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Erschienen in: Journal of Cardiovascular Translational Research 1/2018

08.01.2018 | Original Article

Trajectories of Circulating Monocyte Subsets After ST-Elevation Myocardial Infarction During Hospitalization: Latent Class Growth Modeling for High-Risk Patient Identification

verfasst von: Shan Zeng, Li-Fang Yan, Yan-Wei Luo, Xin-Lin Liu, Jun-Xiang Liu, Zhao-Zeng Guo, Zhong-Wei Xu, Yu-Ming Li, Wen-Jie Ji, Xin Zhou

Erschienen in: Journal of Cardiovascular Translational Research | Ausgabe 1/2018

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Abstract

It remains unclear if the developmental trajectories of a specific inflammatory biomarker during the acute phase of ST-elevation myocardial infarction (STEMI) provide outcome prediction. By applying latent class growth modeling (LCGM), we identified three distinctive trajectories of CD14++CD16+ monocytes using serial flow cytometry assays from day 1 to day 7 of symptom onset in 96 de novo STEMI patients underwent primary percutaneous coronary intervention. Membership in the high-hump-shaped trajectory (16.8%) independently predicted adverse cardiovascular outcomes during a median follow-up of 2.5 years. Moreover, inclusion of CD14++CD16+ monocyte trajectories significantly improved area under the curve (AUC) when added to left ventricular ejection fraction-based prediction model (ΔAUC = 0.093, P = 0.013). Therefore, CD14++CD16+ monocyte trajectories during STEMI hospitalization are a novel risk factor for post-STEMI adverse outcomes. These results provide the first proof-of-principle evidence in support of the risk stratification role of LCGM-based longitudinal modeling of specific inflammatory markers during acute STEMI.
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Metadaten
Titel
Trajectories of Circulating Monocyte Subsets After ST-Elevation Myocardial Infarction During Hospitalization: Latent Class Growth Modeling for High-Risk Patient Identification
verfasst von
Shan Zeng
Li-Fang Yan
Yan-Wei Luo
Xin-Lin Liu
Jun-Xiang Liu
Zhao-Zeng Guo
Zhong-Wei Xu
Yu-Ming Li
Wen-Jie Ji
Xin Zhou
Publikationsdatum
08.01.2018
Verlag
Springer US
Erschienen in
Journal of Cardiovascular Translational Research / Ausgabe 1/2018
Print ISSN: 1937-5387
Elektronische ISSN: 1937-5395
DOI
https://doi.org/10.1007/s12265-017-9782-9

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