Significance of adrenal computed tomography in predicting laterality and indicating adrenal vein sampling in primary aldosteronism

K. Kamemura, N. Wada, T. Ichijo, Y. Matsuda, Y. Fujii, T. Kai, T. Fukuoka, R. Sakamoto, A. Ogo, T. Suzuki, H. Umakoshi, M. Tsuiki, M. Naruse

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25 Citations (Scopus)


Although laterality assessed by computed tomography (CT) in primary aldosteronism (PA) is not always concordant with that assessed by adrenal vein sampling (AVS), it is unclear whether all patients diagnosed with PA should undergo AVS for subtype classification. The aim of the current study was to investigate the accuracy of CT in subtype classification and to develop a prediction score for bilateral subtype in patients without adrenal tumour. As part of the WAVES-J study, 393 patients with PA were analysed. Subtyping using CT was concordant with that using AVS in 68% (269/393) of patients in the total sample, and in 38% (68/156) of patients with unilateral tumours, 56% (5/9) of patients with bilateral tumours and 89% (204/228) of patients without tumour. In patients without tumour, female gender, plasma aldosterone concentration (pg ml-1) to plasma renin activity ratio ≤550 and serum potassium ≥3.8 mEq l-1 were shown to be independent predictors for bilateral subtype. A prediction score based on these three variables was constructed with one point attributed to each variable. A score of three points had 29% sensitivity and 96% specificity in a receiver operating characteristic curve analysis. The results suggest that although CT is not sufficiently accurate for subtype classification in patients with adrenal tumours, it is sufficient to determine bilateral subtype in patients without tumour. Moreover, using our clinical prediction score in patients without tumour could be useful in determining the necessity of AVS for subtype classification.

Original languageEnglish
Pages (from-to)195-199
Number of pages5
JournalJournal of human hypertension
Issue number3
Publication statusPublished - Mar 1 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Internal Medicine


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