Addition of Sacubitril/Valsartan to Mineralocorticoid Receptor Antagonist Therapy in Primary Aldosteronism: Effects on Plasma Aldosterone Concentration and Plasma Renin Activity
Bibliographic record
Abstract
In the pharmacologic treatment of primary aldosteronism (PA), titration of mineralocorticoid receptor antagonist (MRA) dosing is necessary to reverse the renin suppression caused by high aldosterone levels. However, we often encounter cases in which the plasma renin activity (PRA) does not achieve the target level, even with the maximum dose of MRA. In this setting, sacubitril/valsartan, a combination of a neprilysin inhibitor and an angiotensin II type 1 receptor blocker that is approved for use as adjunctive therapy with an MRA, has been reported to inhibit aldosterone secretion both in vitro and in vivo. If sacubitril/valsartan proves to be effective in this context, it may offer a promising treatment for PA. However, there are few reports on the use of sacubitril/valsartan in this disease. We used add-on sacubitril/valsartan in three patients with PA, in whom blood pressure was insufficiently reduced and PRA remained suppressed despite administering the maximum dose of MRA. With the addition of sacubitril/valsartan, the decrease in plasma aldosterone concentration (PAC) was more marked than the increase in PRA. Because MRAs do not suppress aldosterone production but instead act by blocking mineralocorticoid receptors, use of these agents actually promotes the renin-angiotensin system and leads to increased PAC resulting from positive feedback. The pathological significance of the phenomenon whereby PAC increases with MRA administration but decreases with the addition of sacubitril/valsartan is unclear. In PA, more effective treatment may be possible by suppressing aldosterone with sacubitril/valsartan and blocking the action of aldosterone with MRAs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".