OBJECTIVES: To evaluate the prognostic performance of the original Simplified Acute Physiology Score (SAPS) II in Austrian intensive care patients and to evaluate the impact of customization. DESIGN: Analysis of the database of a multicenter study. SETTING: Nine adult medical, surgical, and mixed intensive care units (ICUs) in Austria. PATIENTS: A total of 1733 patients consecutively admitted to the ICUs. MEASUREMENTS AND RESULTS: The database included admission data, SAPS II, length of stay, and hospital mortality. The Hosmer-Lemeshow goodness-of-fit test for the SAPS II showed a lack of uniformity of fit (H = 89.1, 10 df, p < 0.0001; C = 91.8, 10 df, p < 0.0001). Subgroup analysis showed good performance in patients with cardiovascular (medical and surgical) diseases as the primary reasons for admission. A new predictive equation was derived by means of the logistic regression. Goodness-of-fit was excellent for the customized model (SAPS IIAM) (H = 11.2, 9 df, p = 0.33, C = 11.6, 9 df, p = 0.24). The mean standardized mortality ratio (SMR) changed from 0.81 +/- 0.26 to 0.93 +/- 0.29 with customization. CONCLUSIONS: SAPS II was not well calibrated when applied to all patients. However, it performed well for patients with cardiovascular diseases as the primary reason for admission and may thus be applied to these patients. Standardized mortality ratios that are calculated from scoring systems without known calibration must be viewed with skepticism.
OBJECTIVES: To evaluate the prognostic performance of the original Simplified Acute Physiology Score (SAPS) II in Austrian intensive care patients and to evaluate the impact of customization. DESIGN: Analysis of the database of a multicenter study. SETTING: Nine adult medical, surgical, and mixed intensive care units (ICUs) in Austria. PATIENTS: A total of 1733 patients consecutively admitted to the ICUs. MEASUREMENTS AND RESULTS: The database included admission data, SAPS II, length of stay, and hospital mortality. The Hosmer-Lemeshow goodness-of-fit test for the SAPS II showed a lack of uniformity of fit (H = 89.1, 10 df, p < 0.0001; C = 91.8, 10 df, p < 0.0001). Subgroup analysis showed good performance in patients with cardiovascular (medical and surgical) diseases as the primary reasons for admission. A new predictive equation was derived by means of the logistic regression. Goodness-of-fit was excellent for the customized model (SAPS IIAM) (H = 11.2, 9 df, p = 0.33, C = 11.6, 9 df, p = 0.24). The mean standardized mortality ratio (SMR) changed from 0.81 +/- 0.26 to 0.93 +/- 0.29 with customization. CONCLUSIONS: SAPS II was not well calibrated when applied to all patients. However, it performed well for patients with cardiovascular diseases as the primary reason for admission and may thus be applied to these patients. Standardized mortality ratios that are calculated from scoring systems without known calibration must be viewed with skepticism.
Authors: P Kellner; R Prondzinsky; L Pallmann; S Siegmann; S Unverzagt; H Lemm; S Dietz; J Soukup; K Werdan; M Buerke Journal: Med Klin Intensivmed Notfmed Date: 2013-04-06 Impact factor: 0.840
Authors: Barbara Metnitz; Eva Schaden; Rui Moreno; Jean-Roger Le Gall; Peter Bauer; Philipp G H Metnitz Journal: Intensive Care Med Date: 2008-10-10 Impact factor: 17.440
Authors: So Yeon Lim; Cho Rom Ham; So Young Park; Suhyun Kim; Maeng Real Park; Kyeongman Jeon; Sang-Won Um; Man Pyo Chung; Hojoong Kim; O Jung Kwon; Gee Young Suh Journal: Yonsei Med J Date: 2011-01 Impact factor: 2.759
Authors: Rui P Moreno; Philipp G H Metnitz; Eduardo Almeida; Barbara Jordan; Peter Bauer; Ricardo Abizanda Campos; Gaetano Iapichino; David Edbrooke; Maurizia Capuzzo; Jean-Roger Le Gall Journal: Intensive Care Med Date: 2005-08-17 Impact factor: 17.440