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Arch Hellen Med, 31(5), September-October 2014, 541-557


Prognostic scoring systems and outcome markers in ICU patients

S. Fika,1 S. Nanas,1 G. Baltopoulos,2 P. Myrianthefs2
1Intensive Care Unit, "Evangelismos" General Hospital, Athens,
2Intensive Care Unit, "Aghioi Anargyroi" General Oncology Hospital of Kifissia, Athens, Greece

The illness severity and outcome prediction scales for intensive care unit (ICU) patients were developed approximately 30 years ago. They are very important in clinical practice as they are widely used to predict the outcome and characterize the severity of the illness and the degree of organ dysfunction, and also to assess the use of resources and quantify the needs of the ICU. The scoring systems can also be of value for evaluating the quality of care (benchmarking), for risk stratification and for ensuring the comparability of patient populations in clinical trials. Many of these scoring systems have been updated and there should be continuous progress in order to keep up with the population of patients of which the case-mix and the severity change. The acute physiology and chronic health evaluation (APACHE), the mortality probability model (MPM), the simplified acute physiology score (SAPS) and the sequential organ failure assessment (SOFA) are the major generic ICU scoring systems in use today. Central to all these systems is the use of data on the physiological status of the patients and the fact that differences in the time of the data selection may influence the accuracy of the systems. The therapeutic intervention scoring system (TISS) and nursing activity score (NAS) are the scoring systems widely used to assess nursing workload and in many studies they have been found to be associated with the severity of illness and the length of stay in hospital of ICU patients. Recently, there has been great interest in the use of biochemical markers, the rate of change of which during critical illness can predict the outcome. It may be possible to develop reliable prognostic models, including various biological markers, to assist in clinical decision making.

Key words: Intensive care, Nursing workload, Outcome markers, Outcome prediction, Severity of illness.

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