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Record W4206297787 · doi:10.1097/icb.0000000000001219

EXUDATIVE RETINAL DETACHMENT AFTER INTRAVITREAL BROLUCIZUMAB INJECTION

2022· article· en· W4206297787 on OpenAlexaff
Devin Betsch, David Sarraf, Carolina L. M. Francisconi

Bibliographic record

VenueRetinal Cases & Brief Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineRetinal vasculitisRetinal detachmentOphthalmologyRetinalFluorescein angiographyAfliberceptVasculitisSurgeryBevacizumabDiseasePathologyChemotherapy

Abstract

fetched live from OpenAlex

PURPOSE: To report an unusual case of a patient who presented with intraocular inflammation (IOI) and an exudative retinal detachment after first brolucizumab injection and to compare this case to the existing literature. METHODS: An 80-year-old woman being treated for neovascular age-related macular degeneration presented 11 days after her first intravitreal injection of brolucizumab with IOI and an exudative retinal detachment. She was treated with systemic and topical steroids. The patient's chart was thoroughly reviewed, and notes were made on visual acuities and ocular examination findings at each relevant visit. Optical coherence tomography and ultra-widefield fluorescein angiography (UWFA) images were taken across multiple timepoints. RESULTS: The patient's IOI and exudative retinal detachment resolved three weeks after brolucizumab injection. In the literature, the incidence of IOI has been reported to be higher with brolucizumab versus aflibercept, but most of these cases were considered to be mild to moderate in severity. More recently, reports of severe IOI and retinal vasculitis associated with brolucizumab have been published in postmarketing surveillance articles. CONCLUSION: To the authors' knowledge, this is the first report of exudative retinal detachment after intravitreal brolucizumab injection. As the experience with this new drug continues to grow, reports of these events are critical to increase the understanding, so that future management strategies can be developed to improve patient outcomes.

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)0.003
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0040.003
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 head0.279
Teacher spread0.267 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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