• J M Murthy, A K Meena, and S R Kumar.
• Department of Neurology, The Institute of Neurological Sciences, CARE Hospital and Nizam's Institute of Medical Sciences, Hyderabad, India.
• Neurol India. 2001 Jun 1;49 Suppl 1:S91-4.

AbstractPredicting the outcome of critically ill patients admitted to intensive care units (ICU) has undergone considerable evolution over the last two decades. Various general purpose severity-of-illness scoring systems, Acute Physiology and Chronic Health Evaluation score (APACHE II, APACHE III), Mortality Predicting Model (MPM II), and Simplified Acute Physiology Score (SAPS II), have been extensively validated for large groups of critical care patients with mixed diagnoses and found to correlate well with observed outcome in general. The general hypothesis underlying the use of severity-of-illness scoring systems is that clinical variables that can be assessed on ICU admission and subsequent days of stay in the ICU predict survival and other outcomes of critically ill patients. Variables included in severity-of-illness scoring systems measure specific clinical and physiological functions that are major determinants of mortality. These scoring systems may be used alone within a single disease category or any other independently defined patient group to perform relative risk stratification. Variation in death rates by disease reflects the nature of the underlying process. There is a need for using these scoring systems in specialized ICUs like neurological and neurosurgical ICU as they allow, in addition to predicting outcome, evaluation of new therapies, monitoring of resource utilization and quality assessment of intensive care units.

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