MétaCan
Menu
Back to cohort
Record W4292870479 · doi:10.1177/10781552221122005

Ocular toxicity following carboplatin chemotherapy for neuroendocrine tumour of the bladder

2022· article· en· W4292870479 on OpenAlexaff
Jia Ng, Muhayman Sadiq, Qasim Mansoor

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2022
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Ocular Toxicity
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsCarboplatinMedicineChemotherapyCisplatinToxicityBlurred visionEtoposideSurgeryOncologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Carboplatin is a commonly used platinum analogue chemotherapeutic agent that is similar to cisplatin but is known to be better tolerated. This case report outlines a case of ocular toxicity following carboplatin chemotherapy used for the management of a neuroendocrine tumour of the bladder. CASE REPORT: A 70-year-old man with a history of neuroendocrine bladder cancer underwent chemotherapy with carboplatin and etoposide. He presented 4 weeks following his fourth chemotherapy cycle with a 1-week history of right eye blurriness. The patient had suffered a similar episode 2 weeks following his third chemotherapy cycle in his left eye. Carboplatin-induced ocular toxicity was suspected and his vision remained stable following cessation of carboplatin chemotherapy. DISCUSSION: Current literature on carboplatin-induced ocular toxicity remains scanty, however, previous cases have reported symptoms beginning 5 days to 2 weeks following carboplatin use. Visual disturbance in the form of altered colour vision, blind spot, blurred vision and metamorphopsia have been reported by previous literature. This case report emphasised a case of bilateral sequential blurring of vision following carboplatin chemotherapy. CONCLUSION: It remains critical for ophthalmologists and oncologists to look out for ocular side effects of chemotherapy due to its devastating effects.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.394
Teacher spread0.355 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Oncology Pharmacy PracticeSame topicDrug-Induced Ocular ToxicityFrench-language works237,207