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STEMI, Cardiogenic Shock, and Mortality in Patients Admitted for Acute Angiography: Associations and Predictions from
Birgit Debrabant1, Ulrich Halekoh1, Mette Soerensen1,2,3
1Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense C, Denmark.
Insights
This study identified novel protein biomarkers for predicting acute myocardial infarction (AMI) and cardiogenic shock (CS). These protein sets significantly improved prediction accuracy, offering potential for clinical application in diagnosing STEMI and improving patient survival.
Area of Science:
- Biochemistry
- Cardiology
- Proteomics
Background:
- Acute myocardial infarction (AMI) and cardiogenic shock (CS) are leading causes of mortality.
- Effective biomarkers for early detection and prediction of outcomes in ST-elevation myocardial infarction (STEMI) are limited.
- Current biomarker discovery often relies on single-protein, hypothesis-driven approaches, hindering the identification of novel candidates.
Purpose of the Study:
- To identify novel protein biomarkers associated with STEMI, CS, and mortality using proteome-wide data.
- To evaluate the predictive ability of identified proteins for CS and all-cause mortality after AMI.
- To explore the clinical relevance of protein biomarkers in predicting adverse cardiovascular events.
Main Methods:
- Proteome-wide data from 497 patients with suspected STEMI were analyzed.
- Logistic and Cox regression models were used for association analysis.
- Multivariable LASSO regression models were employed for prediction modeling to identify key protein signatures.
Main Results:
- Association studies identified 4 proteins linked to definitive STEMI and 29 proteins associated with mortality.
- Prediction models incorporating protein sets demonstrated improved predictive ability for CS (AUC 0.92) and mortality (AUC 0.89) compared to protein-free models.
- Two and five proteins were identified in the prediction models for CS and mortality, respectively.
Conclusions:
- Individual proteins show potential as biomarkers for STEMI diagnosis and survival prediction.
- Sets of proteins have been identified with significant predictive ability for CS and mortality following AMI.
- These identified proteins warrant further verification as clinically relevant biomarkers for cardiovascular outcomes.
Aim:
Acute myocardial infarction (AMI) remains a major cause of mortality and morbidity, and cardiogenic shock (CS) a major cause of hospital mortality after AMI. Especially for ST elevation myocardial infarction (STEMI) patients, fast intervention is essential.Few proteins have proven clinically applicable for AMI. Most proposed biomarkers are based on a priori hypothesis-driven studies of single proteins, not enabling identification of novel candidates. For clinical use, the ability to predict AMI is important; however, studies of proteins in prediction models are surprisingly scarce.Consequently, we applied proteome data for identifying proteins associated with definitive STEMI, CS, and all-cause mortality after admission, and examined the ability of the proteins to predict these outcomes.
Methods And Results:
Proteome-wide data of 497 patients with suspected STEMI were investigated; 381 patients were diagnosed with STEMI, 35 with CS, and 51 died during the first year. Data analysis was conducted by logistic and Cox regression modeling for association analysis, and by multivariable LASSO regression models for prediction modeling.Association studies identified 4 and 29 proteins associated with definitive STEMI or mortality, respectively. Prediction models for CS and mortality (holding two and five proteins, respectively) improved the prediction ability as compared with protein-free prediction models; AUC of 0.92 and 0.89, respectively.
Conclusion:
The association analyses propose individual proteins as putative protein biomarkers for definitive STEMI and survival after suspected STEMI, while the prediction models put forward sets of proteins with putative predicting ability of CS and survival. These proteins may be verified as biomarkers of potential clinical relevance.
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