Subclinical Primary Aldosteronism and eGFR Decline
Bibliographic record
Abstract
Background: Primary aldosteronism (PA), characterized by renin-independent aldosterone secretion, is the most common and modifiable form of secondary hypertension. Overt PA predisposes to disproportionately high rates of cardiovascular and kidney disease, independent of blood pressure (BP). Growing evidence suggests that milder forms of renin-independent aldosteronism (ie, Subclinical PA) are highly prevalent yet their clinical significance remains uncertain. Methods: Prospective study of 536 participants aged 40-69 yr and on no BP medications from the randomly sampled, population-based CARTaGENE cohort (Canada). Using aldosterone and renin levels from enrollment, we employed multivariable linear regression models to measure the association between the aldosterone-renin ratio (ARR) and eGFR (via the 2021 CKD-EPICr/CysC equation) measured at enrollment and after 5-7 years of follow-up. Results: The mean (SD) age, eGFR, and systolic BP were 55 (7) years, 107 (13) mL/min/1.73m2, and 132 (11) mmHg, respectively. Higher ARR was successively associated with steeper annual eGFR decline with ARR Tertile 3 having a 74% steeper decline than ARR Tertile 1 (1.18 vs. 0.68 mL/min/1.73m2/yr, P=0.01; Fig. 1). On multivariable linear regression, higher ARR was associated with steeper annual eGFR decline (P=0.03; Fig. 2). Conclusions: In a randomly sampled, population-based cohort of individuals on no antihypertensive medication, Subclinical PA was associated with steeper eGFR decline, independent of BP. Subclinical PA may serve as a potentially modifiable risk factor to prevent or slow CKD.FIGURE 1: ANNUAL EGFR DECLINE BY ARR TERTILEFIGURE 2: ARR AND eGFR ASSOCIATIONS
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".