Adrenal vein sampling in primary aldosteronism: concordance of simultaneous vs sequential sampling
Bibliographic record
Abstract
OBJECTIVE: Many investigators believe that basal adrenal venous sampling (AVS) should be done simultaneously, whereas others opt for sequential AVS for simplicity and reduced cost. This study aimed to evaluate the concordance of sequential and simultaneous AVS methods. DESIGN AND METHODS: Between 1989 and 2015, bilateral simultaneous sets of basal AVS were obtained twice within 5 min, in 188 consecutive patients (59 women and 129 men; mean age: 53.4 years). Selectivity was defined by adrenal-to-peripheral cortisol ratio ≥2, and lateralization was defined as an adrenal aldosterone-to-cortisol ratio ≥2, the contralateral side. Sequential AVS was simulated using right sampling at -5 min (t = -5) and left sampling at 0 min (t = 0). RESULTS: There was no significant difference in mean selectivity ratio (P = 0.12 and P = 0.42 for the right and left sides respectively) and in mean lateralization ratio (P = 0.93) between t = -5 and t = 0. Kappa for selectivity between 2 simultaneous AVS was 0.71 (95% CI: 0.60-0.82), whereas it was 0.84 (95% CI: 0.76-0.92) and 0.85 (95% CI: 0.77-0.93) between sequential and simultaneous AVS at respectively -5 min and at 0 min. Kappa for lateralization between 2 simultaneous AVS was 0.84 (95% CI: 0.75-0.93), whereas it was 0.86 (95% CI: 0.78-0.94) and 0.80 (95% CI: 0.71-0.90) between sequential AVS and simultaneous AVS at respectively -5 min at 0 min. CONCLUSIONS: Concordance between simultaneous and sequential AVS was not different than that between 2 repeated simultaneous AVS in the same patient. Therefore, a better diagnostic performance is not a good argument to select the AVS method.
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 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".