Admission diagnosis and mortality risk prediction in a contemporary cardiac intensive care unit population Jacob C. Jentzer, MD, a, b Sean van Diepen, MD MSc, c Dennis H. Murphree, PhD, d Abdalla S. Ismail, MBBS, e Mark T. Keegan, MB MRCPI, f David A. Morrow, MD MPH, g Gregory W. Barsness, MD, a and Nandan S Anavekar, MBBCh a Rochester, MN; Edmonton, Alberta; and Boston, MA Background Critical care risk scores can stratify mortality risk among cardiac intensive care unit (CICU) patients, yet risk score performance across common CICU admission diagnoses remains uncertain. Methods We evaluated performance of the Acute Physiology and Chronic Health Evaluation (APACHE)-III, APACHE-IV, Sequential Organ Failure Assessment (SOFA) and Oxford Acute Severity of Illness Score (OASIS) scores at the time of CICU admission in common CICU admission diagnoses. Using a database of 9,898 unique CICU patients admitted between 2007 and 2015, we compared the discrimination (c-statistic) and calibration (Hosmer-Lemeshow statistic) of each risk score in patients with selected admission diagnoses. Results Overall hospital mortality was 9.2%. The 3182 (32%) patients with a critical care diagnosis such as cardiac arrest, shock, respiratory failure, or sepsis accounted for N85% of all hospital deaths. Mortality discrimination by each risk score was comparable in each admission diagnosis (c-statistic 95% CI values were generally overlapping for all scores), although calibration was variable and best with APACHE-III. The c-statistic values for each score were 0.85-0.86 among patients with acute coronary syndromes, and 0.76- 0.79 among patients with heart failure. Discrimination for each risk score was lower in patients with critical care diagnoses (c-statistic range 0.68-0.78) compared to non-critical cardiac diagnoses (c-statistic range 0.76-0.86). Conclusions The tested risk scores demonstrated inconsistent performance for mortality risk stratification across admission diagnoses in this CICU population, emphasizing the need to develop improved tools for mortality risk prediction among critically-ill CICU patients. (Am Heart J 2020;224:57-64.) Risk stratification among patients with acute cardiovas- cular disease facilitates outcome prediction, therapeutic decisions, and quality assurance in the modern cardiac intensive care unit (CICU). 1 , 2 Contemporary CICU patients often have primary cardiovascular problems with multiple non-cardiovascular comorbidities or com- plications, making standard diagnosis-specific risk scores derived in non-critically-ill populations less applicable. Development and validation of risk prediction models for common CICU conditions has been identified as a priority for contemporary CICU research. 1 , 2 Established intensive care unit (ICU) risk scores such as the Acute Physiology and Chronic Health Evaluation (APACHE) and Sequential Organ Failure Assessment (SOFA) scores are currently used for mortality risk stratification, to adjust for illness severity, and to ensure adequate balance between randomized groups in critically-ill populations. 3-5 The complexity and ease of calculating these ICU risk scores varies: 10 variables are included in the SOFA and OASIS scores and more than 20 variables are required to calculate the APACHE score, including physiological variables reflecting severity of illness, circumstances of admission and admission diag- nosis (Figure 1). Each of these ICU risk scores has demonstrated similar, very good discrimination (ability to From the a Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, b Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, c Department of Critical Care Medicine and Division of Cardiology, Department of Medicine, University of Alberta Hospital, Edmonton, Alberta, d Department of Health Sciences Research, Mayo Clinic, Rochester, MN, e Multidisciplinary Epidemiol- ogy and Translational Research in Intensive Care (METRIC) Group, Mayo Clinic, Rochester, MN, f Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, and g TIMI Study Group, Cardiovascular Division, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA. Disclosures: The authors declare that they have no competing financial interests or conflicts of interest to disclose relevant to this work. Source of funding: No extramural funding source was involved in the collection, analysis or interpretation of study data. Marc Jolicoeur, MD MSc MHS served as guest editor for this article. Submitted November 13, 2019; accepted February 14, 2020. Reprint requests: Jacob C. Jentzer, MD FACC, Department of Cardiovascular Medicine and Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, The Mayo Clinic, 200 First Street SW, Rochester, MN 55905. E-mail: jentzer.jacob@mayo.edu 0002-8703 © 2020 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.ahj.2020.02.018 Clinical Investigations