Abstract

Iron deficiency has been extensively researched and is associated with adverse outcomes in heart failure. However, to our knowledge, the temporal evolution of iron status has not been previously investigated in patients with acute coronary syndrome (ACS). Therefore, we aimed to explore the temporal pattern of repeatedly measured iron, ferritin, transferrin, and transferrin saturation (TSAT) in relation to prognosis post-ACS. BIOMArCS (BIOMarker study to identify the Acute risk of a Coronary Syndrome) is a prospective, multicenter, observational cohort study conducted in The Netherlands between 2008 and 2015. A total of 844 patients with post-ACS were enrolled and underwent high-frequency (median 17) blood sampling during 1year follow-up. Biomarkers of iron status were measured batchwise in a central laboratory. We analyzed 3 patient subsets, including the case-cohort (n=187). The primary endpoint (PE) was a composite of cardiovascular mortality and repeat nonfatal ACS, including unstable angina pectoris requiring revascularization. The association between iron status and the PE was analyzed using multivariable joint models. Mean age was 63years; 78% were men, and >50% had iron deficiency at first sample in the case-cohort. After adjustment for a broad range of clinical variables, 1 SD decrease in log-iron was associated with a 2.2-fold greater risk of the PE (hazard ratio 2.19, 95% confidence interval 1.34 to 3.54, p=0.002). Similarly, 1 SD decrease in log-TSAT was associated with a 78% increased risk of the PE (hazard ratio 1.78, 95% confidence interval 1.17 to 2.65, p=0.006). Ferritin and transferrin were not associated with the PE. Repeated measurements of iron and TSAT predict risk of adverse outcomes in patients with post-ACS during 1year follow-up. Trial Registration: The Netherlands Trial Register. Unique identifiers: NTR1698 and NTR1106. Registered at https://www.trialregister.nl/trial/1614 and https://www.trialregister.nl/trial/1073.

Highlights

  • Iron metabolism is important to maintain biologic function, and disbalance can lead to, for example, iron deficiency (ID).[1]

  • We applied a joint model approach to investigate if the temporal pattern of iron status based on repeatedly measured biomarkers included iron, ferritin, and transferrin, which were measured in serum using the quantitative sandwich electrochemiluminescence immunoassay ECLIA (Roche Diagnostics, Mannheim, Germany) on a Cobas immunoassay analyzer

  • * Per 1 standard deviation decrease of the log-transformed biomarker level. y Unadjusted. z Adjusted for Global Registry of Acute Coronary Events risk score and gender. x Adjusted for Global Registry of Acute Coronary Events risk score, gender, body mass index, smoking status, diabetes, hypercholesterolemia, coronary artery bypass graft, valvular heart disease, stroke, peripheral vascular disease, statin use, vitamin K antagonist use and repeatedly measured log-transformed estimated glomerular filtration rate. In this analysis of patients with post-acute coronary syndrome (ACS) from the BIOMArCS study, we show that repeated measurements of decreased iron and transferrin saturation (TSAT) levels, in contrast to ferritin and transferrin, are associated with an increased risk for the composite primary endpoint (PE) of CV mortality and repeat nonfatal ACS including unstable angina pectoris (UAP) requiring urgent coronary revascularization during 1-year follow-up

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Summary

Introduction

Iron metabolism is important to maintain biologic function, and disbalance can lead to, for example, iron deficiency (ID).[1]. The American Journal of Cardiology (www.ajconline.org) analysis, comprising a total of 7 studies on 2,821 participants with acute coronary syndrome (ACS), showed that patients with baseline ID may have worse prognosis.[10] these previous studies have an important caveat because baseline ID is a binary snapshot of iron status that fails to capture the dynamic process of iron homeostasis and disease progression. Transferrin saturation (TSAT) was calculated in the context of this analysis using the formula:[13]

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