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1 Time Series Analysis in Intensive Care Medicine

Objectives: Time series analysis techniques facilitate statistical analysis of variables in the course of time. Continuous monitoring of the critically ill in intensive care offers an especially wide range of applications. In an open clinical study time series analysis was applied to the monitoring of lab variables after liver surgery, and to support clinical decision making in the treatment of acute respiratory distress syndrome. Patients and Results: For the analysis of lab variables (blood lactate) in 19 patients after liver resections ARIMA (Auto Regressive Integrated Moving Average) models were developed for an estimation period of at least 14 measurements. Prediction values from these models for the following data points were then compared to the actual lab values. With these models in all cases of hepatic complications pathological changes in the lab values could be differentiated from random variance. This work has in part been supported by the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 475 This work has already been published in: Imhoff M., Bauer M., Gather U., Löhlein D.(1997): Time series analysis in intensive care medicine. Applied Cardiopulmonary Pathophysiology 6: 263-281