Early ultrasound for diagnosis and treatment of vascular adverse events with hyaluronic acid fillers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BackgroundHyaluronic acid fillers are known for a reliable safety profile, but complications do occur, even serious vascular adverse events.ObjectiveTo improve the treatment outcome after a vascular adverse event with use of hyaluronic acid filler treatments.MethodsDuplex ultrasonography is used to detect the hyaluronic acid filler causing the intra-arterial obstruction.ResultsIf treated in time, 1 single treatment of ultrasonographically guided injections of hyaluronidase into the filler deposit will prevent skin necrosis.ConclusionBecause the use of duplex ultrasonography adds extra essential information, its use may become an integral part of the prevention and treatment of injection adverse events. Hyaluronic acid fillers are known for a reliable safety profile, but complications do occur, even serious vascular adverse events. To improve the treatment outcome after a vascular adverse event with use of hyaluronic acid filler treatments. Duplex ultrasonography is used to detect the hyaluronic acid filler causing the intra-arterial obstruction. If treated in time, 1 single treatment of ultrasonographically guided injections of hyaluronidase into the filler deposit will prevent skin necrosis. Because the use of duplex ultrasonography adds extra essential information, its use may become an integral part of the prevention and treatment of injection adverse events.
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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 it