Dynamic lactate indices as predictors of outcome in critically ill patients.
BACKGROUND
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 (LACTW₂₄) and the change in lactate (LACΔ₂₄) 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 LACTW₂₄ and LACΔ₂₄ 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 LACTW₂₄ and LACΔ₂₄ 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.
Australian and New Zealand Intensive Care - Research Centre, School of Public Health and Preventive Medicine, Monash University, Commercial Road, Melbourne, VIC, Australia.
Alistair
A
Nichol
Michael
M
Bailey
Moritoki
M
Egi
Ville
V
Pettila
Craig
C
French
Edward
E
Stachowski
Michael C
MC
Reade
David James
DJ
Cooper
Rinaldo
R
Bellomo
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D016638:Critical Illness; D005260:Female; D006305:Health Status Indicators; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D019344:Lactic Acid / Q000097:blood*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D012189:Retrospective Studies; D016896:Treatment Outcome
D015415:Biomarkers; D019344:Lactic Acid