Addition of admission lactate levels to Baux score improves mortality prediction in severe burns

Risk adjustment and mortality prediction models are central in optimising care and for benchmarking purposes. In the burn setting, the Baux score and its derivatives have been the mainstay for predictions of mortality from burns. Other well-known measures to predict mortality stem from the ICU setting, where, for example, the Simplified Acute Physiology Score (SAPS 3) models have been found to be instrumental. Other attempts to further improve the prediction of outcome have been based on the following variables at admission: Sequential Organ Failure Assessment ((a)SOFA) score, determinations of (a)Lactate or Neutrophil to Lymphocyte Ratio ((a)NLR). The aim of the present study was to examine if estimated mortality rate (EMR, SAPS 3), (a)SOFA, (a)Lactate, and (a)NLR can, either alone or in conjunction with the others, improve the mortality prediction beyond that of the effects of age and percentage total body surface area (TBSA%) burned among patients with severe burns who need critical care. This is a retrospective, explorative, single centre, registry study based on prospectively gathered data. The study included 222 patients with median (25th–75th centiles) age of 55.0 (38.0 to 69.0) years, TBSA% burned was 24.5 (13.0 to 37.2) and crude mortality was 17%. As anticipated highest predicting power was obtained with age and TBSA% with an AUC at 0.906 (95% CI 0.857 to 0.955) as compared with EMR, (a)SOFA, (a)Lactate and (a)NLR. The largest effect was seen thereafter by adding (a)Lactate to the model, increasing AUC to 0.938 (0.898 to 0.979) (p < 0.001). Whereafter, adding EMR, (a)SOFA, and (a)NLR, separately or in combinations, only marginally improved the prediction power. This study shows that the prediction model with age and TBSA% may be improved by adding (a)Lactate, despite the fact that (a)Lactate levels were only moderately increased. Thereafter, adding EMR, (a)SOFA or (a)NLR only marginally affected the mortality prediction.