title: The impact of delirium on the prediction of in-hospital mortality in intensive care patients.
abstract: BACKGROUND
  Predictive models, such as acute physiology and chronic health evaluation II (APACHE-II), are widely used in intensive care units (ICUs) to estimate mortality. Although the presence of delirium is associated with a higher mortality in ICU patients, delirium is not part of the APACHE-II model. The aim of the current study was to evaluate whether delirium, present within 24 hours after ICU admission, improves the predictive value of the APACHE-II score.
  
  
  METHODS
  In a prospective cohort study 2116 adult patients admitted between February 2008 and February 2009 were screened for delirium with the confusion assessment method-ICU (CAM-ICU). Exclusion criteria were sustained coma and unable to understand Dutch. Logistic regression analysis was used to estimate the predicted probabilities in the model with and without delirium. Calibration plots and the Hosmer-Lemeshow test (HL-test) were used to assess calibration. The discriminatory power of the models was analyzed by the area under the receiver operating characteristics curve (AUC) and AUCs were compared using the Z-test.
  
  
  RESULTS
  1740 patients met the inclusion criteria, of which 332 (19%) were delirious at the time of ICU admission or within 24 hours after admission. Delirium was associated with in-hospital mortality in unadjusted models, odds ratio (OR): 3.22 (95% confidence interval [CI]: 2.23 - 4.66). The OR between the APACHE-II and in-hospital mortality was 1.15 (95% CI 1.12 - 1.19) per point. The predictive accuracy of the APACHE-II did not improve after adding delirium, both in the total group as well as in the subgroup without cardiac surgery patients. The AUC of the APACHE model without delirium was 0.77 (0.73 - 0.81) and 0.78 (0.74 - 0.82) when delirium was added to the model. The z-value was 0.92 indicating no improvement in discriminative power, and the HL-test and calibration plots indicated no improvement in calibration.
  
  
  CONCLUSIONS
  Although delirium is a significant predictor of mortality in ICU patients, adding delirium as an additional variable to the APACHE-II model does not result in an improvement in its predictive estimates.
authors.affiliation: Department of Intensive Care, Radboud University Nijmegen Medical Centre, Nijmegen, PO box 9101, Nijmegen 6500HB, the Netherlands. m.vandenboogaard@ic.umcn.nl
authors.forename: Mark
authors.initials: M
authors.lastname: van den Boogaard
authors.forename: Sanne Ae
authors.initials: SA
authors.lastname: Peters
authors.forename: Johannes G
authors.initials: JG
authors.lastname: van der Hoeven
authors.forename: Pieter C
authors.initials: PC
authors.lastname: Dagnelie
authors.forename: Pieter
authors.initials: P
authors.lastname: Leffers
authors.forename: Peter
authors.initials: P
authors.lastname: Pickkers
authors.forename: Lisette
authors.initials: L
authors.lastname: Schoonhoven
mesh_terms: D018806:APACHE; D000368:Aged; D016001:Confidence Intervals; D003693:Delirium / Q000175:diagnosis / Q000401:mortality*; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011446:Prospective Studies; D012372:ROC Curve