Assessing the utility of aldosterone suppression testing for primary aldosteronism: time to move forward
Bibliographic record
Abstract
Dear Editors, We are happy to respond to Pamporaki and Stowasser and colleagues. Pamporaki et al. write to advocate that the saline suppression test remains a valuable confirmatory diagnostic tool for primary aldosteronism (PA), even though guidelines no longer recommend using this procedure for this purpose1 given the lack of supportive high quality evidence and poor diagnostic accuracy.1,2 By contrast, Stowasser et al. state that the main purpose of aldosterone suppression tests (AST) is to detect patients who have unilateral PA so that other patients may be spared adrenal venous sampling (AVS). Indeed, one of the reasons we undertook our study was to evaluate whether ASTs exhibited sufficient accuracy to serve this purpose. However, when evaluating patients who had undergone both the saline suppression test and captopril challenge test, we found poor concordance between these ASTs, suboptimal diagnostic accuracy for PA, and poor discriminatory capacity to predict lateralization and surgical outcomes.3
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.038 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".