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Record W2980441092 · doi:10.1097/wno.0000000000000850

Rapidly Sequential Vision Loss From Posterior Ischemic Optic Neuropathy Due to Methicillin-Susceptible Staphylococcus Aureus Bacteremia

2019· article· en· W2980441092 on OpenAlexaff
Sultan Aldrees, Jonathan A. Micieli

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2019
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsKensington HealthUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineBacteremiaContext (archaeology)Visual acuitySepsisFundus (uterus)EndophthalmitisIntensive care unitSurgeryOphthalmologyInternal medicine

Abstract

fetched live from OpenAlex

A 63-year-old man with a history of high-grade bladder cancer was admitted to the intensive care unit (ICU) with renal failure and methicillin-susceptible Staphylococcus aureus bacteremia originating from his nephrostomy tube. While in the ICU, he had painless, severe loss of vision in the right eye followed by his left eye 12 hours later. Visual acuity was no light perception in each eye. He was anemic, and before each eye lost vision, there was a significant decrease in blood pressure. Dilated fundus examination was normal, and MRI showed hyperintense signal in the bilateral intracanalicular optic nerves on diffusion-weighted imaging and a corresponding low signal on apparent diffusion coefficient imaging. He was diagnosed with bilateral posterior ischemic optic neuropathies (PION), and despite transfusion and improvement in his systemic health, his vision did not recover. PION may be seen in the context of sepsis, and patients with unilateral vision loss have a window for optimization of risk factors if a prompt diagnosis is made.

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 score0.003
Threshold uncertainty score0.010

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 studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.307
Teacher spread0.289 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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