Background: The outcome of cardiogenic shock complicating myocardial infarction has not appreciably changed in the last 30 years despite the development of various percutaneous mechanical circulatory support options. It is clear that there are varying degrees of cardiogenic shock but there is no robust classification scheme to categorize this disease state.Methods: A multidisciplinary group of experts convened by the Society for Cardiovascular Angiography and Interventions was assembled to derive a proposed classification schema for cardiogenic shock. Representatives from cardiology (interventional, advanced heart failure, noninvasive), emergency medicine, critical care, and cardiac nursing all collaborated to develop the proposed schema.Results: A system describing stages of cardiogenic shock from A to E was developed. Stage A is “at risk” for cardiogenic shock, stage B is “beginning” shock, stage C is “classic” cardiogenic shock, stage D is “deteriorating”, and E is “extremis”. The difference between stages B and C is the presence of hypoperfusion which is present in stages C and higher. Stage D implies that the initial set of interventions chosen have not restored stability and adequate perfusion despite at least 30 minutes of observation and stage E is the patient in extremis, highly unstable, often with cardiovascular collapse.Conclusion: This proposed classification system is simple, clinically applicable across the care spectrum from pre‐hospital providers to intensive care staff but will require future validation studies to assess its utility and potential prognostic implications.

Right ventricular (RV) failure remains a major cause of global morbidity and mortality for patients with advanced heart failure, pulmonary hypertension, or acute myocardial infarction and after major cardiac surgery. Over the past 2 decades, percutaneously delivered acute mechanical circulatory support pumps specifically designed to support RV failure have been introduced into clinical practice. RV acute mechanical circulatory support now represents an important step in the management of RV failure and provides an opportunity to rapidly stabilize patients with cardiogenic shock involving the RV. As experience with RV devices grows, their role as mechanical therapies for RV failure will depend less on the technical ability to place the device and more on improved algorithms for identifying RV failure, patient monitoring, and weaning protocols for both isolated RV failure and biventricular failure. In this review, we discuss the pathophysiology of acute RV failure and both the mechanism of action and clinical data exploring the utility of existing RV acute mechanical circulatory support devices.

Background: Risk stratifying patients with cardiogenic shock (CS) is a major unmet need. The recently proposed Society for Cardiovascular Angiography and Interventions (SCAI) stages as an approach to identify patients at risk for in-hospital mortality remains under investigation. We studied the utility of the SCAI stages and further explored the impact of hemodynamic congestion on clinical outcomes. Methods: The CS Working Group registry includes patients with CS from 8 medical centers enrolled between 2016 and 2019. Patients were classified by the maximum SCAI stage (B–E) reached during their hospital stay according to drug and device utilization. In-hospital mortality was evaluated for association with SCAI stages and hemodynamic congestion. Results: Of the 1414 patients with CS, the majority were due to decompensated heart failure (50%) or myocardial infarction (MI; 35%). In-hospital mortality was 31% for the total cohort, but higher among patients with MI (41% versus 26%, MI versus heart failure, P <0.0001). Risk for in-hospital mortality was associated with increasing SCAI stage (odds ratio [95% CI], 3.25 [2.63–4.02]) in both MI and heart failure cohorts. Hemodynamic data was available in 1116 (79%) patients. Elevated biventricular filling pressures were common among patients with CS, and right atrial pressure was associated with increased mortality and higher SCAI Stage. Conclusions: Our findings support an association between the proposed SCAI staging system and in-hospital mortality among patient with heart failure and MI. We further identify that venous congestion is common and identifies patients with CS at high risk for in-hospital mortality. These findings provide may inform future management protocols and clinical studies.

Background: Cardiogenic shock (CS) is a heterogeneous syndrome with varied presentations and outcomes. We used a machine learning approach to test the hypothesis that patients with CS have distinct phenotypes at presentation, which are associated with unique clinical profiles and in‐hospital mortality. Methods and Results: We analyzed data from 1959 patients with CS from 2 international cohorts: CSWG (Cardiogenic Shock Working Group Registry) (myocardial infarction [CSWG‐MI; n=410] and acute‐on‐chronic heart failure [CSWG‐HF; n=480]) and the DRR (Danish Retroshock MI Registry) (n=1069). Clusters of patients with CS were identified in CSWG‐MI using the consensus k means algorithm and subsequently validated in CSWG‐HF and DRR. Patients in each phenotype were further categorized by their Society of Cardiovascular Angiography and Interventions staging. The machine learning algorithms revealed 3 distinct clusters in CS: "non‐congested (I)", "cardiorenal (II)," and "cardiometabolic (III)" shock. Among the 3 cohorts (CSWG‐MI versus DDR versus CSWG‐HF), in‐hospital mortality was 21% versus 28% versus 10%, 45% versus 40% versus 32%, and 55% versus 56% versus 52% for clusters I, II, and III, respectively. The "cardiometabolic shock" cluster had the highest risk of developing stage D or E shock as well as in‐hospital mortality among the phenotypes, regardless of cause. Despite baseline differences, each cluster showed reproducible demographic, metabolic, and hemodynamic profiles across the 3 cohorts. Conclusions: Using machine learning, we identified and validated 3 distinct CS phenotypes, with specific and reproducible associations with mortality. These phenotypes may allow for targeted patient enrollment in clinical trials and foster development of tailored treatment strategies in subsets of patients with CS.