Feasibility of Imaging-Guided Adrenalectomy in Young Patients With Primary Aldosteronism
Bibliographic record
Abstract
Many of the patients with primary aldosteronism (PA) are denied curative adrenalectomy because of limited availability or failure of adrenal vein sampling. It has been suggested that adrenal vein sampling can be omitted in young patients with a unilateral adrenal nodule, who show a florid biochemical PA phenotype. As this suggestion was based on a very low quality of evidence, we tested the applicability and accuracy of imaging, performed by computed tomography and/or magnetic resonance, for identification of unilateral PA, as determined by biochemical and/or clinical cure after unilateral adrenalectomy. Among 1625 patients with PA submitted to adrenal vein sampling in a multicenter multiethnic international study, 473 were ≤45 years of age; 231 of them had exhaustive imaging and follow-up data. Fifty-three percentage had a unilateral adrenal nodule, 43% had no nodules, and 4% bilateral nodules. Fifty-six percentage (n=131) received adrenalectomy and 128 were unambiguously diagnosed as unilateral PA. A unilateral adrenal nodule on imaging and hypokalemia were the strongest predictors of unilateral PA at regression analysis. Accordingly, imaging allowed correct identification of the responsible adrenal in 95% of the adrenalectomized patients with a unilateral nodule. The rate raised to 100% in the patients with hypokalemia, who comprised 29% of the total, but fell to 88% in those without hypokalemia. Therefore, a unilateral nodule and hypokalemia could be used to identify unilateral PA in patients ≤45 years of age if adrenal vein sampling is not easily available. However, adrenal vein sampling remains indispensable in 71% of the young patients, who showed no nodules/bilateral nodules at imaging and/or no hypokalemia. 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".