High‐Probability Features of Primary Aldosteronism May Obviate the Need for Confirmatory Testing Without Increasing False‐Positive Diagnoses
Bibliographic record
Abstract
This retrospective review examined all primary aldosteronism (PA) adrenal vein sampling (AVS), diagnoses, and outcomes from an endocrine hypertension unit where confirmatory testing was abandoned in 2005 to determine the potential rate of false-positive diagnoses. Patients with outcome-verified PA (surgical patients) were compared with patients with high-probability PA (nonsurgical but high aldosterone-renin ratio, imaging abnormalities, and/or hypokalemia) or possible PA (nonsurgical, no features besides mild elevation of aldosterone-renin ratio, a potential false diagnosis of PA). Of 83 patients, 58% had unilateral PA and 42% had bilateral aldosteronism. Less than 3% of the cohort showed bilateral aldosteronism without hypokalemia or computed tomographic findings, potentially representing the false-positive PA diagnosis rate with omission of confirmatory tests in this population. In a hypertension referral unit enriched in high-probability PA cases and where high AVS success is achieved, omission of a PA confirmatory test yields a high rate of surgical diagnosis with few potential false-positive diagnoses.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".