Relationship Between Vertical Glabellar Lines and the Supratrochlear and Supraorbital Arteries
Bibliographic record
Abstract
BACKGROUND: Glabellar soft tissue filler injections have been shown to be associated with a high risk of causing injection-related visual compromise. OBJECTIVES: The aim of this study was to identify the course of the superficial branch of the supratrochlear and of the deep branch of the supraorbital artery in relation to the ipsilateral vertical glabellar line and to test whether an artery is located deep to this line. METHODS: Forty-one healthy volunteers with a mean age of 26.17 [9.6] years and a mean BMI of 23.09 [2.3] kg/m2 were analyzed. Ultrasound imaging was applied to measure the diameters, distance from skin surface, distance between the midline, distance between vertical glabella lines, and the cutaneous projection of the supratrochlear/supraorbital arteries at rest and upon frowning. RESULTS: The mean distance between the superficial branch of the supratrochlear artery and the ipsilateral vertical glabellar line was 10.59 [4.0] mm in males and 8.21 [4.0] mm in females, whereas it was 22.38 [5.5] mm for the supraorbital artery in males and 20.73 [5.6] mm in females. Upon frowning, a medial shift in supratrochlear arterial position of 1.63 mm in males and 1.84 mm in females and of 3.9 mm in supraorbital arterial position for both genders was observed. The mean depth of the supratrochlear artery was 3.34 [0.6] mm at rest, whereas the depth of the supraorbital artery was 3.54 [0.8] mm. CONCLUSIONS: The hypothesis that injecting soft tissue fillers next to the vertical glabellar line is safe because the supratrochlear artery courses deep to the crease should be rejected. Additionally, the glabella and the supraorbital region should be considered as an area of mobile, rather than static, soft tissues.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".