Using vascular biomarkers to assess heart failure event risk in hospitalized patients with and without AKI

Audrey A Shi1, Anna Simone Andrawis1, Aditya Biswas1

  • 1Department of Internal Medicine, Section of Nephrology, Yale School of Medicine, New Haven, CT, USA.

BMC Nephrology
|June 2, 2025
PubMed

Insights

Nine vascular biomarkers can identify distinct patient phenotypes, improving prediction of heart failure (HF) risk after hospitalization, particularly for those with acute kidney injury (AKI). These markers enhance risk stratification beyond standard clinical factors.

Area of Science:

  • Cardiovascular Medicine
  • Nephrology
  • Biomarker Discovery

Background:

  • Patients with acute kidney injury (AKI) face elevated risks of heart failure (HF).
  • Identifying reliable predictors of post-hospitalization HF is crucial, especially for AKI survivors.
  • Existing clinical variables may not fully capture HF risk in this population.

Purpose of the Study:

  • To investigate the predictive value of nine vascular biomarkers for future HF events.
  • To determine if these biomarkers can stratify risk in hospitalized patients, including those with AKI.
  • To assess if biomarkers improve HF prediction when combined with clinical data.

Main Methods:

  • Unsupervised spectral clustering of 9 plasma biomarkers (angiopoietin-1, angpt-2, VEGF-A, VEGF-C, VEGF-d, VEGFR1, sTie-2, PlGF, bFGF) in 1,497 patients (half with AKI) at 3 months post-hospitalization.
  • Cox regression analysis to associate biomarker-derived clusters (Vascular Injury, Vascular Repair, Dormant Phenotypes) with HF events.
  • Area Under the Curve (AUC) and net reclassification index calculations to evaluate biomarker addition to a clinical prediction model for HF or death at 3 years.

Main Results:

  • Three distinct phenotypes were identified: Vascular Injury, Vascular Repair, and Dormant.
  • The Vascular Injury Phenotype showed a twofold higher risk of HF events compared to the Repair Phenotype, in both AKI and non-AKI patients.
  • The combined biomarker and clinical model demonstrated superior prediction of HF or death (AUC 0.80) compared to the clinical model alone (AUC 0.77), significantly improving reclassification.

Conclusions:

  • Vascular biomarkers effectively define patient phenotypes.
  • These phenotypes stratify risk for future heart failure events in recently hospitalized individuals.
  • Biomarker incorporation enhances the prediction of HF risk post-hospitalization, especially in AKI patients.
Abstract

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