomly assigned to two treatment modalities which consisted of 15 patients each. The (control group) utilized conventional IANL in direct contact with 20 implants. The (test group) implemented the IAN collagen-membrane wrapping and interposing bone graft to overlay 23 implants. The neural function, the radiographic marginal bone loss, and the implant stability quotient were assessed and compared 6 months postoperatively. RESULTS: All the patients regained their full neurosensory function after 6 months, with statistically nonsignificant differences between both groups throughout the follow-up period. The mean marginal bone loss in the test group was (0.42 ± 0.09) mm versus (0.38 ± 0.14) mm for the control group, which was statistically similar (P = 0.401). The 6-month postoperative mean implant stability quotient values of the test group recorded (74.73 ± 2.68) versus (74.73 ± 1.79) for the control group, which was statistically nonsignificant with a value of P = 0.626. CONCLUSION: The interposed bone graft, coupled with the collagen membrane isolation, neither subsided the neural disturbances nor enhanced the secondary implant stability and marginal bone loss.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".