Nasal Tip Deprojection in Rhinoplasty
Bibliographic record
Abstract
BACKGROUND: Rhinoplasty is one of the most commonly performed facial operations in the United States, and many major and minor nasal tip support structures affect tip projection. Overprojection may result from anatomical factors or occur iatrogenically during primary rhinoplasty. Achieving reliable, reproducible, and stable results is the aim of nasal tip deprojection rhinoplasty. The authors' technique is designed to decrease nasal tip deprojection in patients with an overly projected nasal tip. METHODS: A retrospective chart review of 2003 rhinoplasty cases in the senior author's (R.G.R.) practice was conducted for the period between July of 2014 and June of 2022. The inclusion criteria were cosmetic or functional rhinoplasty cases with nasal tip deprojection, with a minimum of 12 months of follow-up. Outcomes of interest included the rate of operative revisions and the rate of postoperative infection. RESULTS: A total of 447 patients met the inclusion criteria. The mean age of our study group was 32.1 years, with 409 female patients, and 291 cases were primary rhinoplasties. The mean follow-up period was 22.4 months. Eight patients (1.8%) required empiric antibiotics postoperatively, and 17 patients (3.8%) required operative revision. CONCLUSIONS: The authors' case series demonstrates that combining resection of the medial crura with lateral crural steal and a columellar strut graft allows the surgeon to achieve considerable nasal tip deprojection. The comprehensive patient follow-up (mean, 22.4 months) further supports the reliability of the authors' technique. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".