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Record W4402733251 · doi:10.1016/j.jacc.2024.05.079

Patiromer Facilitates Angiotensin Inhibitor and Mineralocorticoid Antagonist Therapies in Patients With Heart Failure and Hyperkalemia

2024· article· en· W4402733251 on OpenAlex
Bertram Pitt, Stefan D. Anker, Lars H. Lund, Andrew J.S. Coats, Gerasimos Filippatos, Patrick Rossignol, Matthew R. Weir, Tim Friede, Mikhail Kosiborod, Marco Metra, Michael Böhm, Justin A. Ezekowitz, Antoni Bayés‐Genís, Robert J. Mentz, Piotr Ponikowski, Michele Senni, Ileana L. Piña, Fausto J. Pinto, Peter van der Meer, Cecilia Bahit, Jan Bělohlávek, Jasper J. Brugts, Amandine Perrin, Sandra Waechter, Jeffrey Budden, Javed Butler

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

VenueJournal of the American College of Cardiology · 2024
Typearticle
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHyperkalemiaMedicineMineralocorticoid receptorHeart failureAntagonistRenin–angiotensin systemInternal medicineEjection fractionMineralocorticoidAldosteroneCardiologyEndocrinologyPharmacologyReceptorBlood pressure

Abstract

fetched live from OpenAlex

BACKGROUND: Hyperkalemia (HK) is associated with suboptimal renin-angiotensin system (RAS) inhibitor and mineralocorticoid receptor antagonist (MRA) use in heart failure with reduced ejection fraction (HFrEF). OBJECTIVES: This study sought to assess characteristics and RAS inhibitor/MRA use in patients receiving patiromer during the DIAMOND (Patiromer for the Management of Hyperkalemia in Subjects Receiving RAASi Medications for the Treatment of Heart Failure) run-in phase. METHODS: Patients with HFrEF and HK or past HK entered a run-in phase of ≤12 weeks with patiromer-facilitated RAS inhibitor/MRA optimization to achieve ≥50% recommended RAS inhibitor dose, 50 mg/d MRA, and normokalemia. Patients achieving these criteria (randomized group) were compared with the run-in failure group (patients not meeting the randomization criteria). RESULTS: Of 1,038 patients completing the run-in, 878 (84.6%) were randomized and 160 (15.4%) were run-in failures. Overall, 422 (40.7%) had HK entering run-in with a similar frequency in the randomized and run-in failure groups (40.3% vs 42.5%; P = 0.605). From start to the end of run-in, in the randomized group, an increase was observed in target RAS inhibitor and MRA use in patients with HK (RAS inhibitor: 76.8% to 98.6%; MRA: 35.9% to 98.6%) and past HK (RAS inhibitor: 60.5% to 98.1%; MRA: 15.6% to 98.7%). Despite not meeting the randomization criteria, an increase after run-in was observed in the run-in failure group in target RAS inhibitor (52.5% to 70.6%) and MRA use (15.0% to 48.1%). This increase was observed in patients with HK (RAS inhibitor: 51.5% to 64.7%; MRA: 19.1% to 39.7%) and past HK (RAS inhibitor: 53.3% to 75.0%; MRA: 12.0% to 54.3%). CONCLUSIONS: In patients with HFrEF and HK or past HK receiving suboptimal RAS inhibitor/MRA therapy, RAS inhibitor/MRA optimization increased during patiromer-facilitated run-in.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.004
GPT teacher head0.212
Teacher spread0.208 · 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