Vertical Lobule Division in Rhinoplasty
Bibliographic record
Abstract
OBJECTIVE: To review the indications for, surgical techniques of, and results of vertical lobule division (VLD) of the alar cartilages. DESIGN: Prospective study of patients assigned to undergo variations of VLD of the lower lateral cartilages. SETTING: Private facial plastic surgery practice in a major university teaching hospital. PATIENTS: Twenty-four patients who underwent variations of VLD of the lower lateral cartilages with re-creation of an intact strip, including 4 patients undergoing revision. MAIN OUTCOME MEASURES: Postoperative photographs were reviewed for tip projection and rotation, tip symmetry, bossae, knuckles, columellar position and length, and alar retraction. Patients were polled about their overall satisfaction with nasal aesthetics and degree of subjective nasal obstruction preoperatively and postoperatively. RESULTS: Vertical lobule division decreased projection in 22 of 22 patients, increased rotation in 12 of 12 patients, decreased rotation in 1 of 2 patients, corrected tip asymmetry in 3 of 4 patients, and shortened a long infratip lobule in 1 patient. Postoperatively, bossae and knuckling developed in 1 patient, and 2 patients demonstrated alar retraction that did not exist preoperatively. One patient undergoing revision noted worsened nasal obstruction not related to VLD. CONCLUSIONS: Vertical lobule division is a reliable, safe technique with predictable outcomes in tip repositioning. It allows for preservation of a strong tip complex while adding versatility to tip refinement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".