Admission Diagnosis and Mortality Risk Prediction in a Contemporary Cardiac Intensive Care Unit Population

Published on Feb 28, 2020in American Heart Journal4.749
路 DOI :10.1016/J.AHJ.2020.02.018
Jacob C. Jentzer25
Estimated H-index: 25
(Mayo Clinic),
Sean van Diepen31
Estimated H-index: 31
(University of Alberta Hospital)
+ 5 AuthorsNandan S. Anavekar26
Estimated H-index: 26
(Mayo Clinic)
Sources
Abstract
Abstract 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 >85% 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.
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#1Ryan A. Watson (Thomas Jefferson University Hospital)H-Index: 3
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Background:The changing landscape of care in the Cardiac Intensive Care Unit (CICU) has prompted efforts to redesign the structure and organization of advanced CICUs. Few studies have quantitativel...
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Background There are no risk scores designed specifically for mortality risk prediction in unselected cardiac intensive care unit (CICU) patients. We sought to develop a novel CICU鈥恠pecific risk score for prediction of hospital mortality using variables available at the time of CICU admission.
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#1Michael Goldfarb (Cedars-Sinai Medical Center)H-Index: 4
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#1Courtney Bennett (Mayo Clinic)H-Index: 13
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Abstract Purpose To assess trends in life support interventions and performance of the automated Acute Physiology and Chronic Health Evaluation (APACHE) IV model at mortality prediction compared with Oxford Acute Severity of Illness Score (OASIS) in a contemporary cardiac intensive care unit (CICU). Methods and materials Retrospective analysis of adults (age鈥墺鈥18鈥痽ears) admitted to CICU from January 1, 2007, through December 31, 2015. Temporal trends were assessed with linear regression. Discrim...
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#2Dennis H. Murphree (Mayo Clinic)H-Index: 13
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Older adults account for an increasing number of cardiac intensive care unit (CICU) admissions. This study sought to determine the predictive value of illness severity scores for mortality in CICU patients 鈮70 years of age. Adult patients admitted to the CICU from 2007 to 2015 at one tertiary care hospital were reviewed. Severity of illness scores were calculated on the first CICU day. Area under the receiver-operator characteristic curve (AUROC) values were used to assess discrimination for hos...
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Background Optimal methods of mortality risk stratification in patients in the cardiac intensive care unit (CICU) remain uncertain. We evaluated the ability of the Sequential Organ Failure Assessment (SOFA) score to predict mortality in a large cohort of unselected patients in the CICU. Methods and Results Adult patients admitted to the CICU from January 1, 2007, to December 31, 2015, at a single tertiary care hospital were retrospectively reviewed. SOFA scores were calculated daily, and Acute P...
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#1Eric M Holland (University of Virginia Health System)H-Index: 4
#2Travis J. Moss (University of Virginia Health System)H-Index: 10
Abstract Background Fifty years after the inception of the cardiac intensive care unit (CICU), noncardiovascular illnesses have become more prevalent and may contribute to morbidity and mortality. Objectives The authors performed multivariate statistical analyses to determine the association of acute noncardiovascular illnesses with outcomes, including length of stay (LOS), mortality, and hospital readmission. Methods We studied 1,042 admissions between October 12, 2013 and November 28, 2014 to ...
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#1Jason N. Katz (UNC: University of North Carolina at Chapel Hill)H-Index: 31
#2Michael Minder (Duke University)H-Index: 1
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Risk stratification dates to the dawn of the cardiac intensive care unit (CICU). As the CICU has evolved from a dedicated unit caring for patients with acute myocardial infarction to a complex healthcare environment encompassing a broad array of acute and chronic cardiovascular pathology, an expanding array of risk scores are available that can be applied to CICU patients. Most of these scores were designed for use either in patients with a specific acute cardiovascular diagnosis or unselected c...
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