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Record W2302979646 · doi:10.1155/2016/1926178

Photopsias during Systemic Bevacizumab Therapy

2016· article· en· W2302979646 on OpenAlexfundno aff
Heather Leisy, Meleha Ahmad, R. Theodore Smith

Bibliographic record

VenueCase Reports in Ophthalmological Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
FundersSchool of Medicine, New York UniversityYork UniversityResearch to Prevent Blindness
KeywordsMedicineBevacizumabFundus (uterus)OphthalmologyNerve fiber layerRetinalOptical coherence tomographyPresentation (obstetrics)Case presentationSurgeryChemotherapy

Abstract

fetched live from OpenAlex

Background. The authors describe a case of recurrent photopsias in a 56-year-old woman following repeat treatments with systemic intravenous bevacizumab for stage IV ovarian cancer. To our knowledge, this is the first report of photopsias following systemic bevacizumab treatments in a patient with a normal eye exam. Case Presentation. A 56-year-old Caucasian female complained of onset of floaters and flashes in the temporal peripheral field of the right eye 1 day after receiving intravenous of 30 g of 25 mg/mL of systemic bevacizumab for treatment of stage IV ovarian cancer. Ophthalmic examination, including dilated fundus exam, spectral domain optical coherence tomography (SD-OCT) of the optic nerve head, and enhanced depth imaging SD-OCT of the macula, revealed no significant abnormalities. Possible mechanisms are reviewed. Conclusion. We propose that patients who undergo intravenous bevacizumab treatments are questioned for any ocular symptoms and that more systematic evaluations of retinal nerve fiber layer and choroidal effects are obtained in those patients who are on long-term treatment at high doses.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.009
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.339
Teacher spread0.290 · 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 teacher head, not a consensus.

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
Published2016
Admission routes1
Has abstractyes

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