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Record W2897299752 · doi:10.1093/asj/sjy247

Commentary on: Pathophysiology Study of Filler-Induced Blindness

2018· letter· en· W2897299752 on OpenAlexaff
Jean Carruthers

Bibliographic record

VenueAesthetic Surgery Journal · 2018
Typeletter
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicinePathophysiologyBlindnessFiller (materials)OptometryPathologyComposite material

Abstract

fetched live from OpenAlex

This excellent study, based on a well-planned and well-executed physiologic cadaveric model, provides clinicians with a clear demonstration of inadvertent supratrochlear cannulation, proposed to be cause of the most feared complication of cosmetic filler injection: iatrogenic blindness.1 The supratrochlear vessels were chosen for study as the glabella is the commonest site of vascular occlusion reported worldwide.2 The authors selected 6 cadaver heads with no known pre-existing cranial dysmorphism or disease, and created a life-like situation with a perfusion model that simulates the rate and pulsation of blood flow, with cannulation of the common carotid artery and jugular vein to complete the vascular circuit. The superficial branch of the supratrochlear artery (STA) was selected to be cannulated under direct vision, and in 3 of the 6 heads the hyaluronic acid (HA) filler injected into the supratrochlear vessels was demonstrated physically in the ipsilateral ophthalmic artery. A C-arm angiogram confirmed the presence of the HA filler, as well as the absence of ophthalmic artery blood flow in those heads. These 3 cadaver heads with ophthalmic artery occlusion had average supratrochlear vessel diameters of 1.42 mm. In the other 3 cadaveric heads, in which no supratrochlear cannulation was possible (average STA diameter: 0.84 mm), no ophthalmic artery occlusion occurred.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.062
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0030.005
Open science0.0030.002
Research integrity0.0620.036
Insufficient payload (model declined to judge)0.0080.005

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.

Opus teacher head0.051
GPT teacher head0.309
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2018
Admission routes1
Has abstractno

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