A Multilayer Cartilaginous Tip‐Grafting Technique for Improved Nasal Tip Refinement in Asian Rhinoplasty
Bibliographic record
Abstract
OBJECTIVE: Tip surgery remains the most difficult part of rhinoplasty in Asian patients because of the lower lateral cartilage characteristics and thick skin. The objective of this study was to evaluate the multilayer cartilaginous tip-grafting technique used for tip refinement in Korean patients undergoing rhinoplasty. STUDY DESIGN: Case series with chart review. SETTING: Academic tertiary care medical center. SUBJECTS AND METHODS: A retrospective study of 99 Korean patients who underwent open rhinoplasty involving multilayer cartilaginous tip-grafting for tip refinement was performed. Autologous septal, conchal, costal, or homologous costal cartilage, or a combination of these materials was used as grafting materials. Preoperative and postoperative photographs were reviewed for objective and subjective assessment of aesthetic outcomes. RESULTS: Among patients, 7 had undergone previous rhinoplasty (7.1%), and removal of the previously placed silicone graft was required in 5 patients (5.1%). Two (6.7%), 3 (61.5%), 4 (28.8%), and 5 (3.0%) layers of cartilaginous graft were used. Postoperative aesthetic outcomes were graded as excellent in 63.6%, fair in 28.3%, and no change/worse in 8.1% of cases. Preoperative and postoperative objective measurements showed that the procedure resulted in increased nasal tip projection (0.52 ± 0.06 vs 0.57 ± 0.05; P < .05) and improved nasolabial angle (92.98° ± 9.95° vs 95.34° ± 8.20°; P < .05). The overall complication rate was 12.1%, and 8 patients required revision surgery (8.1%). Complications included infection (5.1%), visible graft contour (1.0%), nostril deformity (1.0%), overprojection (2.0%), and visible hypertrophic scar at the marginal incision site (3.0%). CONCLUSIONS: The multilayer cartilaginous tip-grafting technique was found to be effective for aesthetic refinement of the nasal tip when used in rhinoplasty for Korean patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".