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Invasive Phenoprofiling of Acute-Myocardial-Infarction-Related Cardiogenic Shock
Jorge A Ortega-Hernández1, Héctor González-Pacheco1, Jardiel Argüello-Bolaños1
1Instituto Nacional de Cardiología Ignacio Chávez, Coronary Care Unit, Juan Badiano 1, Sección XVI, Tlalpan, Ciudad De Mexico 14080, Mexico.
Insights
Understanding cardiogenic shock (CS) phenotypes in acute myocardial infarction (AMI-CS) is key. The cardiometabolic phenotype showed the highest mortality, highlighting the need for tailored treatment strategies based on CS phenotyping.
Area of Science:
- Cardiology
- Intensive Care Medicine
- Hemodynamics
Background:
- Previous studies identified three cardiogenic shock (CS) phenotypes: cardiac-only, cardiorenal, and cardiometabolic.
- Acute myocardial infarction complicated by CS (AMI-CS) exhibits significant heterogeneity.
- Understanding hemodynamic profiles is crucial for managing AMI-CS.
Purpose of the Study:
- To elucidate the hemodynamic characteristics of different AMI-CS phenotypes.
- To investigate the prognostic implications of these phenotypes using pulmonary artery catheter (PAC) data.
- To better understand AMI-CS heterogeneity for improved patient outcomes.
Main Methods:
- Analysis of PAC data from 309 patients with AMI-CS.
- Classification of patients based on SCAI shock stage, congestion profile, and phenotype.
- Collection of 24-hour hemodynamic data via PAC.
Main Results:
- Three AMI-CS phenotypes were identified: cardiac-only (43.7%), cardiorenal (32.0%), and cardiometabolic (24.3%).
- The cardiometabolic phenotype exhibited the highest mortality (70.7%), followed by cardiorenal (52.5%) and cardiac-only (33.3%).
- Higher right atrial pressure and pulmonary capillary wedge pressure were observed in cardiometabolic and cardiorenal phenotypes. Lower cardiac output and related indices were noted in cardiorenal and cardiometabolic groups. Hazard ratios indicated significantly increased mortality risk for cardiorenal (2.1) and cardiometabolic (3.3) phenotypes compared to cardiac-only. Multi-organ failure, AKI, and VT/VF were significant predictors. Multivariate analysis confirmed CS phenotypes, SCAI score, and ∆congestion as independent predictors of mortality.
Conclusions:
- Phenotyping AMI-CS patients is vital for accurate prognosis and tailored treatment strategies.
- Pulmonary artery catheter profiling offers valuable prognostic insights.
- This data can inform the design of future clinical trials for AMI-CS.
Background:
Studies had previously identified three cardiogenic shock (CS) phenotypes (cardiac-only, cardiorenal, and cardiometabolic). Therefore, we aimed to understand better the hemodynamic profiles of these phenotypes in acute myocardial infarction-CS (AMI-CS) using pulmonary artery catheter (PAC) data to better understand the AMI-CS heterogeneity.
Methods:
We analyzed the PAC data of 309 patients with AMI-CS. The patients were classified by SCAI shock stage, congestion profile, and phenotype. In addition, 24 h hemodynamic PAC data were obtained.
Results:
We identified three AMI-CS phenotypes: cardiac-only (43.7%), cardiorenal (32.0%), and cardiometabolic (24.3%). The cardiometabolic phenotype had the highest mortality rate (70.7%), followed by the cardiorenal (52.5%) and cardiac-only (33.3%) phenotypes, with significant differences (p < 0.001). Right atrial pressure (p = 0.001) and pulmonary capillary wedge pressure (p = 0.01) were higher in the cardiometabolic and cardiorenal phenotypes. Cardiac output, index, power, power index, and cardiac power index normalized by right atrial pressure and left-ventricular stroke work index were lower in the cardiorenal and cardiometabolic than in the cardiac-only phenotypes. We found a hazard ratio (HR) of 2.1 for the cardiorenal and 3.3 for cardiometabolic versus the cardiac-only phenotypes (p < 0.001). Also, multi-organ failure, acute kidney injury, and ventricular tachycardia/fibrillation had a significant HR. Multivariate analysis revealed that CS phenotypes retained significance (p < 0.001) when adjusted for the Society for Cardiovascular Angiography & Interventions score (p = 0.011) and ∆congestion (p = 0.028). These scores independently predicted mortality.
Conclusions:
Accurate patient prognosis and treatment strategies are crucial, and phenotyping in AMI-CS can aid in this effort. PAC profiling can provide valuable prognostic information and help design new trials involving AMI-CS.
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