Use of Mineralocorticoid Receptor Antagonists in Patients With Heart Failure and Comorbid Diabetes Mellitus or Chronic Kidney Disease
Bibliographic record
Abstract
Background Perceived risks of hyperkalemia and acute renal insufficiency may limit use of mineralocorticoid receptor antagonist ( MRA ) therapy in patients with heart failure, especially those with diabetes mellitus or chronic kidney disease. Methods and Results Using clinical registry data linked to Medicare claims, we analyzed patients hospitalized with heart failure between 2005 and 2013 with a history of diabetes mellitus or chronic kidney disease. We stratified patients by MRA use at discharge. We used inverse probability–weighted proportional hazards models to assess associations between MRA therapy and 30‐day, 1‐year, and 3‐year mortality, all‐cause readmission, and readmission for heart failure, hyperkalemia, and acute renal insufficiency. We performed interaction analyses for differential effects on 3‐year outcomes for reduced, borderline, and preserved ejection fraction. Of 16 848 patients, 12.3% received MRA therapy at discharge. Higher serum creatinine was associated with lower odds of MRA use (odds ratio, 0.66; 95% confidence interval, 0.61–0.71); serum potassium was not (odds ratio, 1.00; 95% confidence interval, 0.90–1.11). There was no mortality difference between groups. MRA therapy was associated with greater risks of readmission for hyperkalemia and acute renal insufficiency and lower risks of long‐term all‐cause readmission. Patients on MRA therapy with borderline or preserved ejection fraction had greater risks of readmission for hyperkalemia ( P =0.02) and acute renal insufficiency ( P <0.001); patients with reduced ejection fraction did not. Conclusions Among patients with heart failure and diabetes mellitus or chronic kidney disease, MRA use was associated with lower risk of all‐cause readmission despite greater risk of hyperkalemia and acute renal insufficiency.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".