Prognostic categorization of intensive care septic patients.
Sepsis is one of the leading worldwide causes of morbidity and mortality in critically-ill patients. Prediction of outcome in patients with sepsis requires repeated clinical interpretation of the patients' conditions, clinical assessment of tissue hypoxia and the use of severity scoring systems, because the prognostic categorization accuracy of severity scoring indices alone, is relatively poor. Generally, such categorization depends on the severity of the septic state, ranging from systemic inflammatory response to septic shock. Now, there is no gold standard for the clinical assessment of tissue hypoxia which can be achieved by both global and regional oxygen extractabilities, added to prognostic pro-inflammatory mediators. Because the technology used to identify the genetic make-up of the human being is rapidly advancing, the structure of 30 000 genes which make-up the human DNA bank is now known. This would allow easy prognostic categorization of critically-ill patients including those suffering from sepsis. The present review spots lights on the main severity scoring systems used for outcome prediction in septic patients. For morbidity prediction, it discusses the Multiple Organ Dysfunction score, the sequential organ failure assessment score, and the logistic organ dysfunction score. For mortality/survival prediction, it discusses the Acute Physiology and Chronic Health Evaluation scores, the Therapeutic Intervention Scoring System, the Simplified acute physiology score and the Mortality Probability Models. An ideal severity scoring system for prognostic categorization of patients with systemic sepsis is far from being reached. Scoring systems should be used with repeated clinical interpretation of the patients' conditions, and the assessment of tissue hypoxia in order to attain satisfactory discriminative performance and calibration power.
Mohamed Ezzat Moemen, Department of Anaesthesia and Intensive Care, Faculty of medicine, Zagazig University, Zagazig 44519, Egypt.
Mohamed Ezzat
ME
Moemen
Genome; Prognostic markers; Sepsis; Severity scoring systems; Systemic inflammatory Response syndrome