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.
Background: Cardiogenic shock occurring in the setting of advanced heart failure (HF-CS) is increasingly common. However, recent studies have focused almost exclusively on acute myocardial infarction-related CS. We sought to define clinical, hemodynamic, metabolic, and treatment parameters associated with clinical outcomes among patients with HF-CS, using data from the Cardiogenic Shock Working Group registry. Methods: Patients with HF-CS were identified from the multicenter Cardiogenic Shock Working Group registry and divided into 3 outcome categories assessed at hospital discharge: mortality, heart replacement therapy (HRT: durable ventricular assist device or orthotopic heart transplant), or native heart survival. Clinical characteristics, hemodynamic, laboratory parameters, drug therapies, acute mechanical circulatory support device (AMCS) utilization, and Society of Cardiovascular Angiography and Intervention stages were compared across the 3 outcome cohorts. Results: Of the 712 patients with HF-CS identified, 180 (25.3%) died during their index admission, 277 (38.9%) underwent HRT (durable ventricular assist device or orthotopic heart transplant), and 255 (35.8%) experienced native heart survival without HRT. Patients who died had the highest right atrial pressure and heart rate and the lowest mean arterial pressure of the 3 outcome groups ( P <0.01 for all). Biventricular and isolated left ventricular congestion were common among patients who died or underwent HRT, respectively. Lactate, blood urea nitrogen, serum creatinine, and aspartate aminotransferase were highest in patients with HF-CS experiencing in-hospital death. Intraaortic balloon pump was the most commonly used AMCS device in the overall cohort and among patients receiving HRT. Patients receiving >1 AMCS device had the highest in-hospital mortality rate irrespective of the number of vasoactive drugs used. Mortality increased with deteriorating Society of Cardiovascular Angiography and Intervention stages (stage B: 0%, stage C: 10.7%, stage D: 29.4%, stage E: 54.5%, 1-way ANOVA=<0.001). Conclusions: Patients with HF-CS experiencing in-hospital mortality had a high prevalence of biventricular congestion and markers of end-organ hypoperfusion. Substantial heterogeneity exists with use of AMCS in HF-CS with intraaortic balloon pump being the most common device used and high rates of in-hospital mortality after exposure to >1 AMCS device.
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