Mortality Prediction Model of Septic Shock Patients Based on Routinely Recorded Data

12Citations
Citations of this article
45Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

We studied the problem of mortality prediction in two datasets, the first composed of 23 septic shock patients and the second composed of 73 septic subjects 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 nonsurvivors and features which gain importance only when considered together with the others in a multivariate regression model. This preliminary study on two small septic shock populations represents a novel contribution towards new personalized models for an integration of multiparameter patient information to improve critical care management of shock patients.

Cite

CITATION STYLE

APA

Carrara, M., Baselli, G., & Ferrario, M. (2015). Mortality Prediction Model of Septic Shock Patients Based on Routinely Recorded Data. Computational and Mathematical Methods in Medicine, 2015. https://doi.org/10.1155/2015/761435

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free