The Prognostic Role of C-Reactive Protein Velocity in Patients with First Acute Myocardial Infarction

<b>Background/Objectives</b>: Inflammation plays a key role in the pathophysiology of acute myocardial infarction (AMI). Yet static measures of C-reactive protein (CRP) provide limited prognostic information. CRP velocity (CRPv), which reflects the rate of CRP rise within the first 24 h, may better depict the dynamic inflammatory response. To investigate the prognostic role of CRPv in patients presenting with a first AMI. <b>Methods</b>: Consecutive patients presenting with first AMI were enrolled. CRPv was calculated as the difference between CRP at admission and after 24 ± 8 h, divided by time. A prognostic CRPv cut-off was derived from spline curve analysis to dichotomize the population. Patients were followed up for the primary composite endpoint of cardiovascular death, non-fatal AMI, and hospitalization for heart failure. <b>Results</b>: Among 604 patients, 189 (31.3%) had CRPv ≥ 1.36 mg/L/h and 415 (68.7%) had CRPv < 1.36 mg/L/h. Higher hs-cTnT (adjusted odds ratio [aOR] 2.552, 95% CI, 1.520-4.286; <i>p</i> < 0.001) and NT-proBNP (aOR 2.229, 95% CI, 1.241-4.002; <i>p</i> = 0.007) were independently associated with CRPv ≥ 1.36 mg/L/h. At a median follow-up of 13.8 months, 115 patients (19.0%) reached the primary composite endpoint. High CRPv patients had significantly lower event-free survival rate than low CRPv patients (66.7% vs. 85.5%, log-rank <i>p</i> < 0.001). CRPv independently predicted the primary composite endpoint [adjusted hazard ratio 1.226, 95% CI 1.102-1.364, <i>p</i> < 0.001]. Adding CRPv on top of clinical, echocardiographic, and biochemical risk factors significantly improved model discrimination (<i>p</i> < 0.001), whereas single CRP on admission (<i>p</i> = 0.947) or CRP 24 ± 8 h from admission (<i>p</i> = 0.064) did not. <b>Conclusions</b>: CRPv appears to be a robust predictor of adverse outcomes in first AMI patients, offering incremental prognostic value beyond established clinical and biomarker indices. Its feasibility and low cost support its integration into early clinical risk stratification.