Serum C-Reactive Protein and IL-6 Levels as Predictors of Disease Severity in Patients with Acute Myocardial Infarction

Background: Inflammation during acute myocardial infarction (AMI) critically influences infarct size, ventricular remodeling, and subsequent clinical outcomes. Systemic inflammatory markers particularly interleukin-6 (IL-6) and high-sensitivity C-reactive protein (hs-CRP) are well established. However, their utility for forecasting early risk and disease severity in South Asian AMI patients remains unclear. Objectives: To determine whether admission levels of hs-CRP and IL-6 individually predict AMI severity and whether a combined biomarker approach offers superior discrimination of high-risk clinical profiles. Methods: From January to December 2023, we conducted a prospective observational study enrolling 150 patients aged 30–80 years who presented within 24 hours of symptom onset to two tertiary care centers in Lahore, Pakistan. Blood samples were obtained before reperfusion therapy to measure hs-CRP (immunoturbidimetric assay) and IL-6 (high-sensitivity ELISA). Severe AMI was defined as Killip class ≥ II, left ventricular ejection fraction < 40%, or GRACE score ≥ 156. Multivariable logistic regression identified independent predictors, and receiver operating characteristic (ROC) analyses determined optimal cut-offs and diagnostic accuracy. Results: Of 150 patients, 58 (38.7%) met criteria for severe AMI. Severe cases had significantly higher median hs-CRP (14.8 mg/L vs 7.9 mg/L) and IL-6 (30.6 pg/mL vs 17.4 pg/mL) than non-severe cases (both p < 0.001). After adjustment, hs-CRP ≥ 10 mg/L (OR 3.12) and IL-6 ≥ 25 pg/mL (OR 4.28) independently predicted severity. The AUC was 0.82 for hs-CRP, 0.86 for IL-6, and 0.90 for the combined model, with sensitivity and specificity both >84%. Conclusion: Elevated admission hs-CRP and IL-6 levels are independent, complementary predictors of AMI severity. A dual-marker model substantially improves early risk stratification and may support targeted monitoring and treatment in resource-limited settings.