DOI: 10.5937/jomb0-64892 ISSN: 1452-8258

Serum cytokine panel predicts cardiac outcomes following acute myocardial infarction

Sichao Tai

Background: Individual cytokines have been implicated in the pathogenesis of acute myocardial infarction (AMI). However, the predictive utility of a comprehensive serum cytokine panel for post-infarction outcomes remains underexplored. Methods: We conducted a prospective cohort study of 184 patients presenting with ST-segment elevation myocardial infarction (STEMI). Blood samples were collected within 24 hours of primary percutaneous coronary intervention (PCI). We analysed a panel of 11 cytokines (GDF-15, IL-1<span style="color: rgb(32, 33, 34); font-family: sans-serif; font-size: 16px; background-color: rgb(248, 249, 250);">β</span>, IL-6, IL-8, IL-10, IFN-<span style="color: rgb(32, 33, 34); font-family: sans-serif; font-size: 16px; background-color: rgb(248, 249, 250);">γ</span>, VEGF, G-CSF, GM-CSF, TGF-<span style="color: rgb(32, 33, 34); font-family: sans-serif; font-size: 16px; background-color: rgb(248, 249, 250);">β</span>, and hs-cTnT) using a multiplex bead-based immunoassay. The primary endpoint was the occurrence of Major Adverse Cardiac Events (MACE) at 12 months. MACE was defined as cardiovascular death, recurrent MI, or heart failure hospitalisation. Results: Elevated levels of IL-6, IL-8, GDF-15, and hs-cTnT were significantly associated with 12-month MACE. Multivariable logistic regression identified GDF-15 (OR 3.58, 95% CI 1.82-7.04, p&lt;0.001) and hs-cTnT (OR 2.94, 95% CI 1.53-5.65, p=0.001) as independent predictors. In univariable analysis, IL-6, IL-8, GDF-15, and hs-cTnT were elevated. Still, only GDF-15 and hs-cTnT retained independent prognostic significance in the multivariable model. A composite biomarker score showed an AUC of 0.86 (95% CI 0.80-0.92) for predicting MACE. Conclusion: A serum biomarker profile including GDF-15 and hs-cTnT may improve early risk assessment after primary PCI in STEMI, supporting routine biomarker profiling to enhance risk stratification beyond traditional variables.

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