Lactate clearance as a marker of mortality in pediatric intensive care unit.

Indian Pediatr. 2014 Jul 8;51(7):565-7.

Munde A, Kumar N, Beri RS, Puliyel JM.

: To correlate lactate clearance with Pediatric Intensive Care Unit (PICU)
: 45 (mean age 40.15 mo, 60% males) consecutive admissions in the
PICU were enrolled between May 2012 to June 2013. Lactate clearance (Lactate level at
admission – level 6 hr later x 100 / lactate level at admission) in first 6 hours of hospitalization
was correlated to in-hospital mortality and PRISM score.
: Twelve out of 45 patients
died. 90% died among those with delayed/poor clearance (clearance <30%) compared to
8.5% in those with good clearance (clearance >30%) (
<0.001). Lactate clearance <30%
predicted mortality with sensitivity of 75%, specificity of 97%, positive predictive value of
90%, and negative predictive value of 91.42%. Predictability was comparable to PRISM
score >30.
: Lactate clearance at six hours correlates with mortality in the PICU.

yperlactatemia is an indicator of inadequate
tissue perfusion, particularly in sepsis
[1]. It
reflects severity of illness with significant
prognostic implications [2]. The severity and
duration of lactic acidosis in critically ill patients
correlates with overall oxygen debt, and increased
[3,4]. However, a single lactate measurement
has not been correlated to mortality consistently
Lactate clearance is the rate of fall in lactate after
resuscitation is started. This has shown more promise in
predicting mortality. Two studies in adult patients with
shock showed that lactate clearance of <10% was related
to mortality [5,6]. There are no pediatric studies looking
at lactate clearance and mortality although Hatheril,
et al
[7] showed that persistent hyper-lactatemia at 24 hours
(>2 mmol/dL) was associated with mortality. We
investigated whether lactate clearance in the early period
of resuscitation (first 6 hours of hospitalization) could
help predict mortality in pediatric patients.
Admissions to the PICU (aged >1 month and <13 years)
were studied between May 2012 and June 2013 after
obtaining informed written consent from parents.
Children with inborn error of metabolism and trauma
were excluded. The study was approved by the hospital
ethics committee. As a pilot study, a convenience sample
of 45 patients admitted consecutively was enrolled.
Heparinized syringe was used to collect venous blood.
Lactate estimation was done by Radiometer Copenhagen ABL 555 blood gas analyzer.
Lactate levels were estimated at admission and after
six hours of admission and the clearance was calculated
as follows: Lactate clearance = [Initial Lactate - Current
Lactate) × 100 / Initial Lactate].
A positive value denotes clearance of lactate, whereas
a negative value denotes an increase in lactate after
intervention. Routine ICU care and investigations were
performed and Pediatric Risk of Mortality (PRISM)
score was calculated. In-hospital mortality was the
primary outcome of interest.
Survivors and non-survivors were compared by the
Mann-Whitney test for continuous variables and by
Fisher’s exact test for categorical variables. For non-
parametric data, pair-wise comparisons were made using
Wilcoxon’s signed-rank test. For continuous variable, we
used t-test. A
value <0.05 was taken as statistically
significant. SPSS version 16.0 was used.
Out of 45 children (mean age 40.15, range 1-144 months,
M:F ratio 1.5:1), twelve died. The initial lactate was not
significantly different between those who died and those
who survived [8.44 (3.27)
7.29 (3.31),
=0.18], but
clearance at 6 hours was significantly lower in those who
died (-4.01%) than those who survived (55.53)
<0.001). The mean (SD) PRISM score was also higher
in those who died compared with those who survived
[43.6 (7.27)
. 21.7 (9.2),
Where lactate clearance was <30% at 6 hours, nine
out of ten died. In those with clearance >30% only three
out of thirty-five died. ROC curve analysis for mortality
prediction was 0.97 (
< 0.001) (
. Three children
died within 24 hours. Mean (SD) duration of hospital stay
in those with lactate clearance >30% was 18.5 (8.44) d
(range 3-40), against 3.1 (2.61) d (range 1-9) in those
with clearance <30%.
An inverse relationship was observed between lactate
clearance and PRISM score (
). Lactate clearance
<30% at six hours predicted mortality with sensitivity of
75%, specificity of 97%, PPV 90%, NPV 91.42%.
Observed and expected mortality was almost similar in
those having PRISM score of >30.
Lactate clearance at 6 hours was significantly associated
with mortality as was a PRISM score >35. The ROC
curve shows mortality prediction of lactate clearance was
The duration of stay was longer in those with good
clearance because of early mortality in the ones with poor
clearance. There were very few survivors among those
with poor clearance to allow us to compare duration of
stay in survivors in the two groups.
High admission lactate was a significant independent
predictor of mortality in adult patients admitted to ICU
[8-10] but it could not be replicated in other studies [6,11
Studies have suggested the value of monitoring for lactate
clearance with hypo-perfusion
[6,7]. One of these studies
found a 41% higher mortality rate among those subjects
who failed to reach a lactate clearance of 10% when
compared with those that effectively cleared lactate (60%
. 19% mortality) during the early resuscitative period.
The only study in pediatric age group conducted by
et al
[7], showed that persistent hyper-lactatemia
>2 mmol/L after 24 hours was associated with 93%
mortality, as compared to 30% in those children whose
lactate level had normalized. Following the study in adults,
we used lactate clearance at 6 hours
[6]. We found that we
can predict mortality as early as 6 hours. In our study PPV,
NPV and ROC curve analysis for mortality prediction at 6
hours of lactate clearance are comparable to Hatheril,
et al
[7] findings at 24 hours.
We found that a lactate clearance
30% at six hours
and PRISM score more than 30 have high prediction for
mortality. Lactate clearance can probably be used as a
screening tool to predict adverse outcome. We have
provided stratification and cut-off values of lactate
clearance which need validation by more studies with
larger samples