Cardiogenic shock (CS) is a heterogeneous condition associated with exceptionally high mortality rates, despite significant advances in the field of cardiology. The primary causes of CS are myocardial infarction-related CS (AMI-CS) and acute decompensated heart failure-related CS (ADHF-CS).

CS remains a complex and multifaceted condition with high mortality rates despite advancements in medical management.

The heterogeneity of CS, coupled with the challenges in diagnosis and treatment, underscores the need for a nuanced approach to patient care.

The use of inotropes and vasopressors continues to be a cornerstone in the initial management of CS, providing critical support to maintain cardiac output and blood pressure.

However, the scarcity of high-quality data from randomized trials limits our ability to establish robust guidelines, often relying on limited data and expert opinion.

The recent advances in the SCAI classification and the work by Zweck et al. using machine learning to define CS phenotypes represent significant steps forward. These developments hold promise for generating better quality data and improving our understanding of CS.

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