Dynamic lactate indices as predictors of outcome in critically ill patients

Introduction: Dynamic changes in lactate concentrations in the critically ill may predict patient outcome more accurately than static indices. We aimed to compare the predictive value of dynamic indices of lactatemia in the first 24 hours of intensive care unit (ICU) admission with the value of more commonly used static indices. Methods: This was a retrospective observational study of a prospectively obtained intensive care database of 5,041 consecutive critically ill patients from four Australian university hospitals. We assessed the relationship between dynamic lactate values collected in the first 24 hours of ICU admission and both ICU and hospital mortality. Results: We obtained 36,673 lactate measurements in 5,041 patients in the first 24 hours of ICU admission. Both the time weighted average lactate (LAC(TW24)) and the change in lactate (LAC Delta 24) over the first 24 hours were independently predictive of hospital mortality with both relationships appearing to be linear in nature. For every one unit increase in LAC(TW24) and LAC Delta 24 the risk of hospital death increased by 37% (OR 1.37, 1.29 to 1.45; P < 0.0001) and by 15% (OR 1.15, 1.10 to 1.20; P < 0.0001) respectively. Such dynamic indices, when combined with Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, improved overall outcome prediction (P < 0.0001) achieving almost 90% accuracy. When all lactate measures in the first 24 hours were considered, the combination of LAC(TW24) and LAC Delta 24 significantly outperformed (P < 0.0001) static indices of lactate concentration, such as admission lactate, maximum lactate and minimum lactate. Conclusions: In the first 24 hours following ICU admission, dynamic indices of hyperlactatemia have significant independent predictive value, improve the performance of illness severity score-based outcome predictions and are superior to simple static indices of lactate concentration.