Abstract 12747: Protein Profiling for Survival Outcome Prediction in Out-of-Hospital Cardiac Arrest Patients
Introduction: Outcome prediction is still a challenge for out-of-hospital cardiac arrest (OHCA) patients in early post-cardiac arrest period. Changes of protein expression after cardiac arrest and resuscitation could be biomarkers for outcomes prediction. Single biomarker can not reach adequate power to predict outcome due to the complexity of pathophysiological cascades in post-cardiac arrest period. Protein profiling can measure multiple biomarkers at a time point and can provide better information for outcome prediction.
Hypothesis: Identify the association of survival to discharge outcome and biomarkers changes by protein profiling in cardiac arrest patients
Methods: Total 99 adult non-traumatic OHCA patients with sustained ROSC were enrolled for the study. There were 45 patients survival to hospital discharge. Blood were sampled at 24 hours after cardiac arrest. Protein profiling for 21 different biomarkers, which included brain, heart, inflammatory reactions, oxidative stress and coagulation markers, was measured by suspension microarray assay. Clustering analyses were carried out using Multi-Experiment Viewer (MeV v4.8.1).
Results: Heat maps were generated to visualize the Log2 values relative to median values of overall patient sample pool. Based on the performed statistical analysis to narrow down the biomarker panel, we investigated samples respectively by employing only the significant parameters for the Hierarchical Clustering (HCL) analysis. Nine candidate biomarkers (IL-6, IL-8, IL-10, MCP-1, MDA-LDL, Cystatin C, PAI-1, NT-Pro-BNP and S100B) identified respectively from samples pools were applied. The discrimination based on the selected parameters was 76.3% to be accurately clustered in HCL analysis. When adding these biomarkers into clinical variables (age, sex, Apache II, hypothermia, shockable rhythm, CPR duration), receiver-operating characteristic curve analysis showed high prediction power for survival to discharge (area under curve = 0.9378, p<0.01)
Conclusion: Protein profiling with suspension microarray can demonstrate the pattern of biomarkers in various pathophysiological changes after cardiac arrest. It has the potential to help predicting the outcome in OHCA patients.
Author Disclosures: C. Huang: None. M. Tsai: None. W. Chang: None. H. Hsu: None. W. Chen: None.
- © 2014 by American Heart Association, Inc.