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.
Keywords: Biomarker; Cardiovascular outcomes; Inflammation; Latent class growth modeling; Monocyte subsets; ST-elevation myocardial infarction.