Abstract Background Acute myocardial infarction (AMI) is one of the most frequent causes of cardiac arrest with a high mortality rate over the past decades. Currently available risk stratification tools for very early prediction of patient mortality primarily rely on static data obtained at the time of the cardiac arrest event, without considering early patient trajectories.(1) However, neurological prognostication is typically performed after multiple days following the event by which time initially assessed parameters may no longer accurately reflect the patient's condition. Objectives To identify parameters within the first 96 hours following AMI-induced cardiac arrest that predict in-hospital mortality. Methods A consecutively enrolled cohort of adult patients with AMI-induced cardiac arrest was analysed at one cardiac arrest centre. Patient demographics, cardiac arrest parameters and laboratory values within 96 hours after the event were assessed. Regression analyses were performed to identify independent predictors of in-hospital mortality. Results A total of 195 patients with AMI-induced cardiac arrest were included in the study, of whom 118 (61%) survived and 77 (39%) died during hospitalization. The mean patient age was 63 years (±13) and 155 patients (80%) were male. Non-survivors presented significantly less frequently with a shockable cardiac arrest rhythm (65% vs. 88%), were more likely to receive veno-arterial extracorporeal membrane oxygenation (47% vs. 16%) or micro-axial flow pump support (57% vs. 16%), exhibited more complex coronary artery disease (53% vs. 33% with three-vessel coronary disease) and had a significantly greater reduction in left ventricular ejection fraction (30% vs. 42%). Significant differences emerged between survivors and non-survivors regarding the 96-hour trajectories of inflammatory markers (C-reactive protein CRP, procalcitonin, leukocytes and neutrophils), organ injury markers (creatine kinase CK, CK-MB, lactate, creatinine and glomerular filtration rate), coagulation and blood count parameters (platelet count, haemoglobin, D-dimer, lactate dehydrogenase as a haemolysis marker) and metabolic markers (albumin and bilirubin) (Figure). Particularly, inflammatory and metabolic markers measured after 48 hours were identified as independent predictors of in-hospital mortality. Conclusions Risk stratification following cardiac arrest should not be static but should incorporate dynamic patient trajectories within the first days, including markers on inflammatory status, organ injury, coagulation, blood count and metabolism. These time-sensitive parameters may provide valuable prognostic information and might be considered in early risk assessment.
Thevathasan et al. (Sat,) studied this question.