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Record W4312673191 · doi:10.4103/joco.joco_41_22

Unilateral Acute Central Serous Chorioretinopathy with Inactivated Coronavirus Disease 2019 Vaccination

2022· article· en· W4312673191 on OpenAlexaff
Mojtaba Abrishami, Seyedeh Maryam Hosseini, Nasser Shoeibi, Hamid Reza Heidarzadeh

Bibliographic record

VenueJournal of Current Ophthalmology · 2022
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSerous fluidVaccinationCoronavirus disease 2019 (COVID-19)CoronavirusDiseaseVirologyOphthalmologyInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Purpose: To report unilateral acute-onset central serous chorioretinopathy (CSC) following vaccination with inactivated coronavirus disease 2019 (COVID-19) vaccine in a healthy patient. Methods: Case report and review of literature. Results: A 39-year-old male was referred with sudden-onset, painless, unilateral blurred vision in the right eye. His first dose of the Sinopharm vaccine was injected 2 days before. A complete ocular examination revealed central subretinal fluid (SRF) accumulation in favor of CSC in the right eye. Systemic workup disclosed no previous COVID-19 infection or any systemic involvement. After 3 weeks, SRF decreased remarkably without treatment. Conclusions: It is proposed that CSC development can be an ocular adverse effect of COVID-19 vaccination, although it is infrequent. Ophthalmologists should be aware of the possible association between COVID-19 vaccination and ocular adverse effects, but vaccination is the best effectual measure against COVID-19.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.035
GPT teacher head0.345
Teacher spread0.310 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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