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Record W4396229481 · doi:10.4103/joco.joco_21_23

Hypotony and Anterior Uveitis following Dual Therapy with Nivolumab and Ipilimumab for Metastatic Melanoma: A Case Report

2023· article· en· W4396229481 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
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineIpilimumabNivolumabMetastatic melanomaMelanomaUveitisDermatologyOncologyInternal medicineOphthalmologyImmunotherapyCancer researchCancer

Abstract

fetched live from OpenAlex

Purpose: To describe a rare case of hypotony and anterior uveitis following dual therapy with nivolumab and ipilimumab for metastatic melanoma. Methods: Case report. Results: Here, we present the case of a 64-year-old man taking nivolumab and ipilimumab dual therapy for BRAF+ (v-raf murine sarcoma viral oncogene homolog B1) metastatic melanoma. After treatment for 3 months, he presented to the ophthalmology clinic with bilateral intraocular pressures of 1 mmHg, bilateral keratic precipitates, cataracts, posterior synechiae, and anterior chamber inflammation. He improved with topical medications and the cessation of immunotherapy. Conclusions: Immunotherapies are a novel class of chemotherapy that has increased in prevalence for the treatment of numerous malignancies. There are many rare complications from these medications that are sparsely reported. Knowledge of ocular hypotony as a potential consequence of nivolumab and ipilimumab is important, particularly as it may arise months after treatment initiation and necessitate immunotherapy cessation.

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 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 score0.402
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.046
GPT teacher head0.328
Teacher spread0.282 · 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