Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease (Jan 2024)

Acute Coronary Syndrome Subphenotypes Based on Repeated Biomarker Measurements in Relation to Long‐Term Mortality Risk

  • Marie de Bakker,
  • Niels T. B. Scholte,
  • Rohit M. Oemrawsingh,
  • Victor A. Umans,
  • Bas Kietselaer,
  • Carl Schotborgh,
  • Eelko Ronner,
  • Timo Lenderink,
  • Ismail Aksoy,
  • Pim van der Harst,
  • Folkert W. Asselbergs,
  • Arthur Maas,
  • Anton J. Oude Ophuis,
  • Boudewijn Krenning,
  • Robbert J. de Winter,
  • S. Hong Kie The,
  • Alexander J. Wardeh,
  • Walter Hermans,
  • G. Etienne Cramer,
  • Ron H. van Schaik,
  • Yolanda B. de Rijke,
  • K. Martijn Akkerhuis,
  • Isabella Kardys,
  • Eric Boersma

DOI
https://doi.org/10.1161/JAHA.123.031646
Journal volume & issue
Vol. 13, no. 2

Abstract

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Background We aimed to identify patients with subphenotypes of postacute coronary syndrome (ACS) using repeated measurements of high‐sensitivity cardiac troponin T, N‐terminal pro‐B‐type natriuretic peptide, high‐sensitivity C‐reactive protein, and growth differentiation factor 15 in the year after the index admission, and to investigate their association with long‐term mortality risk. Methods and Results BIOMArCS (BIOMarker Study to Identify the Acute Risk of a Coronary Syndrome) was an observational study of patients with ACS, who underwent high‐frequency blood sampling for 1 year. Biomarkers were measured in a median of 16 repeated samples per individual. Cluster analysis was performed to identify biomarker‐based subphenotypes in 723 patients without a repeat ACS in the first year. Patients with a repeat ACS (N=36) were considered a separate cluster. Differences in all‐cause death were evaluated using accelerated failure time models (median follow‐up, 9.1 years; 141 deaths). Three biomarker‐based clusters were identified: cluster 1 showed low and stable biomarker concentrations, cluster 2 had elevated concentrations that subsequently decreased, and cluster 3 showed persistently elevated concentrations. The temporal biomarker patterns of patients in cluster 3 were similar to those with a repeat ACS during the first year. Clusters 1 and 2 had a similar and favorable long‐term mortality risk. Cluster 3 had the highest mortality risk. The adjusted survival time ratio was 0.64 (95% CI, 0.44–0.93; P=0.018) compared with cluster 1, and 0.71 (95% CI, 0.39–1.32; P=0.281) compared with patients with a repeat ACS. Conclusions Patients with subphenotypes of post‐ACS with different all‐cause mortality risks during long‐term follow‐up can be identified on the basis of repeatedly measured cardiovascular biomarkers. Patients with persistently elevated biomarkers have the worst outcomes, regardless of whether they experienced a repeat ACS in the first year.

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