Is cardiac arrest still a binary clinical diagnosis? Toward electro-mechanical–hemodynamic phenotyping in the era of point-of-care ultrasound

BACKGROUND: Cardiac arrest (CA) remains operationally recognized through clinical signs of absent effective circulation and classified primarily by electrical rhythm. Point-of-care ultrasound (PoCUS) challenges this rhythm-pulse paradigm by directly revealing cardiac mechanical activity and, with Doppler, circulatory flow, exposing physiologically distinct states concealed within current CA categories. METHODS: This physiology-based conceptual manuscript proposes an integrated electro-mechanical-hemodynamic framework for CA and translates it into PoCUS-consistent phenotyping, portraying CA presentations (CA phenotypes) as pathophysiological states that may transition from one to another along a spontaneous or treatment-modified continuum. CLINICAL IMPLICATIONS: The framework distinguishes three principal phenotypes: shockable CA (ventricular fibrillation/pulseless ventricular tachycardia); zero-flow CA, encompassing Asystole and PEA without organized ventricular contraction (S-PEA) or with agonal mechanical activity (A-PEA); and severe low-flow CA (C-PEA), in which organized ventricular contraction persists despite absent palpable pulse, and may generate residual circulation. PoCUS can define mechanical states, identify reversible causes, contextualize diagnostic findings, reveal occult shockable activity, and track phenotype transitions. Doppler and invasive arterial-pressure monitoring further characterize spontaneous flow and pressure and may support phenotype-informed treatment. CONCLUSIONS: Electro-mechanical-hemodynamic phenotyping extends established ALS classification by providing a standardized physiological language for distinct CA states, enabling more homogeneous research populations, phenotype-specific resuscitation research, and rigorous evaluation of PoCUS-informed management. Taken together, these physiological distinctions provide a rationale for reconsidering how cardiac arrest is characterized and how PoCUS-derived information could inform future research, evidence reviews, and resuscitation recommendations.