Targeting aldosterone to improve cardiorenal outcomes: from nonsteroidal mineralocorticoid receptor antagonists to aldosterone synthase inhibitors
Bibliographic record
Abstract
PURPOSE OF REVIEW: Aldosterone dysregulation plays a major role in the pathogenesis of hypertension, cardiovascular disease, and kidney disease. Traditionally, steroidal mineralocorticoid receptor (MR) antagonists, namely spironolactone and eplerenone, have been the only available options to target aldosterone. Over recent years, a host of promising novel aldosterone-targeted pharmacologic agents have been developed thereby providing new options to mitigate aldosterone-mediated cardiovascular and kidney disease. RECENT FINDINGS: Recently, a number of nonsteroidal MR antagonists (finerenone, esaxerenone, and ocedurenone) and highly specific aldosterone synthase inhibitors (baxdrostat, lorundrostat, dexfadrostat, and vicadrostat) have been developed. The early clinical data for these novel medications looks promising regarding their efficacy in improving blood pressure control, preventing adverse cardiovascular outcomes, and slowing chronic kidney disease progression. Moreover, they appear to be generally safe and well tolerated. SUMMARY: In the coming years, nonsteroidal MR antagonists and aldosterone synthase inhibitors are likely to play an increasingly large role in routine medical practice to help improve cardiovascular and kidney outcomes.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.005 | 0.002 |
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.
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".