Mortality prediction in septic shock patients: Towards new personalized models in critical care

We studied the problem of mortality prediction in 23 septic shock patients selected from the public database MIMIC-II. For each patient we derived hemodynamic variables, laboratory results and clinical information of the first 48 hours after shock onset and we performed univariate and multivariate analyses to predict mortality in the following 7 days. The results show interesting features that individually identify significant differences between survivors and non survivors and features which gain importance only when considered together with the others in a multivariate regression model, such as the respiratory rate (RR). This preliminary study on a small septic shock population represents a novel contribution towards new personalized models for an integration of multi-scale and multi-level patient information to improve critical care management of shock patients.

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