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Abstract Aims Hospitalized patients with heart failure (HF) are a heterogeneous population, with multiple phenotypes proposed. Prior studies have not examined the biological phenotypes of critically ill patients with HF admitted to the contemporary cardiac intensive care unit (CICU). We aimed to leverage unsupervised machine learning to identify previously unknown HF phenotypes in a large and diverse cohort of patients with HF admitted to the CICU. Methods We screened 6008 Mayo Clinic CICU patients with an admission diagnosis of HF from 2007 to 2018 and included those without missing values for common laboratory tests. Consensus k‐means clustering was performed based on 10 common admission laboratory values (potassium, chloride, anion gap, blood urea nitrogen, haemoglobin, red blood cell distribution width, mean corpuscular volume, platelet count, white blood cell count and neutrophil‐to‐lymphocyte ratio). In‐hospital mortality was evaluated using logistic regression, and 1 year mortality was evaluated using Cox proportional hazard models after multivariable adjustment. Results Among 4877 CICU patients with HF who had complete admission laboratory data (mean age 69.4 years, 38.4% females), we identified five clusters with divergent demographics, comorbidities, laboratory values, admission diagnoses and use of critical care therapies. We labelled these clusters based on the characteristic laboratory profile of each group: uncomplicated (25.7%), iron‐deficient (14.5%), cardiorenal (18.4%), inflamed (22.3%) and hypoperfused (19.2%). In‐hospital mortality occurred in 10.7% and differed between the phenotypes: uncomplicated, 2.7% (reference); iron‐deficient, 8.1% [adjusted odds ratio (OR) 2.18 (1.38–3.48), P

Background The epidemiology and pathophysiology of heart failure (HF) differ in women and men. Whether these differences extend to the subgroup of patients with advanced HF is not well defined. Methods and Results This is a retrospective cohort study of all adult Olmsted County, Minnesota residents with advanced HF (European Society of Cardiology criteria) from 2007 to 2017. Differences in survival and hospitalization risks in women and men following advanced HF development were examined using Cox proportional hazard regression and Andersen‐Gill models, respectively. Of 936 individuals with advanced HF, 417 (44.6%) were women and 519 (55.4%) were men (self‐reported sex). Time from development of HF to advanced HF was similar in women and men (median 3.2 versus 3.6 years). Women were older at diagnosis (mean age 79 versus 75 years), less often had coronary disease and hyperlipidemia, but more often had hypertension and depression (P