SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission

Abstract

Objective: To develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data.

Design: Prospective multicentre, multinational cohort study.

Patients and setting: A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002.

Measurements and results: ICU admission data (recorded within +/-1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test H=10.56, p=0.39, C=14.29, p=0.16). Customized equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit.

Conclusions: The SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels.

Fig. 1

Distribution of the SAPS 3 admission score in the SAPS 3 database

Fig. 2

Relationship between the SAPS 3 admission score and the respective probabilities of hospital mortality

Fig. 3

Hosmer-Lemeshow goodness-of-fit test Ĉ in the overall sample. Predicted risk of hospital death, observed hospital mortality rate, and the corresponding number of patients per decile are shown. Columns: Number of patients; squares: mean SAPS 3-predicted mortality per decile; circles: mean observed mortality per decile

Fig. 4

Hosmer-Lemeshow goodness-of-fit test Ĥ in the overall sample. Predicted risk of hospital death, observed hospital mortaliy rate, and the corresponding number of patients per decile are shown. Columns: Number of patients; squares: mean SAPS 3-predicted mortality per decile; circles: mean observed mortality per decile

Fig. 5

Observed-to-expected (O/E) mortality ratios by region. Observed-to-expected (O/E) mortality ratios are shown by region. Bars indicate 95% confidence intervals