Validation of the Aldosteronoma Resolution Score Within Current Clinical Practice
Bibliographic record
Abstract
Abstract Introduction Complete resolution of hypertension after adrenalectomy for primary aldosteronism is far from a certainty. This stresses the importance of adequate preoperative patient counseling. The aldosteronoma resolution score (ARS) is a simple and easy to use prediction model only including four variables: ≤ 2 antihypertensive medications, body mass index ≤ 25 kg/m 2 , duration of hypertension ≤ 6 years and female sex. However, because the model was developed and validated within the USA over a decade ago, the applicability in modern practice and outside of the USA is questionable. Therefore, we aimed to validate the ARS in current clinical practice within an international cohort. Materials and method Patients who underwent unilateral adrenalectomy, between 2010 and 2016, in 16 medical centers from the USA, Europe (EU), Canada (CA) and Australia (AU) were included. Resolution of hypertension was defined as normotension without antihypertensive medications. Results In total, 514 patients underwent adrenalectomy and 435 (85%) patients were eligible. Resolution of hypertension was achieved in 27% patients within the total cohort and in 22%, 30%, 40% and 38% of patients within USA, EU, CA and AU, respectively ( p = 0.015). The area under the curve (AUC) for the complete cohort was 0.751. Geographic validation displayed a AUC within the USA, EU, CA and AU of 0.782, 0.681, 0.811 and 0.667, respectively. Discussion The ARS is an easy to use prediction model with a moderate to good predictive performance within current clinical practice. The model showed the highest predictive performance within North America but potentially has less predictive performance in EU and AU.
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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 | 0.002 | 0.001 |
| 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".