Validation of severity scoring systems SAPS II and APACHE II in a single-center population

To validate two severity scoring systems, the Simplified Acute Physiology Score (SAPS II) and Acute Physiology and Chronic Health Evaluation (APACHE II), in a single-center ICU population. Prospective data collection in a two four-bed multidisciplinary ICUs of a teaching hospital. Data were collecte...

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Published in:Intensive care medicine Vol. 26; no. 12; pp. 1779 - 1785
Main Authors: CAPUZZO, M, VALPONDI, V, SGARBI, A, BORTOLAZZI, S, PAVONI, V, GILLI, G, CANDINI, G, GRITTI, G, ALVISI, R
Format: Journal Article
Language:English
Published: Heidelberg Springer 01-12-2000
Berlin Springer Nature B.V
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Summary:To validate two severity scoring systems, the Simplified Acute Physiology Score (SAPS II) and Acute Physiology and Chronic Health Evaluation (APACHE II), in a single-center ICU population. Prospective data collection in a two four-bed multidisciplinary ICUs of a teaching hospital. Data were collected in ICU over 4 years on 1,721 consecutively admitted patients (aged 18 years or older, no transferrals, ICU stay at least 24 h) regarding SAPS II, APACHE II, predicted hospital mortality, and survival upon hospital discharge. At the predicted risk of 0.5, sensitivity was 39.4 % for SAPS II and 31.6 % for APACHE II, specificity 95.6 % and 97.2 %, and correct classification rate 85.6 % and 85.5 %, respectively. The area under the ROC curve was higher than 0.8 for both models. The goodness-of-fit statistic showed no significant difference between observed and predicted hospital mortality (H = 7.62 for SAPS II, H = 3.87 for APACHE II; and C = 9.32 and C = 5.05, respectively). Observed hospital mortality of patients with risk of death higher than 60 % was overpredicted by SAPS II and underpredicted by APACHE II. The observed hospital mortality was significantly higher than that predicted by the models in medical patients and in those admitted from the ward. This study validates both SAPS II and APACHE II scores in an ICU population comprised mainly of surgical patients. The type of ICU admission and the location in the hospital before ICU admission influence the predictive ability of the models.
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ISSN:0342-4642
1432-1238
DOI:10.1007/s001340000715