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Record W4386529567 · doi:10.4103/joco.joco_111_23

Reply to Letter to Editor: Unilateral Acute Central Serous Chorioretinopathy with Inactivated Coronavirus Disease 2019 Vaccination – A Case Report and Review of Literature

2023· letter· en· W4386529567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Current Ophthalmology · 2023
Typeletter
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineVaccinationSerous fluidDiseaseConfoundingCausality (physics)Incidence (geometry)PediatricsIntensive care medicineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Dear Editor, We thank the authors for their comments regarding our article entitled “Unilateral acute central serous chorioretinopathy with inactivated coronavirus disease 2019 (COVID-19) vaccination: A case report and review of literature”.1 We presented a case report of a 39-year-old man who developed central serous chorioretinopathy (CSC) 2 days after receiving the Sinopharm vaccine, and we acknowledge that the relationship between COVID-19 vaccination and ocular side effects is worth studying. While we considered the probability of coincidence due to the patient’s age and gender, we agree that the influence of confounding variables and the pathopharmacological relationship between the vaccine and the clinical problem can be challenging to determine without sufficient clinical data on vaccine recipients’ physiological and immunological status before vaccination. However, we found no modifiable risk factors in the patient’s history for developing CSC. We believe that a longitudinal case–control study on a large number of participants is necessary to establish the true link between vaccination and these reported side effects. However, due to ethical concerns about vaccinating individuals against infectious diseases like COVID-19, which have proven benefits in decreasing the incidence and severity of infection,2 such studies may be challenging to conduct. Nevertheless, it is crucial to collect and report such cases to determine causality over coincidence. In addition, ophthalmologists must pay attention to relevant points in patient history when approaching similar cases. Clues that help to prove causality include time series, biological validity, dose-response relation, and findings concurrence. The autoimmune nature of all reported cases of presumed COVID-19 vaccine side effects is another factor that may help understand the causality. Furthermore, CSC has been reported after vaccination for influenza, yellow fever, anthrax, and smallpox; however, the causality has not been established in a proper manner.3–5 Thank you for your valuable comments on this important issue. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.352
Teacher spread0.323 · 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