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Record W4206713533 · doi:10.51731/cjht.2021.119

Patiromer (Veltassa)

2021· article· en· W4206713533 on OpenAlexaboutno aff
Reimbursement Team

Bibliographic record

VenueCanadian Journal of Health Technologies · 2021
Typearticle
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsReimbursementHyperkalemiaMedicineKidney diseaseIntensive care medicineRenal functionInternal medicineEconomic growthHealth care

Abstract

fetched live from OpenAlex

CADTH reimbursement reviews are comprehensive assessments of the clinical effectiveness and cost-effectiveness, as well as patient and clinician perspectives, of a drug or drug class. The assessments inform non-binding recommendations that help guide the reimbursement decisions of Canada's federal, provincial, and territorial governments, with the exception of Quebec. This review assesses patiromer (Veltassa), 8.4 g, 16.8 g, 25.2 g patiromer (as patiromer sorbitex calcium) and patiromer powder for oral suspension. Indication: For the treatment of hyperkalemia in adults with chronic kidney disease (estimated glomerular filtration rate ≥ 15 mL/min/1.73 m2). Reimbursement request: For the treatment of hyperkalemia in patients with chronic kidney disease 3 to 4 on renin-angiotensin-aldosterone system inhibitor therapy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.130
Threshold uncertainty score0.434

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1300.032

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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Health TechnologiesSame topicPotassium and Related DisordersFrench-language works237,207