Rebeccah M Brusca1, Catherine E Simpson2, Sarina K Sahetya2, Zeba Noorain3, Varshitha Tanykonda4, R Scott Stephens2, Dale M Needham2,5,6,7, David N Hager2. 1. Department of Medicine, 1500Johns Hopkins University, Baltimore, MD, USA. 2. Division of Pulmonary & Critical Care Medicine, Department of Medicine, 1500Johns Hopkins University, Baltimore, MD, USA. 3. 29099Bangalore Medical College and Research Institute, Bangalore, India. 4. Department of Medicine, 12227University of Connecticut School of Medicine, Farmington, CT, USA. 5. Armstrong Institute for Patient Safety, 1466John Hopkins University, Baltimore, MD, USA. 6. Outcomes After Critical Illness and Surgery (OACIS) Group, 1466Johns Hopkins University, Baltimore, MD, USA. 7. Department of Physical Medicine and Rehabilitation, School of Medicine, 1466Johns Hopkins University, Baltimore, MD, USA.
Abstract
BACKGROUND: Intermediate care units (IMCUs) are heterogeneous in design and operation, which makes comparative effectiveness studies challenging. A generalizable outcome prediction model could improve such comparisons. However, little is known about the performance of critical care outcome prediction models in the intermediate care setting. The purpose of this study is to evaluate the performance of the Acute Physiology and Chronic Health Evaluation version II (APACHE II), Simplified Acute Physiology Score version II (SAPS II) and version 3 (SAPS 3), and Mortality Probability Model version III (MPM0III) in patients admitted to a well-characterized IMCU. MATERIALS AND METHODS: In the IMCU of an academic medical center (July to December 2012), the discrimination and calibration of each outcome prediction model were evaluated using the area under the receiver-operating characteristic and Hosmer-Lemeshow goodness-of-fit test, respectively. Standardized mortality ratios (SMRs) were also calculated. RESULTS: The cohort included data from 628 unique IMCU admissions with an inpatient mortality rate of 8.3%. All models exhibited good discrimination, but only the SAPS II and MPM0III were well calibrated. While the APACHE II and SAPS 3 both markedly overestimated mortality, the SMR for the SAPS II and MPM0III were 0.91 and 0.91, respectively. CONCLUSIONS: The SAPS II and MPM0III exhibited good discrimination and calibration, with slight overestimation of mortality. Each model should be further evaluated in multicenter studies of patients in the intermediate care setting.
BACKGROUND: Intermediate care units (IMCUs) are heterogeneous in design and operation, which makes comparative effectiveness studies challenging. A generalizable outcome prediction model could improve such comparisons. However, little is known about the performance of critical care outcome prediction models in the intermediate care setting. The purpose of this study is to evaluate the performance of the Acute Physiology and Chronic Health Evaluation version II (APACHE II), Simplified Acute Physiology Score version II (SAPS II) and version 3 (SAPS 3), and Mortality Probability Model version III (MPM0III) in patients admitted to a well-characterized IMCU. MATERIALS AND METHODS: In the IMCU of an academic medical center (July to December 2012), the discrimination and calibration of each outcome prediction model were evaluated using the area under the receiver-operating characteristic and Hosmer-Lemeshow goodness-of-fit test, respectively. Standardized mortality ratios (SMRs) were also calculated. RESULTS: The cohort included data from 628 unique IMCU admissions with an inpatient mortality rate of 8.3%. All models exhibited good discrimination, but only the SAPS II and MPM0III were well calibrated. While the APACHE II and SAPS 3 both markedly overestimated mortality, the SMR for the SAPS II and MPM0III were 0.91 and 0.91, respectively. CONCLUSIONS: The SAPS II and MPM0III exhibited good discrimination and calibration, with slight overestimation of mortality. Each model should be further evaluated in multicenter studies of patients in the intermediate care setting.
Entities:
Keywords:
intermediate care unit; mortality prediction; outcome prediction; progressive care; stepdown care
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