Noninvasive model predicts BP decrease post-RDN for arterial hypertension

The use of a noninvasive bivariate model can accurately predict blood pressure (BP) response at 6 and 12 months after renal denervation (RDN) in patients with resistant hypertension, a study has shown.

The authors carried out a predefined secondary analysis from a prospective single-centre trial among patients with resistant hypertension undergoing ultrasound-based RDN. They assessed both invasive and noninvasive arterial stiffness markers prior to the procedure and evaluated BP response at 6 and 12 months via 24-h ambulatory BP monitoring.

Furthermore, the authors assessed model performance using linear regression to predict 24-h ambulatory BP change and receiver operating curve analyses to determine the accuracy for a binary systolic ambulatory BP reduction of >5 mm Hg.

Eighty-patients (mean age 63 years, baseline 24-h systolic BP [SBP] 150 mm Hg) participated in this study. SBP decreased by 11 mm Hg at 6 months and by 7 mm Hg at 12 months (p<0.001 for both).

Notably, the prediction model delivered high accuracy in its predictions at 6 months (r2=0.45; area under the curve [AUC], 0.82; p<0.001). However, this decreased at 12 months (r2=0.26; AUC, 0.79; p<0.001).

“These findings may enhance patient selection and shared decision-making, warranting further validation in larger studies,” the authors said. 

"RDN has emerged as a potential therapy for lowering BP in patients with arterial hypertension,” but nearly one-third do not show significant BP reductions, which highlights the need for reliable predictors of treatment response, according to the authors.