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Pediatric Emergency Medicine Journal > Volume 12(3); 2025 > Article
Trotter, Jackson, Khetarpal, Bhattarai, Barlow, Hurkett, and Foster: Admission lactate as a rule-in predictor of severe pediatric trauma in an Arizona trauma center

Abstract

Purpose

Pediatric trauma is a leading cause of mortality among children. A high lactate concentration is a well-established prognostic indicator for severe trauma in adults, but evidence is lacking in children.

Methods

A retrospective review was performed on patients aged 0-17 years who underwent trauma activations at an urban medical center in Arizona from 2010 through 2020. Data were collected on demographics, injury mechanisms, admission lactate values, Glasgow Coma Scale, Injury Severity Score, hospital length of stay, and severe trauma. The severe trauma was defined as in-hospital mortality, or need for blood transfusion or emergency surgical interventions.

Results

Of 566 patients, 53 (9.4%) had severe trauma, of whom 11 (1.9%) died, 32 (5.7%) underwent blood transfusions, and 32 (5.7%) underwent emergency surgical interventions. Patients with severe trauma had a significantly higher median lactate concentration than those without severe trauma (2.5 mmol/L [interquartile range, 1.9-3.8] vs. 1.7 mmol/L [1.2-2.4]; P < 0.001). An optimal lactate cutoff was 1.9 showed an area under the curve of 0.69 (95% confidence interval, 0.61-0.77), resulting in a maximal combined sensitivity (75.4%) and specificity (57.9%). As a lactate cutoff increased from 1.0 to 6.0 mmol/L, the specificity increased from 9.2% to 98.8%, while the sensitivity decreased from 96.2% to 13.2% for predicting severe trauma. Admission lactate was correlated negatively with Glasgow Coma Scale (Spearman’s rho = - 0.134; P = 0.001) and positively with Injury Severity Score (0.130; P = 0.002), while not correlated with hospital length of stay (0.070; P = 0.096).

Conclusion

Admission lactate has a high specificity for severe trauma in children at the cost of sensitivity. It should be used in conjunction with other screening tools when ruling out severe trauma.

Introduction

Trauma is a major cause of mortality in children. Identifying potentially severe injuries can be complicated because children have a greater capacity for hemodynamic compensation than adults do. Although late shock is quickly recognizable in children, it may be difficult to detect early shock for several reasons. First, while tachycardia can be a sensitive indicator of shock, it is less applicable in children than in adults because of variations in resting heart rate at different ages and extreme lability of the heart rate due to anxiety or pain. Second, children often have normal mean arterial pressure during early shock due to catecholamine release, which increases diastolic pressure and obscures the effect of systolic pressure on mean arterial pressure. Third, with a smaller blood volume than adults, children are predisposed to unanticipated hemodynamic decompensation even from small blood volume losses.
Traumatic hemorrhage leads to tissue hypoxia that releases lactate, a biomarker for shock (1). There are unique challenges in interpretation of lactate concentrations in children. Lactate concentration may transiently increase by stress hormones released in fearful, anxious, or crying children (2,3). On the other hand, children have more efficient buffering systems and higher oxygen-carrying capacity than adults, resulting in a better response to tissue hypoxia (4,5). Therefore, the clinical utility of lactate in children has been questioned. Elevated values of admission lactate (6-8) and prehospital lactate (9) have been shown to be early prognostic indicators in adults with trauma. However, sparse evidence supports the utility of this biomarker in pediatric trauma. A promising association has been demonstrated in a few studies that are limited in size and scope. Shah et al. (10) found that prehospital lactate concentrations were higher in those requiring critical care, including those with normal prehospital vital signs and Glasgow Coma Scale (GCS). Ramanathan and colleagues (11) showed that elevated lactate values correlated with injury severity, hospital length of stay (LOS), morbidity, and mortality. Although elevated lactate concentration has not yet been universally defined in pediatric trauma, Ramanathan et al. (11) considered lactate > 4.7 mmol/L to be elevated.
We primarily aimed to determine the utility of admission lactate concentration in severe pediatric trauma by measuring the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of varying lactate values. The secondary objective was to assess the correlations of admission lactate with GCS, Injury Severity Score (ISS), and hospital LOS.

Methods

1. Study setting and population

The study site is Valleywise Health Medical Center which is an urban academic medical center located in Phoenix, AZ, USA, serving a primarily lower socioeconomic population. It has been designated as an American College of Surgeons-verified, level 1 adult and level 2 pediatric trauma center. From 2010 through 2020, there was an annual average of 948 trauma activations of which 7% were patients younger than 18 years. Our hospital’s institutional review board granted expedited approval for this retrospective chart review (IRB no. 2020-051). The study was performed in compliance with institutional guidelines. Informed consent was not required, and funding was not received for any part of this research.

2. Study design

The commercial trauma database utilized by our institution during the study period was Trauma One (Lancet Technology Inc.). Trauma registrars extracted data from the electronic medical records and manually entered it in the database. For each patient’s entry, 208 variables were collected from prehospital and hospital care. Only individuals approved by the institution were able to access and run reports from the database. Trauma activation at our facility is modeled according to the National Guidelines for the Field Triage of Injured Patients developed by the American College of Surgeons Committee on Trauma. The original trauma activation criteria constituted a 3-level response (red-yellow-green) from 2010 to 2019 followed by a revised criteria in 2019 with 2-tiers (levels 1 and 11) (Appendices 1-4 [https://doi.org/10.22470/pemj.2025.01305]). The highest level of activation (red or level 1) is confirmed age-specific hypotension, respiratory compromise, obstruction, or endotracheal intubation; patients transferred from other hospitals receiving blood products at emergency physician’s discretion, gunshot wounds to the abdomen, neck, or chest; or a GCS less than 8 with mechanism attributed to trauma.
We queried the database records from June 1, 2010 through May 31, 2020 for patients aged 0-17 years with trauma activations and venous samples for lactate concentrations drawn in the emergency department (ED) upon arrival. The venous lactate is routinely ordered as part of the initial laboratory evaluation of all traumatic activations. We collected information on demographics, medical history, trauma mechanisms, ISS, GCS, concentration of admission lactate, hospital LOS, blood transfusion, surgical procedures, final diagnosis, and disposition. We excluded patients who received trauma consultation without trauma activation, were transferred from outside facilities, or received blood transfusions or emergency procedures prior to arrival at the ED.

3. Key outcomes

The primary outcome was severe trauma as defined by (1) in-hospital mortality (< 30 days post-admission), (2) need for blood transfusion within 24 hours post-admission, or (3) need for emergency surgical interventions, such as advanced lifesaving beside trauma procedures, surgical exploration, angioembolization, or tube thoracostomy. These categories were based on publications whereby major trauma, irrespective of the mechanism of injury, resulted in fatal injuries, injuries requiring emergent or delayed surgical interventions, or blood transfusion (6-10). While we described each classification as separate percentages, some patients met more than 1 criterion for severe trauma and thus the percentages should be considered only for descriptive purposes. We reported on the ages, mechanisms of injury, admission lactate, secondary outcomes of GCS, ISS, hospital LOS, and the initial disposition.

4. Data analysis

Demographic and clinical characteristics were summarized as median values with interquartile ranges for non-Gaussian variables tested using the Shapiro-Wilk tests. Continuous variables were compared using Wilcoxon rank-sum tests with t-approximation. Counts and proportions were compared using chi-square or Fisher exact tests. Sensitivity, specificity, PPV, and NPV for severe trauma were analyzed at lactate cutoffs of 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, and 6.0 mmol/L, with an optimal cutoff for the best combination of sensitivity and specificity reported using Youden Index. Receiver operating characteristic (ROC) curves for severe trauma, GCS, and ISS were constructed for the lactate cutoffs. Spearman’s rank correlation tests were used to examine correlations between quantifiable patient characteristics and severe trauma. A 2-sided P < 0.05 was considered significant. All analyses were performed using SAS ver. 9.4 (SAS Institute, Inc.).

Results

Table 1 shows the characteristics of the 566 patients included in this analysis. Motor vehicular collision was the most prevalent trauma mechanism (53.0%). Of the 53 patients (9.4%) who suffered severe trauma, 11 (1.9%) died, 32 (5.7%) underwent transfusions, and 32 (5.7%) did emergency surgical interventions. We applied mutually inclusive criteria for severe trauma, and as such the sum of patients in each classification exceeded the total number of patients with severe trauma (75 vs. 53). None of the patients had bleeding diseases such as hemophilia. The median lactate concentration was 1.7 mmol/L (interquartile range, 1.3-2.5) for the entire population. Patients with severe trauma had a higher median lactate value than those with non-severe trauma (2.5 mmol/L [1.9-3.8] vs. 1.7 mmol/L [1.2-2.4]; P < 0.001). There was a significant difference in the disposition of patients with and without severe trauma. Table 2 details the primary injury types. Head injuries were most prevalent (25.8%), followed by a similar distribution of injuries to the extremities, lungs, spine, and intraabdominal solid organs.
Table 3 shows the sensitivity, specificity, PPV, and NPV for different lactate cutoffs. A high cutoff had a higher specificity and NPV for severe trauma but did not perform as well for sensitivity and PPV. Fig. 1 depicts an ROC curve representing the sensitivity and specificity for varying lactate cutoffs with the optimal cutoff predictive of severe trauma. At an optimal cutoff of 1.9, the area under the curve was 0.69 (95% confidence interval, 0.61-0.77), resulting in a sensitivity of 75.4% and a specificity of 57.9%. ROC curves and optimal cutoffs for GCS and ISS are represented in Figs 2 and 3. Admission lactate was correlated negatively with GCS (Spearman’s rho = -0.134; P = 0.001) and positively with ISS (0.130; P = 0.002), while not correlated with hospital LOS (0.070; P = 0.096).

Discussion

In this pediatric study, we found that admission lactate has a good specificity, i.e., rule-in capacity, for severe trauma at the cost of limited sensitivity, i.e., rule-out capacity. As expected, the specificity improved with increasing lactate cutoffs. A cutoff higher than 3.5 mmol/L had a specificity higher than 91%. Conversely, the sensitivity tends to be better at a lower cutoff (12); the overall sensitivities were relatively low (13.2%-96.2%) at lactate cutoffs ranging from 1 to 6 mmol/L. This means that some patients with severe trauma did not have high lactate concentrations. When ruling out severe trauma, lactate concentration should be used with caution, and in conjunction with other screening tools. The optimal sensitivity and specificity at a lactate value of 1.9 mmol/L (Fig. 1) indicate that any value above this cutoff, the upper limit of normal lactate value, should raise concern about severe trauma.
In a prospective study on 277 children, Ramanathan and colleagues (11) showed that a lactate concentration above 4.7 mmol/L strongly suggested severe injury, while a lower value is reassuring for not having an injury. In our report, higher lactate values around 4.7 mmol/L (thresholds of 4.5 and 5.0 mmol/L) were highly specific for severe trauma. Contrary to the prospective study, a lactate value lower than 4.7 mmol/L was not necessarily reassuring against severe injury. At the time of writing, the authors found an article describing similar initial lactate cutoffs in pediatric trauma; 5.1 mmol/L for mortality (AUC, 0.87 [95% confidence interval, 0.84-0.90]); sensitivity, 65.8% [48.6-80.4]; specificity, 92.7% [90.1-94.8]; and odds ratio, 6.43), 3.2 mmol/L for transfusion (AUC, 0.73 [0.69-0.77]; sensitivity, 51.9% [45.3-58.4]; specificity, 84.4% [79.9-88.3]; and odds ratio, 2.82), and 2.9 mmol/L for surgical intervention (AUC, 0.60 [0.56-0.65]; sensitivity, 49.4% [38.1-60.7]; specificity, 67.2% [62.8-71.5]; and odds ratio, 2.82) (13).
The PPV improved with increasing lactate cutoffs, but overall, PPVs were 10.9%-53.9% while NPVs were 91.7%-95.5%. Unlike sensitivity and specificity, PPV and NPV vary with prevalence levels. The prevalence of severe trauma in our cohort was low (9.4%), which means that a higher NPV does not necessarily prove that the test is beneficial in deciding whether the trauma is severe. In effect, some patients without severe trauma may still have high lactate values.
In our cohort, head injury was the most common type of injury (Table 2), which is also the most prevalent cause of trauma mortality in relevant studies (14-16). We found correlations of admission lactate positive with ISS and negative with GCS, indicating that patients with severe head trauma tended to have higher lactate values. Fu et al. (16) studied admission lactate values in 213 children with moderate and severe traumatic brain injuries. They reported that lactate value was an independent risk factor for mortality (odds ratio, 1.19; 95% confidence interval, 1.002-1.41) and that children with a lactate of 2 mmol/L or smaller had a 3.2% mortality, whereas those with a lactate higher than 2 mmol/L had a 46.6% mortality (P < 0.001).
This retrospective study had inherent limitations in data analysis and interpretation. The patients were all from a single center with modest pediatric trauma capacity, which may restrict the generalizability to large multispecialty pediatric institutions. However, this limitation might be counterbalanced by the extensive period and substantial sample size. An important limitation of the study is that we did not account for factors affecting lactate concentration, such as the timing between initial blood draw and injury, lack of information about prehospital resuscitation, or occurrence of sampling errors with hemolyzed specimens. Finally, the sensitivity and specificity might be skewed by the substantial proportion of patients with only mild injury.
To establish a more conclusive role of serum lactate as a prognostic biomarker for severe trauma, future research should include larger cohorts of severely injured children with adjustments made for different patient characteristics as well as specific clinical and injury features. It will be helpful to address the challenges of interpreting serum lactate concentration in children by excluding hemolyzed samples or including data on the time of blood draw relative to the traumatic event. Two adult trauma studies exploring lactate clearance yielded favorable findings, wherein poor lactate clearance was highly predictive of mortality (17,18). Hence, multiple sequential testing may be clinically relevant in accounting for factitious elevation or temporal changes in lactate values from the prehospital phase, ED, and hospital stay. Integrating serum lactate into different nonspecific trauma scoring systems and comparing their predictive performance to traditional prediction models may shed more light on the utility of lactate in pediatric trauma evaluations.
In conclusion, admission lactate demonstrates high specificity, a good rule-in capacity, for severe trauma in children at the cost of inadequate sensitivity. It should be used in conjunction with other screening tools when ruling out severe trauma.

Notes

Conflicts of interest

No potential conflicts of interest relevant to this article were reported.

Funding sources

No funding source relevant to this article was reported.

Author contributions

Conceptualization, Methodology, and Visualization: all authors

Software, Formal analysis, and Project administration: ZT, EJ, SK, BB, and KF

Validation: ZT, EJ, SK, KB, CH, and KF

Investigation and Data curation: EJ, SK, BB, KB, and CH

Resources: ZT, EJ, SK, BB, KB, and CH

Supervision: ZT, SK, and KF

Writing-original draft: ZT, EJ, SK, BB, and KF

Writing-review and editing: all authors

All authors read and approved the final manuscript.

Fig. 1.
Receiver operating characteristic curve of lactate. The optimal cutoff was 1.9 (black square), which had an area under the curve of 0.69 (95% confidence interval, 0.61-0.77), resulting in the maximal combined sensitivity (75.4%) and specificity (57.9%). The diagonal indicates the baseline, of which the area under the curve is 0.50. Each number of the line indicates each cutoff (see details in Table 3).
pemj-2025-01305f1.jpg
Fig. 2.
Receiver operating characteristic curve of Glasgow Coma Scale. The optimal cutoff was 9.0 (black square), which had an area under the curve of 0.72 (95% confidence interval, 0.64-0.79), resulting in the maximal combined sensitivity (45.3%) and specificity (96.7%).
pemj-2025-01305f2.jpg
Fig. 3.
Receiver operating characteristic curve of Injury Severity Score. The optimal cutoff was 10.0 (black square), which had an area under the curve of 0.92 (95% confidence interval, 0.0.89-0.95), resulting in the maximal combined sensitivity (90.6%) and specificity (77.3%).
pemj-2025-01305f3.jpg
Table 1.
Characteristics of the study population
Characteristics Total (N = 566) Severe trauma (N = 53) Non-severe trauma (N = 513) P value
Age, y 14.4 (9.1-16.6) 15.7 (14.2-17.3) 14.2 (8.8-16.5) 0.002
Age category, y 0.053
 0-2 40 (7.1)* 1 (1.9) 39 (7.6)
 3-8 100 (17.7)* 5 (9.4) 95 (18.5)
 9-17 426 (75.3)* 47 (88.7) 379 (73.9)
Mechanism of injury < 0.001
 Motor vehicular collision 300 (53.0) 25 (47.2) 275 (53.6)
 Fall 55 (9.7) 2 (3.8) 53 (10.3)
 Car vs. pedestrian 49 (8.7) 4 (7.5) 45 (8.8)
 All-terrain vehicle 36 (6.4) 5 (9.4) 31 (6.0)
 Gunshot 35 (6.2) 7 (13.2) 28 (5.5)
 Non-accidental 24 (4.2) 3 (5.7) 21 (4.1)
 Sports 12 (2.1) 0 (0) 12 (2.3)
 Bicycle 8 (1.4) 0 (0) 8 (1.6)
 Others 47 (8.3) 7 (13.2) 40 (7.8)
Admission lactate, mmol/L 1.7 (1.3-2.5) 2.5 (1.9-3.8) 1.7 (1.2-2.4) < 0.001
Secondary outcomes
 Glasgow Coma Scale 15.0 (15.0-15.0) 14.0 (3.0-15.0) 15.0 (15.0-15.0) < 0.001
 Injury Severity Score 5.0 (1.0-10.0) 25.0 (17.0-35.0) 5.0 (1.0-9.0) < 0.001
 Hospital length of stay, d 1.0 (1.0-3.0) 7.0 (4.0-17.0) 1.0 (1.0-2.0) 0.923
Initial disposition < 0.001
 Hospitalization, overall 402 (71.0) 36 (67.9) 366 (71.3)*
  Intensive care unit 218 (38.5) 34 (64.2) 184 (35.9)
  General ward 184 (32.5) 2 (3.8) 182 (35.5)
 Operating room 48 (8.5) 16 (30.2) 32 (6.2)*
 Discharge 116 (20.5) 1 (1.9) 115 (22.4)*

Values are expressed as medians (interquartile ranges) or numbers (%).

* The sums of proportions are not equal to 100% due to rounding.

Table 2.
Primary injury types (N = 566)*
Injury type Data
No injury 232 (41.0)
Head injury (closed head injury/skull fracture/intracranial hemorrhage) 146 (25.8)
Extremity fractures 76 (13.4)
Pulmonary (lung contusion/hemothorax) 35 (6.2)
Spine injury/fracture 29 (5.1)
Intraabdominal solid organ (liver/kidney/spleen) 27 (4.8)
Bowel injury 11 (1.9)
Laceration 6 (1.1)
Genitourinary injury 4 (0.7)

Values are expressed as numbers (%).

* In case of multiple injuries, the most representative one was chosen based on clinical severity.

Table 3.
Lactate cutoffs in predicting severe trauma
Lactate, mmol/L Sensitivity (%) Specificity (%) PPV* (%) NPV* (%) AUC (95% CI)
1.0 96.2 9.2 10.9 95.5 NA
1.5 81.3 37.6 13.1 94.6 NA
1.9 (optimal) 75.4 57.9 17.1 95.3 0.69 (0.61-0.77)
2.0 69.8 61.6 15.8 95.2 NA
2.5 52.8 76.0 18.5 94.0 NA
3.0 34.0 84.4 18.4 92.5 NA
3.5 28.3 91.0 24.6 92.5 NA
4.0 24.5 94.0 29.6 92.3 NA
4.5 24.5 96.9 44.8 92.6 NA
5.0 20.8 97.5 45.8 92.3 NA
5.5 18.9 97.7 45.5 92.1 NA
6.0 13.2 98.8 53.9 91.7 NA

* Estimated for the prevalence of severe trauma held constant at 10.3%.

PPV: positive predictive value, NPV: negative predictive value, AUC: area under the curve, CI: confidence interval.

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