Background: The existing models to predict mortality in intensive care units (ICU) present difficulties in clinical practice.
Objectives: The aim of this study was to develop and internally validate a points system to predict mortality in the ICU, which can be applied instantly and with high discriminating power.
Methods: This cohort study comprised all patients admitted to the ICU in a Spanish region between January 2013 and April 2014, followed from admission to death or discharge (N=1113). Primary variable: ICU mortality. Secondary variables at admission: gender, Fried criteria for frailty, function scale, medical admission, cardiac arrest, cardiology admission, sepsis, mechanical ventilation, inotropic support, age, frailty index and clinical frailty scale. The sample was divided randomly into two groups (80% and 20%): construction (n=844) and internal validation (n=269). Construction: A logistic regression model was implemented and adapted to the points system.
Validation: the area under the ROC curve (AUC) of the model was calculated and the risk quintiles were created to determine whether differences existed between observed and expected deaths.
Results: The points system included: function scale, medical admission, cardiology admission, sepsis, mechanical ventilation and inotropic support. The validation showed: (i) AUC=0.95 (95% CI: 0.91-0.99, p<.001); (ii) No differences between observed and expected deaths (p=.799).
Conclusions: A predictive model of mortality in the ICU has been constructed and internally validated. This model improves on the previous models through its simplicity, its discriminating power and free use. External validation studies are needed in other geographical areas.
© 2016 John Wiley & Sons Ltd.