Subtype Identification of Surgically Curable Primary Aldosteronism During Treatment With Mineralocorticoid Receptor Blockade
Bibliographic record
Abstract
BACKGROUND: Current guidelines and consensus documents recommend withdrawal of mineralocorticoid receptor antagonists (MRAs) before primary aldosteronism (PA) subtyping by adrenal vein sampling (AVS), but this practice can cause severe hypokalemia and uncontrolled high blood pressure. Our aim was to investigate if unilateral PA can be identified by AVS during MRA treatment. METHODS: We compared the rate of unilateral PA identification between patients with and without MRA treatment in large data sets of patients submitted to AVS while off renin-angiotensin system blockers and β-blockers. In sensitivity analyses, the between-group differences of lateralization index values after propensity score matching and the rate of unilateral PA identification in subgroups with undetectable (≤2 mUI/L), suppressed (<8.2 mUI/L), and unsuppressed (≥8.2 mUI/L) direct renin concentration levels were also evaluated. RESULTS: Plasma aldosterone concentration, direct renin concentration, and blood pressure values were similar in non-MRA-treated (n=779) and MRA-treated (n=61) patients with PA, but the latter required more antihypertensive agents ( P =0.001) and showed a higher rate of adrenal nodules (82% versus 67%; P =0.022) and adrenalectomy (72% versus 54%; P =0.01). However, they exhibited no significant differences in commonly used AVS indices and the area under the receiving operating characteristic curve of lateralization index, both under unstimulated conditions and postcosyntropin. Several sensitivity analyses confirmed these results in propensity score matching adjusted models and in patients with undetectable, or suppressed or unsuppressed renin levels. CONCLUSIONS: At doses that controlled blood pressure and potassium levels, MRAs did not preclude the identification of unilateral PA at AVS. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01234220.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".