Apparent failed and discordant adrenal vein sampling: A potential confounding role of cortisol cosecretion?
Bibliographic record
Abstract
OBJECTIVE: Adrenal vein sampling (AVS) and computed tomography (CT) often show confusingly discordant lateralisation results in primary aldosteronism (PA). We tested a biochemical algorithm using AVS data to detect cortisol cosecretion as a potential explanation for discordant cases. DESIGN: Retrospective analysis from a large PA + AVS database. PATIENTS: All patients with PA and AVS, 2005-2020. MEASUREMENTS: An algorithm using biochemical data from paired AVS + CT images was devised from physiological first principles and informed by data from unilateral, AVS-CT concordant patients. The algorithm involved calculations based upon the expectation that low cortisol levels exist in adrenal vein effluent opposite an aldosterone-and-cortisol-producing adrenal mass and may reverse lateralisation due to inflated aldosterone/cortisol ratios. MAIN OUTCOMES: The algorithm was applied to cases with discordant CT-AVS lateralisation to determine whether this might be a common or explanatory finding. Clinical and biochemical characteristics of identified cases were collected via chart review and compared to CT-AVS concordant cases to detect evidence of biological plausibility for cortisol cosecretion. RESULTS: From a total of 588 AVS cases, 141 AVS + CT pairs were clear unilateral PA cases, used to develop the three-step algorithm for AVS interpretation. Applied to 88 AVS + CT discordant pairs, the algorithm suggested possible cortisol cosecretion in 40%. Case review showed that the proposed cortisol cosecretors, as identified by the algorithm, had low/suppressed adrenocorticotropic hormone levels, larger average nodule size and lower plasma aldosterone. CONCLUSIONS: Pending external validation and outcome verification by surgery and tissue immunohistochemistry, cortisol cosecretion from aldosteronomas may be a common explanation for discordant CT-AVS results in 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 | 0.000 | 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 | 0.000 |
| 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".