Prognostic impact of renal microcirculatory dysfunction in heart failure assessed by superb microvascular imaging.

The critical role of cardio-renal interactions in heart failure (HF) prognosis has gained increasing recognition, yet standardized methods for their assessment remain elusive. This study introduces a novel approach utilizing Superb Microvascular Imaging (SMI), an advanced ultrasound technique enabling detailed microvascular flow visualization, to evaluate renal microcirculation. We conducted a retrospective analysis of 78 patients who underwent renal ultrasonography with SMI between October 2020 and May 2023. Temporal changes in the Vascular Index (VI), which quantifies the blood flow signal area within the region of interest on SMI images, were measured. Key parameters included Maximum VI (Max.VI), Minimum VI (Min.VI), and the cyclic variation of VI, calculated as the intrarenal perfusion index (IRPI) = (Max.VI - Min.VI) / Max.VI within one cardiac cycle. The primary endpoint was a composite event (CE), defined as all-cause mortality or unplanned hospitalization due to worsening HF. Over a mean follow-up period of 1.6 ± 0.8 years, 13 of 78 patients (17%) experienced CEs. Patients with CEs exhibited significantly lower Max.VI and Min.VI values, while IRPI was significantly elevated in this group compared to those without CEs. Univariable Cox regression analyses revealed significant associations between Max.VI, Min.VI, and IRPI with CEs. In multivariable Cox regression analyses, Max.VI and Min.VI maintained significant associations with CEs after adjusting for creatinine, estimated central venous pressure, and intra-renal venous flow pattern. Kaplan-Meier analysis demonstrated that Max.VI (< 0.31, as determined by ROC analysis; 43% vs. 7%, log-rank p < 0.001), Min.VI (< 0.08, 42% vs. 8%, log-rank p < 0.001), and IRPI (> 0.70, 39% vs. 10%, log-rank p = 0.002) could effectively stratify CE prognosis. This novel application of SMI for renal circulation assessment provides valuable insights into HF prognosis and enables risk stratification beyond conventional markers.