Patiromer-Facilitated Renin-Angiotensin-Aldosterone System Inhibitor Utilization in Patients with Heart Failure with or without Comorbid Chronic Kidney Disease: Subgroup Analysis of DIAMOND Randomized Trial
Bibliographic record
Abstract
INTRODUCTION: Renin-angiotensin-aldosterone system inhibitor (RAASi; including mineralocorticoid receptor antagonists [MRAs]) benefits are greatest in patients with heart failure with reduced ejection fraction (HFrEF) and chronic kidney disease (CKD); however, the risk of hyperkalemia (HK) is high. METHODS: The DIAMOND trial (NCT03888066) assessed the ability of patiromer to control serum potassium (sK+) in patients with HFrEF with/without CKD. Prior to randomization (double-blind withdrawal, 1:1), patients on patiromer had to achieve ≥50% recommended doses of RAASi and 50 mg/day of MRA with normokalemia during a run-in period. The present analysis assessed the effect of baseline estimated glomerular filtration rate (eGFR) in subgroups of ≥/<60, ≥/<45 (prespecified), and ≥/<30 mL/min/1.73 m2 (added post hoc). RESULTS: In total, 81.3, 78.9, and 81.1% of patients with eGFR <60, <45, and <30 mL/min/1.73 m2 at screening achieved RAASi/MRA targets. A greater efficacy of patiromer versus placebo to control sK+ in patients with more advanced CKD was reported (p-interaction ≤ 0.027 for all eGFR subgroups). Greater effects on secondary endpoints were observed with patiromer versus placebo in patients with eGFR <60 and <45 mL/min/1.73 m2. Adverse effects were similar between patiromer and placebo across subgroups. CONCLUSION: Patiromer enabled use of RAASi, controlled sK+, and minimized HK risk in patients with HFrEF, with greater effect sizes for most endpoints noted in patient subgroups with lower eGFR. Patiromer was well tolerated by patients in all eGFR subgroups.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".