The Alberta Reconstructive Technique: An Occlusion‐Driven and Digitally Based Jaw Reconstruction
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The free flap reconstructive protocols of the jaws have been refined over the years and presently are based on bone-driven approaches that generally use the lower border of the mandible or the anterior surface of the maxilla as the templates for reconstruction because these contours are deemed important to the eventual cosmetic outcomes of patients. The ultimate goal of functional jaw reconstruction, however, is the reconstruction of the dental occlusion and oral rehabilitation. The purpose of the present study was to evaluate the Alberta reconstructive technique (ART), which is a new approach of occlusion-driven jaw reconstruction with digitally planned immediate osseointegrated implant installation. STUDY DESIGN: Prospective cohort study. METHODS: This research study considers the ART's safety, effectiveness, accuracy, timeliness of reconstruction, aesthetic appeal, and cost-effectiveness in comparison with the standard bone-driven and delayed osseointegrated implant installation (BDD) protocol. RESULTS: The ART procedures were as safe and more effective at achieving full occlusal reconstruction and oral rehabilitation. The ART cohort of patients achieved oral rehabilitation in 21.4 month as compared to 73.1 months for the BDD cohort. There were no differences in the aesthetic appeal the two groups. The ART cost an average of $22,004 less than BDD and we calculated the quality adjusted life years gain to be between 2.14 and 4.04 in favour of ART. CONCLUSIONS: The ART is a good option for patients with jaw defects. It provides a safe, effective, accurate, aesthetic, and cost-effective reconstruction that restores form and function in a timely manner. LEVEL OF EVIDENCE: 2b Laryngoscope, 129:S1-S14, 2019.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".