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Record W4404386205 · doi:10.1177/24741264241297936

Serpiginous Choroiditis After COVID-19 Infection

2024· article· en· W4404386205 on OpenAlexaff
Sorayya Seddigh, Ashlyn Pinto, Amr Zaki, R. Rishi Gupta

Bibliographic record

VenueJournal of VitreoRetinal Diseases · 2024
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChoroiditisMedicineFundus (uterus)Retinal pigment epitheliumOphthalmologyCoronavirus disease 2019 (COVID-19)Indocyanine green angiographyLesionRetinalFluorescein angiographyPathology

Abstract

fetched live from OpenAlex

Purpose: To present the first case of macular serpiginous choroiditis after COVID-19 infection. Methods: A single case was analyzed. Results: A 28-year-old previously healthy man presented with severe unilateral vision loss in the left eye. A fundus examination showed severe atrophic pigmentary changes that corresponded with optical coherence tomography (OCT) findings of a rapidly progressing amoeboid-like lesion disrupting the ellipsoid zone and retinal pigment epithelium. Multimodal imaging, including fundus autofluorescence, OCT angiography, and indocyanine green angiography, was supportive of serpiginous choroiditis. After a comprehensive systemic workup, the diagnosis of macular serpiginous choroiditis was confirmed. No improvement was seen with high-dose steroids; therefore, an immunosuppressive regimen was initiated. Conclusions: An exaggerated choroidal inflammatory response may be triggered by a COVID-19 infection, although causation cannot be inferred. Retinal manifestations should be considered when assessing patients presenting with visual symptoms after COVID-19 infection.

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)0.001
metaresearch head score (Gemma)0.003
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
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.316
Teacher spread0.306 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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