External validation of eight different models to predict sepsis mortality in intensive care units

Purpose: Sepsis is a complex, heterogenous syndrome defined as life-threatening organ dysfunction due to severe infection. Existing mortality prediction models may not adequately capture the complexities of sepsis. The objectives of this study were twofold; to clarify to what extent variables belonging to eight different mortality prediction models used in intensive care units (ICU) were collected in routine medical care, and to externally validate these models. Material and methods: A retrospective cohort of 750 patients admitted to three ICU's with a final diagnosis of sepsis at ICU discharge were included. Mortality prediction models were evaluated by calculating the area under receiver operating curve (AUROC) for their ability to predict 30-day mortality. Results: The CSM-4, when used 4 h after ICU admission, predicted ICU episode-of-care mortality best with an AUROC of 0.80. It used only a few variables which are frequently retrieved in routine medical care. ANZROD 24 was the best performing model to be applied 24 h after admission with AUROC of 0.83. Conclusions: Time after admission may decide which prediction model is most useful. Early after ICU admission, the sepsis-specific CSM-4 mortality prediction model performed slightly better than other models. However, at 24 h after admission general models not specific for sepsis, like the ANZROD 24, performed well.

Journal of Critical Care

Journal of Critical Care

90

1557-8615

N/A

N/A

6