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Record W3163644691 · doi:10.15420/cfr.2020.29

Hyperkalaemia in Heart Failure

2021· review· en· W3163644691 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCardiac failure review · 2021
Typereview
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
Fundersnot available
KeywordsMedicineHeart failureIntensive care medicineGuidelineKidney diseaseDiabetes mellitusInternal medicineCardiologyEndocrinologyPathology

Abstract

fetched live from OpenAlex

Hyperkalaemia has become an increasingly prevalent finding in patients with heart failure (HF), especially with renin-angiotensin-aldosterone system (RAAS) inhibitors and angiotensin-neprilysin inhibitors being the cornerstone of medical therapy. Patients living with HF often have other comorbidities, such as diabetes and chronic kidney disease, which predispose to hyperkalaemia. Until now, we have not had any reliable or tolerable therapies for the treatment of hyperkalaemia to facilitate implementation or achievement of target doses of RAAS inhibition. Patiromer sorbitex calcium and sodium zirconium cyclosilicate are two novel potassium-binding resins that have shown promise in the management of patients predisposed to developing recurrent hyperkalaemia, and their use may allow for further optimisation of guideline directed medical 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.480
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.004
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.327
Teacher spread0.304 · 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