OBJECTIVE: To determine the impact of missing Acute Physiology Score (APS) values on risk-adjusted mortality. DESIGN: Retrospective review of prospectively collected Acute Physiology and Chronic Health Evaluation (APACHE) III database. SETTING: The intensive care units (ICUs) of an academic medical center. PATIENTS: 38,411 patients admitted to ICU between October 1994 and December 2003. MEASUREMENTS AND RESULTS: Data were collected on ICU type, missing first ICU day APS values, predicted and observed hospital mortality, standardized mortality ratio (SMR), 95% confidence interval (CI), odds ratio (OR). The overall observed and predicted hospital mortality rates were 8.7% and 10.8%, respectively, with SMR of 0.806 (95% CI 0.779-0.834). Complete data were available in 829 (2.2%). Vital signs were missing in almost none and serum albumin and bilirubin in over 80% of the patients. The number of missing variables was higher in less sick and surgical ICU patients. Logistic regression analysis showed that the risk of dying in the hospital was significantly associated with the number of missing APS variables (OR 1.058, 95% CI 1.027-1.090) when adjusted for the severity of illness. The risk of death was also associated with the type of missing variables. CONCLUSIONS: Since missing APS values may lead to underestimation of the predicted mortality rates, the number and type of missing variables should be taken into consideration when assessing the performance of an ICU. Unless data collection is standardized, future prognostic models should use variables that are routinely measured in most critically ill patients without sacrificing statistical precision.
OBJECTIVE: To determine the impact of missing Acute Physiology Score (APS) values on risk-adjusted mortality. DESIGN: Retrospective review of prospectively collected Acute Physiology and Chronic Health Evaluation (APACHE) III database. SETTING: The intensive care units (ICUs) of an academic medical center. PATIENTS: 38,411 patients admitted to ICU between October 1994 and December 2003. MEASUREMENTS AND RESULTS: Data were collected on ICU type, missing first ICU day APS values, predicted and observed hospital mortality, standardized mortality ratio (SMR), 95% confidence interval (CI), odds ratio (OR). The overall observed and predicted hospital mortality rates were 8.7% and 10.8%, respectively, with SMR of 0.806 (95% CI 0.779-0.834). Complete data were available in 829 (2.2%). Vital signs were missing in almost none and serum albumin and bilirubin in over 80% of the patients. The number of missing variables was higher in less sick and surgical ICU patients. Logistic regression analysis showed that the risk of dying in the hospital was significantly associated with the number of missing APS variables (OR 1.058, 95% CI 1.027-1.090) when adjusted for the severity of illness. The risk of death was also associated with the type of missing variables. CONCLUSIONS: Since missing APS values may lead to underestimation of the predicted mortality rates, the number and type of missing variables should be taken into consideration when assessing the performance of an ICU. Unless data collection is standardized, future prognostic models should use variables that are routinely measured in most critically ill patients without sacrificing statistical precision.
Authors: P G Metnitz; H Vesely; A Valentin; C Popow; M Hiesmayr; K Lenz; C G Krenn; H Steltzer Journal: Crit Care Med Date: 1999-08 Impact factor: 7.598
Authors: Bekele Afessa; Mark T Keegan; Rolf D Hubmayr; James M Naessens; Ognjen Gajic; Kirsten Hall Long; Steve G Peters Journal: Mayo Clin Proc Date: 2005-02 Impact factor: 7.616
Authors: Peter Andrews; Elie Azoulay; Massimo Antonelli; Laurent Brochard; Christian Brun-Buisson; Geoffrey Dobb; Jean-Yves Fagon; Herwig Gerlach; Johan Groeneveld; Jordi Mancebo; Philipp Metnitz; Stefano Nava; Jerome Pugin; Michael Pinsky; Peter Radermacher; Christian Richard; Robert Tasker Journal: Intensive Care Med Date: 2006-02-17 Impact factor: 17.440