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Baseline 24-hour blood pressure and ascending aortic distensibility can predict blood pressure response up to 12 months post-renal denervation.
A new study shows that a noninvasive predictive model can effectively identify patients likely to benefit from renal denervation (RDN). RDN appears to be a promising intervention for decreasing blood pressure (BP) in arterial hypertension. Yet, about one-third of patients do not experience substantial reductions, highlighting the requisition for tools to predict individual treatment responses.
Paula Sagmeister and other researchers executed a secondary analysis from a prospective, single-center trial to explore the accuracy of a previously developed bivariate prediction model. The model, which uses baseline 24-hour BP and ascending aortic distensibility, was assessed for its ability to forecast 24-hour ambulatory BP outcomes up to 12 months after RDN.
The study enrolled 80 patients with resistant hypertension, with a mean age of 63 years and a baseline 24-hour systolic BP of 150 mmHg. Prior to RDN, both invasive and noninvasive markers of arterial stiffness were measured. Blood pressure was then monitored at 6 and 12 months using 24-hour ambulatory BP monitoring.
Results showed that systolic BP dropped by an average of 11 mmHg at 6 months and 7 mmHg at 12 months post-procedure (both P < 0.001). The predictive model illustrated strong accuracy at 6 months, with an R² of 0.45 and an area under the curve (AUC) of 0.82. While performance slightly dropped at 12 months, the model still maintained reasonable predictive value (R² = 0.26, AUC 0.79).
The findings suggest that this noninvasive bivariate model can serve as a valuable tool in predicting BP response after RDN, potentially guiding clinical decision-making and optimizing patient outcomes. The authors emphasized the need for additional validation in larger, multicenter studies to substantiate these results.
Journal of Hypertension
Long-term prediction of blood pressure reduction after renal denervation for arterial hypertension
Paula Sagmeister et al.
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