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Patiromer: A significant advance in the management of hyperkalemia

2015· review· en· W2398096896 on OpenAlexaff
David M. Paton

Bibliographic record

VenueDrugs of today · 2015
Typereview
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHyperkalemiaMedicineSpironolactoneKidney diseaseHeart failureAldosteroneAdverse effectInternal medicineUrology

Abstract

fetched live from OpenAlex

The U.S. Food and Drug Administration (FDA) approved patiromer to treat hyperkalemia on October 21, 2015, making it the first agent approved for this condition in 50 years. Patiromer was developed by Relypsa, Inc. The active ingredient is patiromer sorbitex calcium which consists of the active moiety, patiromer, a nonabsorbed potassium-binding polymer, and a calcium-sorbitol counterion. In the colon, patiromer exchanges calcium for potassium thus causing a fall in serum potassium. Trials have shown that patiromer reduces serum potassium in patients with mild, moderate and moderate to severe hyperkalemia to the normal range. It has also been used successfully in patients with chronic kidney disease and/or heart failure. It has also allowed the use of the mineralocorticoid antagonist spironolactone in full dosage in patients with chronic kidney disease and/or heart failure who were already receiving a renin-angiotensin-aldosterone system inhibitor. Adverse effects have mostly been gastrointestinal in nature and have not caused patients to discontinue treatment in unacceptable numbers.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.030
GPT teacher head0.336
Teacher spread0.306 · 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
GenreReview

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

Citations4
Published2015
Admission routes1
Has abstractyes

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