Cardiometabolic Biomarkers and Their Temporal Patterns Predict Poor Outcome in Chronic Heart Failure (Bio-SHiFT

Milos Brankovic1,2, K Martijn Akkerhuis1, Henk Mouthaan3

  • 1Department of Cardiology, Erasmus Medical Center, Rotterdam, Netherlands.

Insights

Temporal patterns of four cardiometabolic biomarkers, including Insulin-like Growth Factor Binding Proteins (IGFBP-1, IGFBP-2, IGFBP-7) and adipose fatty acid binding protein 4 (FABP-4), predict adverse clinical events in chronic heart failure patients.

Area of Science:

  • Cardiology
  • Endocrinology
  • Metabolic Syndrome

Background:

  • Chronic heart failure (CHF) involves complex hormonal and metabolic changes.
  • Monitoring these changes during clinically silent CHF progression is difficult.

Purpose of the Study:

  • To investigate if temporal patterns of six emerging cardiometabolic biomarkers predict future adverse clinical events in stable CHF patients.

Main Methods:

  • 263 CHF patients were followed for 2.2 years.
  • Risk assessed for composite endpoint (HF hospitalization, cardiac death, LVAD, transplant).
  • Serial measurements of IGFBP-1, IGFBP-2, IGFBP-7, FABP-4, resistin, and chemerin.

Main Results:

  • IGFBP-1, IGFBP-2, IGFBP-7, and FABP-4 levels predicted adverse events.
  • Biomarker slopes (rate of change) were also strong predictors, independent of baseline levels.
  • Associations remained significant after multivariable adjustment.

Conclusions:

  • Temporal patterns of IGFBP-1, IGFBP-2, IGFBP-7, and FABP-4 predict adverse outcomes in CHF outpatients.
  • These biomarkers may help identify aggressive CHF forms and guide therapy.
Abstract

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