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Record W2041681837 · doi:10.1055/s-0031-1278380

Arteritic anterior ischemic optic neuropathy treated with intravenous prostaglandin E<sub>1</sub>and steroids

2010· article· en· W2041681837 on OpenAlexaff
Robert D. Steigerwalt, M R Cesarone, Gianni Belcaro, Antonella Pascarella, Mauro De Angelis, Roberto Gattegna, Marcella Nebbioso

Bibliographic record

VenueInternational Journal of Angiology · 2010
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsMonsanto (Canada)
Fundersnot available
KeywordsMedicineAnterior ischemic optic neuropathyVisual acuityOptic nerveCiliary arteriesVasodilationIschemiaBlood flowOptic neuropathyProstaglandin E1AnesthesiaOphthalmologyMicrocirculationOphthalmic arterySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Arteritic anterior ischemic optic neuropathy (AAION) is an acute ischemia of the posterior ciliary arteries and/or ophthalmic artery due to inflammation. Therapy is immediate intervention with systemic steroids, especially to protect against vision loss in the other eye. The addition of a potent vasodilator to the steroids could help restore ocular blood flow and improve visual acuity. The objective of the current report was to present the use of prostaglandin E(1) (PGE(1)) - a powerful vasodilator of the microcirculation - in the treatment of AAION. Two patients with AAION were treated with intravenous steroids and PGE(1). The visual acuity improved from 4/50 (less than 20/200) to 6/10 (20/35) in one patient and from 1/50 (20/400) to 1/10 (20/200) in the second patient. The visual fields in both patients maintained small central islands of vision. No complications due to the use of PGE(1) were seen. Intravenous PGE(1) should be considered in addition to steroids in cases of AAION to immediately restore blood flow to the optic nerve and improve visual acuity while the steroids reduce the inflammation.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.242
Teacher spread0.237 · 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 designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2010
Admission routes1
Has abstractyes

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