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Record W2982207199 · doi:10.1136/bcr-2019-231211

Acute kidney injury from immune checkpoint inhibitor use

2019· article· en· W2982207199 on OpenAlexaff
Lexis Gordon, Pouneh Dokouhaki, Kimberly R. Hagel, Bhanu Prasad

Bibliographic record

VenueBMJ Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsRegina General HospitalSaskatchewan Cancer AgencyUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineAcute kidney injuryImmune systemNivolumabImmunosuppressionAdverse effectVomitingImmunologyInternal medicineImmunotherapy

Abstract

fetched live from OpenAlex

Immune checkpoint inhibitors are novel oncological medications, current classes of which include monoclonal antibodies that target inhibitory receptors cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), programmed death 1 protein (PD-1) and programmed death-ligand 1. While they are novel in their ability to treat cancer, they also have a unique spectrum of immune-related adverse events. Renal-related immune adverse events, though rare, are an increasingly recognised clinical entity. We present the case of a 67-year-old man with acute kidney injury (AKI) after the second cycle of combination anti-CTLA-4 and anti-PD-1 antibodies for metastatic cutaneous melanoma. He presented with vomiting and diarrhoea, and AKI secondary to dehydration was treated with aggressive rehydration. After failing to recover biochemically, a renal biopsy was performed, which demonstrated severe acute interstitial nephritis. The culprit medications were held and he was treated with steroids. With immunosuppression, creatinine improved to pretreatment values.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.999

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)0.0020.000

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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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