TY - JOUR
T1 - Acute coronary syndrome subphenotypes based on repeated biomarker measurements in relation to long-term mortality risk
AU - De Bakker, Marie
AU - Scholte, Niels T.B.
AU - Oemrawsingh, Rohit M.
AU - Umans, Victor A.
AU - Kietselaer, Bas
AU - Schotborgh, Carl
AU - Ronner, Eelko
AU - Lenderink, Timo
AU - Aksoy, Ismail
AU - Van Der Harst, Pim
AU - Asselbergs, Folkert W.
AU - Maas, Arthur
AU - Ophuis, Anton J.Oude
AU - Krenning, Boudewijn
AU - De Winter, Robbert J.
AU - Kie The, S. Hong
AU - Wardeh, Alexander J.
AU - Hermans, Walter
AU - Cramer, G. Etienne
AU - Van Schaik, Ron H.
AU - De Rijke, Yolanda B.
AU - Akkerhuis, K. Martijn
AU - Kardys, Isabella
AU - Boersma, Eric
N1 - Publisher Copyright:
© 2024, American Heart Association Inc.. All rights reserved.
PY - 2024/1/16
Y1 - 2024/1/16
N2 - 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-f requency 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-t erm 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.
AB - 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-f requency 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-t erm 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.
KW - Acute coronary syndrome
KW - Cardiovascular biomarkers
KW - Death
KW - Phenotypes
KW - Repeated measurements
UR - https://www.scopus.com/pages/publications/85182594171
U2 - 10.1161/JAHA.123.031646
DO - 10.1161/JAHA.123.031646
M3 - Article
C2 - 38214281
AN - SCOPUS:85182594171
SN - 2047-9980
VL - 13
JO - Journal of the American Heart Association
JF - Journal of the American Heart Association
IS - 2
M1 - e031646
ER -