Multiparameter models for the prediction of sepsis outcome

This study reports the predictive value, in septic patients, of septic shock at presentation (SS factor) alone and in combination with multiple markers, using survival of the sepsis episode as the outcome measure. The SS factor correctly predicted the outcome in 53/68 (78%) of patients in this study. The Acute Physiology and Chronic Health Evaluation II Score (APACHE II or APII) and interleukin-6 (IL-6) and IL-6 soluble receptor (IL-6sR) concentrations were evaluated in combination with the SS factor in the same 68 patient population which was randomly divided into design (# = 50) and test groups (# = 18). Two iterations of an algorithm were evaluated using randomized patient groups corresponding to those producing the best (Group A) and worst (Group B) performance using a neural network. The four-input algorithm (APII, IL-6, IL-6sR, SS factor) correctly classified 16/18 (89%, Group A) and 14/18 (78%, Group B) of patients in the test subset. The corresponding four-input neural network model (10 iterations) correctly classified 61 to 89% of the 18 patients in the 10 test subsets.

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				R. A. Lukaszewski, A. M. Yates, M. C. Jackson, K. Swingler, J. M. Scherer, A. J. Simpson, P. Sadler, P. McQuillan, R. W. Titball, T. J. G. Brooks, et al. Presymptomatic Prediction of Sepsis in Intensive Care Unit Patients Clin. Vaccine Immunol., July 1, 2008; 15(7): 1089 - 1094. [Abstract] [Full Text] [PDF]