The Aldosteronoma Resolution Score
Bibliographic record
Abstract
In Brief Objective: To develop a prediction model using information readily available, at clinical presentation, which could determine whether patients with aldosterone-producing adenomas would have complete resolution of hypertension after adrenalectomy. Background: Primary aldosteronism is the most common curable cause of secondary hypertension. However, a large number of patients continue to require antihypertensive medications to control their blood pressure. Differentiating patients that will have complete resolution of hypertension without the need for antihypertensive medications from patients that will require continued use of antihypertensive medications is difficult before adrenalectomy. Methods: The predictive logistic regression model was derived using data on 100 patients who underwent adrenalectomy for primary aldosteronism at one tertiary medical center and was externally validated using an independent series of 67 patients from another center. Results: Clinical features were similar for patients in the derivation and validation groups. Four readily available predictors (2 or fewer antihypertensive medications, body mass index ≤25 kg/m2, duration of hypertension ≤6 years, and female sex) yielded the best predictive model for complete resolution of hypertension after adrenalectomy. Based on the resulting 4-item aldosteronoma resolution score (ARS), 3 likelihood levels for complete resolution were identified: low (0–1), medium (2–3), and high (4–5) with a predictive accuracy of 27%, 46%, and 75%, respectively. Conclusion: The ARS accurately identifies individuals at low (ARS ≤1) or high (ARS ≥4) likelihood of complete resolution of hypertension without further need of lifelong antihypertensive medications after adrenalectomy for aldosteronoma. This scoring system can help clinicians objectively inform patients of likely clinical outcomes before surgical intervention. A predictive 4-item logistic regression model using readily available clinical features was derived and externally validated for complete resolution of hypertension after adrenalectomy for aldosterone-producing adenoma. Based on the resulting aldosteronoma resolution score (ARS), 3 likelihood levels for complete resolution were identified: low, medium, and high with a predictive accuracy of 27%, 46%, and 75%, respectively.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".