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 < or =25 kg/m, duration of hypertension < or =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 < or =1) or high (ARS > or =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.
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 < or =25 kg/m, duration of hypertension < or =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 < or =1) or high (ARS > or =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.
Authors: Jens Waldmann; Lisa Maurer; Julia Holler; Peter H Kann; Annette Ramaswamy; Detlef K Bartsch; Peter Langer Journal: World J Surg Date: 2011-11 Impact factor: 3.352
Authors: Jin Young Kim; See Hyung Kim; Hee Jung Lee; Young Hwan Kim; Mi Jeong Kim; Seung Hyun Cho Journal: Diagn Interv Radiol Date: 2014 Jan-Feb Impact factor: 2.630
Authors: Ute I Scholl; James M Healy; Anne Thiel; Annabelle L Fonseca; Taylor C Brown; John W Kunstman; Matthew J Horne; Dimo Dietrich; Jasmin Riemer; Seher Kücükköylü; Esther N Reimer; Anna-Carinna Reis; Gerald Goh; Glen Kristiansen; Amit Mahajan; Reju Korah; Richard P Lifton; Manju L Prasad; Tobias Carling Journal: Clin Endocrinol (Oxf) Date: 2015-09-23 Impact factor: 3.478