Identification of Surgically Curable Primary Aldosteronism by Imaging in a Large, Multiethnic International Study
Bibliographic record
Abstract
CONTEXT: Adrenal gland imaging is recommended by the current guidelines for the workup of primary aldosteronism (PA). However, its diagnostic performance has not been established in large, multiethnic cohorts of patients who undergo adrenal vein sampling (AVS) and adrenalectomy. OBJECTIVE: This work aims to assess the diagnostic accuracy of cross-sectional adrenal imaging. METHODS: This international multicenter study took place in tertiary referral centers. A total of 1625 PA patients seeking surgical cure were enrolled in an international study involving 19 centers in North America, Europe, Asia, and Australia. Of these, 1311 (81%) had imaging data available and 369 (23%), who received a final diagnosis of surgically cured unilateral PA, were examined. Patients underwent AVS and imaging by computed tomography and/or magnetic resonance imaging. The accuracy of detection of unilateral PA at imaging was estimated by the area under the receiver operator characteristics curve using cure (biochemical and/or full clinical success) as the reference at follow-up after unilateral adrenalectomy. RESULTS: In the cohort of 1311 patients with imaging data available, 34% and 7% of cases showed no detectable or bilateral nodules, respectively. Imaging did not detect the culprit adrenal in 28% of the surgically cured unilateral PA patients. Moreover, the clinical outcome did not differ significantly between the imaging-positive and imaging-negative patients. CONCLUSION: Cross-sectional imaging did not identify a lateralized cause of disease in around 40% of PA patients and failed to identify the culprit adrenal in more than one-fourth of patients with unilateral PA.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".