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

Author:

de Bakker Marie1ORCID,Scholte Niels T. B.1ORCID,Oemrawsingh Rohit M.2ORCID,Umans Victor A.3ORCID,Kietselaer Bas4ORCID,Schotborgh Carl5ORCID,Ronner Eelko6ORCID,Lenderink Timo7ORCID,Aksoy Ismail8ORCID,van der Harst Pim9ORCID,Asselbergs Folkert W.1011ORCID,Maas Arthur12ORCID,Oude Ophuis Anton J.13,Krenning Boudewijn114,de Winter Robbert J.10ORCID,The S. Hong Kie15,Wardeh Alexander J.16ORCID,Hermans Walter17,Cramer G. Etienne18ORCID,van Schaik Ron H.19ORCID,de Rijke Yolanda B.19ORCID,Akkerhuis K. Martijn1,Kardys Isabella1ORCID,Boersma Eric1ORCID,Akkerhuis K Martijn,de Bakker Marie,Boersma Eric,Kardys Isabella,de Rijke Yolanda B.,van Schaik Ron H.,Scholte Niels T.B.,Aksoy Ismail,Asselbergs Folkert W,Cramer G Etienne,van der Harst Pim,Hermans Walter,The S Hong Kie,Kietselaer Bas,Krenning Boudewijn,Gasthuis Franciscus,Lenderink Timo,Maas Arthur,Oemrawsingh Rohit M.,Oude Ophuis Anton J.,Ronner Eelko,Schotborgh Carl,Umans Victor A.,Wardeh Alexander J.,de Winter Robbert J.

Affiliation:

1. Department of Cardiology Erasmus MC, University Medical Center Rotterdam Rotterdam The Netherlands

2. Department of Cardiology Albert Schweitzer Ziekenhuis Dordrecht The Netherlands

3. Department of Cardiology Noordwest Ziekenhuisgroep Alkmaar The Netherlands

4. Department of Cardiology Mayo Clinic Rochester MN USA

5. Department of Cardiology HagaZiekenhuis Den Haag The Netherlands

6. Department of Cardiology Reinier de Graaf Hospital Delft The Netherlands

7. Department of Cardiology Zuyderland Hospital Heerlen The Netherlands

8. Department of Cardiology Admiraal de Ruyter Hospital Goes The Netherlands

9. Department of Cardiology University Medical Center Utrecht Utrecht The Netherlands

10. Amsterdam University Medical Centers, Department of Cardiology University of Amsterdam Amsterdam The Netherlands

11. Health Data Research UK and Institute of Health Informatics University College London London United Kingdom

12. Department of Cardiology Gelre Hospital Zutphen The Netherlands

13. Department of Cardiology Canisius‐Wilhelmina Hospital Nijmegen The Netherlands

14. Department of Cardiology Franciscus Gasthuis & Vlietland Rotterdam The Netherlands

15. Department of Cardiology Treant Zorggroep Emmen The Netherlands

16. Department of Cardiology Haaglanden Medisch Centrum Den Haag The Netherlands

17. Department of Cardiology Elizabeth‐Tweesteden Hospital Tilburg The Netherlands

18. Department of Cardiology Radboud University Medical Center Nijmegen Nijmegen The Netherlands

19. Department of Clinical Chemistry Erasmus MC, University Medical Center Rotterdam Rotterdam The Netherlands

Abstract

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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