The Predictive Value of Serum Aldosterone Level for Coronary Artery Calcium Score in Patients with Chronic Kidney Disease: A Single-center Study

Viktor V. Semenov, Jizzo R. Bosdriesz, Olexandr Kuryata

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Patients with chronic kidney disease (CKD) have high cardiovascular risk (CVR), which is often underestimated by conventional tools. The coronary artery calcium score (CACS) significantly improves CVR stratification by conventional tools, but it is often not available in low-resources settings. Aldosterone may be a cheaper alternative to CACS for CVR assessment in CKD patients. The aim was to assess the ability of serum aldosterone level to predict CACS in patients with CKD in comparison to standard predictors. This single-center study included 57 patients aged 40 to 67 years with CKD (estimated glomerular filtration rate [eGFR] ≥45 ml/min) and arterial hypertension. Serum aldosterone, sex, age, body mass index, blood pressure, total cholesterol, eGFR, and proteinuria were used for prediction of CACS>0 Agatston units (AU) and CACS>100 AU. The area under the curve (AUC) with 95% confidence intervals (CI) and the mean Brier scores were examined for predictors of CACS. Aldosterone predicted a CACS>100 AU (AUC = 0.72, 95% CI: 0.56-0.88), but not a CACS>0 AU. Age predicted a CACS>100 AU (AUC = 0.80, 95% CI: 0.67-0.93) and a CACS>0 AU (AUC = 0.75, 95% CI: 0.62-0.89). The addition of aldosterone to age for prediction of a CACS>100 AU improved the mean Brier score, compared to the model with age alone, from 0.16 to 0.14, but not the AUC (0.83, 95% CI: 0.70-0.95). Aldosterone was a significant predictor of a CACS>100 AU in patients with CKD, but aldosterone was not a better predictor than age alone.

Original languageEnglish
Pages (from-to)242-254
Number of pages13
JournalPrague medical report
Volume124
Issue number3
DOIs
Publication statusPublished - 2023

Keywords

  • Aldosterone
  • Chronic kidney disease
  • Coronary artery calcium score
  • Prediction

Cite this