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Record W1971153308 · doi:10.1097/sla.0b013e318165c075

The Aldosteronoma Resolution Score

2008· article· en· W1971153308 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of Surgery · 2008
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsInstitute of Nutrition, Metabolism and Diabetes
FundersUniversity of California, San Francisco
KeywordsMedicinePrimary aldosteronismAdrenalectomyBlood pressureLogistic regressionSecondary hypertensionBody mass indexAldosteroneInternal medicineEssential hypertensionResistant hypertension

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.114

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.458
GPT teacher head0.350
Teacher spread0.108 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it