Transfixion Incision As An Initial Technique in Nasal Tip Deprojection
Bibliographic record
Abstract
BACKGROUND: The overprojected nasal tip presents a significant challenge to the surgeon performing rhinoplasty. Full transfixion incision as a means of dealing with this deformity has been studied only in combination with other surgical methods. OBJECTIVES: To determine whether transfixion incision alone would result in significant nasal tip deprojection, and if skin thickness had an effect on the extent of deprojection the procedure yielded. METHOD: Seventy-two consecutive patients with an aesthetic goal of nasal tip deprojection were enrolled. The sole surgical means of deprojection used was transfixion incision. Subjects were categorized as thin-, medium- or thick-skinned based on the surgeon's analysis. These groups were compared in terms of their postprocedural nasal tip deprojection. RESULTS: Using transfixion incision as the sole means of correcting this deformity resulted in a mean nasal tip deprojection of 1.6 mm (ranging from 0 mm to 3 mm). Patients in the thin skin group had a mean deprojection of 2.12 mm. This was significantly greater than for both the medium- and thick-skinned groups. There was no significant difference between the medium- and thick-skinned groups. CONCLUSIONS: Surgeons may use skin thickness when planning interventions for correcting nasal tip overprojection. When used alone, transfixion incision resulted in tip deprojection comparable with that achieved when combined with other methods, particularly for thin-skinned patients. Surgeons can thus use a graduated approach in which transfixion incision, the least destructive method, is used before proceeding with other interventions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".