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Record W4412529176 · doi:10.34067/kid.0000000934

Long-Term Experience of Tolvaptan

2025· article· en· W4412529176 on OpenAlexafffundabout
Pierre Antoine Brown, Suzy Bubolic, Annick Laplante, Thomas Jaeger

Bibliographic record

VenueKidney360 · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsMcGill University Health CentreOttawa HospitalUniversity of Ottawa
FundersOtsuka Canada Pharmaceutical
KeywordsTolvaptanMedicineAutosomal dominant polycystic kidney diseaseIntensive care medicineRenal functionInternal medicineAcute kidney injuryLiver injuryDiseaseHeart failure

Abstract

fetched live from OpenAlex

In Canada, tolvaptan (JINARC) is approved for the treatment of adults with autosomal dominant polycystic kidney disease to slow the progression of kidney enlargement and kidney function decline. Safety data from the pivotal Tolvaptan Efficacy and Safety in Management of Autosomal Dominant Polycystic Kidney Disease and Its Outcomes (TEMPO 3:4) study suggested the potential for increased risk of liver injury with tolvaptan, which led to the establishment of the Canadian Hepatic Safety Monitoring and Distribution Programme in 2015. This review summarizes data regarding hepatic safety from clinical trials and presents data from established risk mitigation programs and real-world evidence. Data show that frequent liver function monitoring allows timely detection of drug-induced liver injury and prompt treatment interruption. To date, this approach has led to the absence of serious liver injury or liver failure in more than 2800 patients treated with tolvaptan in Canada over the past 10 years.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.369

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 head0.007
GPT teacher head0.272
Teacher spread0.265 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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