Validating the ATLS Shock Classification for Predicting Death, Transfusion, or Urgent Intervention

Comparison of Vital Sign Cutoffs to Identify Children With Major Trauma

Importance

Vital signs are essential components in the triage of injured children. The Advanced Trauma Life Support (ATLS) and Pediatric Advanced Life Support (PALS) physiologic criteria are frequently used for trauma assessments.

Objective

To evaluate the performance of ATLS and PALS criteria vs empirically derived criteria for identifying major trauma in children.

Design, Setting, and Participants

This retrospective cohort study used 2021 American College of Surgeons Trauma Quality Improvement Program (TQIP) data contributed by US trauma centers. Included encounters involved pediatric patients (aged <18 years) with severe injury, excluding those who experienced out-of-hospital cardiac arrest, were receiving mechanical ventilation, or were transferred from another facility. Data were analyzed between April 9 and December 21, 2023.

Exposure

Initial hospital vital signs, including heart rate, respiratory rate, and systolic blood pressure (SBP).

Main Outcome and Measures

Major trauma, determined by the Standard Triage Assessment Tool, a composite measure of injury severity and interventions performed. Multivariable models developed from PALS and ATLS vital sign criteria were compared with models developed from the empirically derived criteria using the area under the receiver operating characteristic curve. Validation of the findings was performed using the 2019 TQIP dataset.

Results

A total of 70 748 patients (median [IQR] age, 11 [5-15] years; 63.4% male) were included, of whom 3223 (4.6%) had major trauma. The PALS criteria classified 31.0% of heart rates, 25.7% of respiratory rates, and 57.4% of SBPs as abnormal. The ATLS criteria classified 25.3% of heart rates, 4.3% of respiratory rates, and 1.1% of SBPs as abnormal. Among children with all 3 vital signs documented (64 326 [90.9%]), PALS had a sensitivity of 88.4% (95% CI, 87.1%-89.3%) and specificity of 25.1% (95% CI, 24.7%-25.4%) for identifying major trauma, and ATLS had a sensitivity of 54.5% (95% CI, 52.7%-56.2%) and specificity of 72.9% (95% CI, 72.6%-73.3%). The empirically derived cutoff vital sign z scores had a sensitivity of 80.0% (95% CI, 78.5%-81.3%) and specificity of 48.7% (95% CI, 48.3%-49.1%) and area under the receiver operating characteristic curve of 70.9% (95% CI, 69.9%-71.8%), which was similar to PALS criteria (69.6%; 95% CI, 68.6%-70.6%) and greater than ATLS criteria (65.4%; 95% CI, 64.4%-66.3%). Validation using the 2019 TQIP database showed similar performance to the derivation sample.

Conclusions and Relevance

These findings suggest that empirically derived vital sign criteria strike a balance between the sensitivity of PALS criteria and the specificity of ATLS criteria in identifying major trauma in children. These criteria may help to identify children at greatest risk of trauma-related morbidity and mortality.

Is the shock index correlated with blood loss? An experimental study on a controlled hemorrhagic shock model in piglets

INTRODUCTION

The quantification of blood loss in a severe trauma patient allows prognostic quantification and the engagement of adapted therapeutic means. The Advanced Trauma Life Support classification of hemorrhagic shock, based in part on hemodynamic parameters, could be improved. The search for reproducible and non-invasive parameters closely correlated with blood depletion is a necessity. An experimental model of controlled hemorrhagic shock allowed us to obtain hemodynamic and echocardiographic measurements during controlled blood spoliation. The primary aim was to demonstrate the correlation between the Shock Index (SI) and blood depletion volume (BDV) during the hemorrhagic phase of an experimental model of controlled hemorrhagic shock in piglets. The secondary aim was to study the correlations between blood pressure (BP) values and BDV, SI and cardiac output (CO), and pulse pressure (PP) and stroke volume during the same phase.

METHODS

We analyzed data from 66 anesthetized and ventilated piglets that underwent blood spoliation at 2 mL.kg-1.min-1 until a mean arterial pressure (MAP) of 40 mmHg was achieved. During this bleeding phase, hemodynamic and echocardiographic measurements were performed regularly.

RESULTS

The correlation coefficient between the SI and BDV was 0.70 (CI 95%, [0.64; 0.75]; p < 0.01), whereas between MAP and BDV, the correlation coefficient was -0.47 (CI 95%, [-0.55; -0.38]; p < 0.01). Correlation coefficient between SI and CO and between PP and stroke volume were - 0.45 (CI 95%, [-0.53; -0.37], p < 0.01) and 0.62 (CI 95%, [0.56; 0.67]; p < 0.01), respectively.

CONCLUSIONS

In a controlled hemorrhagic shock model in piglets, the correlation between SI and BDV seemed strong.

Recommendations for Placement of Bleeding Control Kits in Public Spaces-A Simulation Study

OBJECTIVE

Bleeding control measures performed by members of the public can prevent trauma deaths. Equipping public spaces with bleeding control kits facilitates these actions. We modeled a mass casualty incident to investigate the effects of public bleeding control kit location strategies.

METHODS

We developed a computer simulation of a bomb exploding in a shopping mall. We used evidence and expert opinion to populate the model with parameters such as the number of casualties, the public's willingness to aid, and injury characteristics. Four alternative placement strategies of public bleeding control kits in the shopping mall were tested: co-located with automated external defibrillators (AEDs) separated by 90-second walking intervals, dispersed throughout the mall at 10 locations, located adjacent to 1 exit, located adjacent to 2 exits.

RESULTS

Placing bleeding control kits at 2 locations co-located with AEDs resulted in the most victims surviving (18.2), followed by 10 kits dispersed evenly throughout the mall (18.0). One or 2 kit locations placed at the mall's main exits resulted in the fewest surviving victims (15.9 and 16.1, respectively).

CONCLUSIONS

Co-locating bleeding control kits with AEDs at 90-second walking intervals results in the best casualty outcomes in a modeled mass casualty incident in a shopping mall.

Resuscitation Patterns and Massive Transfusion for the Critical Bleeding Dog-A Multicentric Retrospective Study of 69 Cases (2007-2013)

Objective: To describe resuscitation patterns of critically bleeding dogs, including those receiving massive transfusion (MT). Design: Retrospective study from three universities (2007-2013). Animals: Critically bleeding dogs, defined as dogs who received ≥ 25 ml/kg of blood products for treatment of hemorrhagic shock caused by blood loss. Measurements and Main Results: Sixty-nine dogs were included. Sources of critical bleeding were trauma (26.1%), intra/perioperative surgical period (26.1%), miscellaneous (24.6%), and spontaneous hemoabdomen (23.1%). Median (range) age was 7 years (0.5-18). Median body weight was 20 kg (2.6-57). Median pre-transfusion hematocrit, total protein, systolic blood pressure, and lactate were 25% (10-63), 4.1 g/dl (2-7.1), 80 mm Hg (20-181), and 6.4 mmol/L (1.1-18.2), respectively. Median blood product volume administered was 44 ml/kg (25-137.4). Median plasma to red blood cell ratio was 0.8 (0-4), and median non-blood product resuscitation fluid to blood product ratio was 0.5 (0-3.6). MT was given to 47.8% of dogs. Survival rate was 40.6%. The estimated odds of survival were higher by a factor of 1.8 (95% CI: 1.174, 3.094) for a dog with 1 g/dl higher total protein above reference interval and were lower by a factor of 0.6 (95% CI: 0.340, 0.915) per 100% prolongation of partial thromboplastin time above the reference interval. No predictors of MT were identified. Conclusions: Critical bleeding in dogs was associated with a wide range of resuscitation patterns and carries a guarded to poor prognosis.