Aprocitentan: a new horizon in the treatment of hypertension
Bibliographic record
Abstract
INTRODUCTION: There has been a lack of novel medication classes approved for reducing blood pressure (BP) in hypertensive patients. Endothelins, powerful vasoconstricting peptides, have been at the forefront of experimental hypertension research since they were discovered in 1988. The recent PRECISION trial demonstrated the efficacy of aprocitentan, a novel endothelin receptor antagonist, in lowering blood pressure in patients with resistant hypertension (RH). This trial was the driving force behind the approval of aprocitentan in 2024 for the treatment of resistant hypertension. AREAS COVERED: This clinical trial review will cover the literature leading to the approval of aprocitentan and argue for its use on top of current treatments of hypertension. We argue for the need of novel anti-hypertensive medication classes and provide a brief overview of endothelin receptor antagonists. Finally, we will describe the PRECISION trial and highlight the key benefits of aprocitentan that it elucidated. EXPERT OPINION: The PRECISION trial demonstrated numerous key benefits of aprocitentan, including efficacy in reducing BP and proteinuria, minimal adverse side effects, and efficacy in patients with advanced chronic kidney disease (CKD) without development of hyperkalemia. However, a lack of long-term data necessitates future investigation regarding safety. Aprocitentan may represent a novel therapeutic alternative to treat patients with RH and CKD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".