A Systematic Review of Hospital Trauma Team Activation Criteria for Children

Computer Simulation to Assess Emergency Department Length of Stay in Pediatric Traumatic Brain Injury

OBJECTIVES

Our study aimed to identify how emergency department (ED) arrival rate, process of care, and physical layout can impact ED length of stay (LOS) in pediatric traumatic brain injury care.

METHODS

Process flows and value stream maps were developed for 3 level I pediatric trauma centers. Computer simulation models were also used to examine "what if" scenarios based on ED arrival rates.

RESULTS

Differences were observed in prearrival preparation time, ED physical layouts, and time spent on processes. Shorter prearrival preparation time, trauma bed location far from diagnostic or treatment areas, and ED arrival rates that exceed 20 patients/day prolonged ED LOS. This was particularly apparent in 1 center where computer simulation showed that relocation of trauma beds can reduce ED LOS regardless of the number of patients that arrive per day.

CONCLUSIONS

Exceeding certain threshold ED arrival rates of children with traumatic brain injury can substantially increase pediatric trauma center ED LOS but modifications to ED processes and bed location may mitigate this increase.

Comparison of nine trauma scoring systems in prediction of inhospital outcomes of pediatric trauma patients: a multicenter study

Hereby, we aimed to comprehensively compare different scoring systems for pediatric trauma and their ability to predict in-hospital mortality and intensive care unit (ICU) admission. The current registry-based multicenter study encompassed a comprehensive dataset of 6709 pediatric trauma patients aged ≤ 18 years from July 2016 to September 2023. To ascertain the predictive efficacy of the scoring systems, the area under the receiver operating characteristic curve (AUC) was calculated. A total of 720 individuals (10.7%) required admission to the ICU. The mortality rate was 1.1% (n = 72). The most predictive scoring system for in-hospital mortality was the adjusted trauma and injury severity score (aTRISS) (AUC = 0.982), followed by trauma and injury severity score (TRISS) (AUC = 0.980), new trauma and injury severity score (NTRISS) (AUC = 0.972), Glasgow coma scale (GCS) (AUC = 0.9546), revised trauma score (RTS) (AUC = 0.944), pre-hospital index (PHI) (AUC = 0.936), injury severity score (ISS) (AUC = 0.901), new injury severity score (NISS) (AUC = 0.900), and abbreviated injury scale (AIS) (AUC = 0.734). Given the predictive performance of the scoring systems for ICU admission, NTRISS had the highest predictive performance (AUC = 0.837), followed by aTRISS (AUC = 0.836), TRISS (AUC = 0.823), ISS (AUC = 0.807), NISS (AUC = 0.805), GCS (AUC = 0.735), RTS (AUC = 0.698), PHI (AUC = 0.662), and AIS (AUC = 0.651). In the present study, we concluded the superiority of the TRISS and its two derived counterparts, aTRISS and NTRISS, compared to other scoring systems, to efficiently discerning individuals who possess a heightened susceptibility to unfavorable consequences. The significance of these findings underscores the necessity of incorporating these metrics into the realm of clinical practice.

Accuracy of the American College of Surgeons Minimum Criteria for Full Trauma Team Activation for Children

OBJECTIVE

Pediatric trauma centers use reports from emergency medical service providers to determine if a trauma team should be sent to the emergency department to prepare to care for the patient. Little scientific evidence supports the current American College of Surgeons (ACS) indicators for trauma team activation. The objective of this study was to determine the accuracy of the ACS Minimum Criteria for Full Trauma Team Activation for children as well as the accuracy of the modified criteria used at the local sites for trauma activation.

METHODS

Emergency medical service providers who transported an injured child aged 15 years or younger to a pediatric trauma center in 1 of 3 cities were interviewed after emergency department arrival. Emergency medical service providers were asked if each of the activation indicators were present based on their evaluation. The need for full trauma team activation was determined through a medical record review using a published criterion standard definition. Undertriage and overtriage rates and positive likelihood ratios (+LRs) were calculated.

RESULTS

Emergency medical service provider interviews were conducted and outcome data were obtained for 9483 children. There were 202 (2.1%) cases that met the criterion standard for need for trauma team activation. Based on the ACS Minimum Criteria, 299 (3.0%) cases should have received a trauma activation. The ACS Minimum Criteria undertriaged 44.1% and overtriaged 20% (+LR, 27.9; 95% confidence interval, 23.1-33.7). Based on the actual activation status using the local criteria, 238 cases received a full trauma activation, 45% were undertriaged, and 1.4% were overtriaged (+LR, 40.1; 95% confidence interval, 32.4-49.7). There was 97% agreement between the ACS Minimum Criteria and the actual local activation status at the receiving institution.

CONCLUSIONS

The ACS Minimum Criteria for Full Trauma Team Activation for children have a high rate of undertriage. Changes that individual institutions have made to improve the accuracy of activations at their institutions seem to have had a limited effect on decreasing undertriage.

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.

Comparison of age-adjusted shock indices as predictors of injury severity in paediatric trauma patients immediately after emergency department triage: A report from the Korean multicentre registry

INTRODUCTION

Shock index paediatric-adjusted (SIPA) was presented for early prediction of mortality and trauma team activation in paediatric trauma patients. However, the derived cut-offs of normal vital signs were based on old references. We established alternative SIPAs based on the other commonly used references and compared their predictive values.

METHODS

We performed a retrospective review of all paediatric trauma patients aged 1-15 years in the Emergency Department (ED)-based Injury In-depth Surveillance (EDIIS) database from January 1, 2011 to December 31, 2019. A total of 4 types of SIPA values were obtained based on the references as follows: uSIPA based on the Nelson textbook of paediatrics 21st ed., SIATLS based on the ATLS 10th guideline, SIPALS based on the PALS 2020 guideline, and SIPA. In each SIPA group, the cut-off was established by dividing the group into 4 subgroups: toddler (age 1-3), preschooler (age 4-6), schooler (age 7-12), and teenager (age 13-15). We performed an ROC analysis and calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to compare the predicted values of each SIPA in mortality, ICU admission, and emergent surgery or intervention.

RESULTS

A total of 332,271 patients were included. The proportion of patients with an elevated shock index was 14.9 % (n = 49,347) in SIPA, 22.8 % (n = 75,850) in uSIPA, 0.3 % (n = 1058) in SIATLS, and 4.3 % (n = 14,168) in SIPALS. For mortality, uSIPA achieved the highest sensitivity (57.0 %; 95 % confidence interval 56.9 %-57.2 %) compared to SIPA (49.4 %, 95 % CI 49.2 %-49.5 %), SIATLS (25.5 %, 95 % CI 25.4 %-25.7 %), and SIPALS (43.8 %, 95 % CI 43.7 %-44.0 %), but there were no significant differences in the negative predictive value (NPV) or area under the curve (AUC). The positive predictive value (PPV) was highest in SIATLS (5.7 %, 95 % CI 5.6 %-5.8 %) compared to SIPA (0.2 %, 95 % CI 0.2 %-0.3 %), uSIPA (0.2 %, 95 % CI 0.2 %-0.2 %), and SIPALS (0.7 %, 95 % CI 0.7 %-0.8 %). The same findings were presented in ICU admission and emergent operation or intervention.

CONCLUSION

The ATLS-based shock index achieved the highest PPV and specificity compared to SIPA, uSIPA, and SIPALS for adverse outcomes in paediatric trauma.

Pediatric Trauma and Trauma Team Activation in a Swiss Pediatric Emergency Department: An Observational Cohort Study

BACKGROUND

Trauma is one of the most common causes of death in childhood, but data on severely injured Swiss children are absent from existing national registries. Our aim was to analyze trauma activations and the profiles of critically injured children at a tertiary, non-academic Swiss pediatric emergency department (PED). In the absence of a national pediatric trauma database, this information may help to guide the design of infrastructure, processes within organizations, training, and policies.

METHODS

A retrospective analysis of pediatric trauma patients in a prospective resuscitation database over a 2-year period. Critically injured trauma patients under the age of 16 years were included. Patients were described with established triage and injury severity scales. Statistical evaluation included logistic regression analysis.

RESULTS

A total of 82 patients matched one or more of the study inclusion criteria. The most frequent age group was 12-15 years, and 27% were female. Trauma team activation (TTA) occurred with 49 patients (59.8%). Falls were the most frequent mechanism of injury, both overall and for major trauma. Road-traffic-related injuries had the highest relative risk of major trauma. In the multivariate analysis, patients receiving medicalized transport were more likely to trigger a TTA, but there was no association between TTA and age, gender, or Injury Severity Score (ISS). Nineteen patients (23.2%) sustained major trauma with an ISS > 15. Injuries of Abbreviated Injury Scale severity 3 or greater were most frequent to the head, followed by abdomen, chest, and extremities. The overall mortality rate in the cohort was 2.4%. Conclusions: Major trauma presentations only comprise a small proportion of the total patient load in the PED, and trauma team activation does not correlate with injury severity. Low exposure to high-acuity patients highlights the importance of deliberate learning and simulation for all professionals in the PED. Our findings indicate that high priority should be given to training in the management of severely injured children in the PED. The leading major trauma mechanisms were preventable, which should prompt further efforts in injury prevention.

Predicting Complicated Mild Traumatic Brain Injury in Adolescent Trauma to Enhance Clinical Decisions in Imaging

BACKGROUND

The Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury algorithm is used to identify children at low risk of clinically significant traumatic brain injuries to reduce computed tomography (CT) exposure. Adapting PECARN rules based on population-specific risk stratification has been suggested to improve diagnostic accuracy.

OBJECTIVE

This study sought to identify center-specific patient variables, beyond PECARN rules, that may enhance the identification of patients requiring neuroimaging.

METHODS

This single-center, retrospective cohort study was conducted from July 1, 2016, to July 1, 2020, in a Southwestern U.S. Level II pediatric trauma center. The inclusion criteria were adolescents (10-15 years), Glasgow Coma Scale (13-15), with a confirmed mechanical blow to the head. Patients without a head CT were excluded. Logistic regression was performed to identify additional complicated mild traumatic brain injury predictor variables beyond the PECARN.

RESULTS

There were 136 patients studied; 21 (15%) presented with a complicated mild traumatic brain injury. Relative to motorcycle collision or all-terrain vehicle trauma (odds ratio [OR] 211.75, 95% confidence interval, CI [4.51, 9931.41], p < .001), an unspecified mechanism (OR 42.0, 95% CI [1.30, 1350.97], p = .03) and consult activation (OR 17.44, 95% CI [1.75, 173.31], p = .01) were significantly associated with complicated mild traumatic brain injury.

CONCLUSIONS

We identified additional factors associated with complex mild traumatic brain injury, including motorcycle collision and all-terrain vehicle trauma, unspecified mechanism, and consult activation that are not in the PECARN imaging decision rule. Adding these variables may aid in determining the need for appropriate CT scanning.

Evaluation of activation criteria in paediatric multi-trauma

Objective

To explore the optimal set of trauma activation criteria predicting paediatric patients' need for acute care following multi-trauma, with particular attention to Glasgow Coma Scale (GCS) cut-off value.

Methods

A retrospective cohort study of paediatric multi-trauma patients aged 0 to 16 years, performed at a Level 1 paediatric trauma centre. Trauma activation criteria and GCS levels were examined with respect to patients' need for acute care, defined as: direct to operating room disposition, intensive care unit admission, need for acute interventions in the trauma room, or in-hospital death.

Results

We enrolled 436 patients (median age 8.0 years). The following predicted need for acute care: GCS <14 (adjusted odds ratio [aOR] 23.0, 95% confidence interval [CI]: 11.5 to 45.9, P < 0.001), hemodynamic instability: (aOR 3.7, 95% CI: 1.2-8.1, P = 0.01), open pneumothorax/flail chest (aOR: 20.0, 95% CI: 4.0 to 98.7, P < 0.001), spinal cord injury (aOR 15.4, 95% CI; 2.4 to 97.1, P = 0.003), blood transfusion at the referring hospital (aOR: 7.7, 95% CI: 1.3 to 44.2, P = 0.02) and GSW to the chest, abdomen, neck, or proximal extremities (aOR 11.0, 95% CI; 1.7 to 70.8, P = 0.01). Using these activation criteria would have decreased over- triage by 10.7%, from 49.1% to 37.2% and under-triage by 1.3%, from 4.7% to 3.5%, in our cohort of patients.

Conclusions

Using GCS<14, hemodynamic instability, open pneumothorax/flail chest, spinal cord injury, blood transfusion at the referring hospital, and GSW to the chest, abdomen, neck of proximal extremities, as T1 activation criteria could decrease over- and under-triage rates. Prospective studies are needed to validate the optimal set of activation criteria in paediatric patients.

Adding age-adjusted shock index to the American College of Surgeons' trauma team activation criteria to predict severe injury in children

BACKGROUND

The American College of Surgeons (ACS) requires trauma centers to use six minimum criteria (ACS-6) for full trauma team activation. Our goal was to evaluate the effect of adding age-adjusted shock index (SI) to the ACS-6 for the prediction of severe injury among pediatric trauma patients with the hypothesis that SI would significantly improve sensitivity with an acceptable decrease in specificity.

METHODS

We performed a secondary analysis of prospectively collected EMS and trauma registry data from two urban pediatric trauma centers. Age-adjusted SI thresholds were calculated as heart rate divided by systolic blood pressure using 2020 Pediatric Advanced Life Support SI vital sign ranges and previously published Shock Index, Pediatric Adjusted (SIPA) thresholds. The primary outcome was a composite of emergency operative (within 1 hour of arrival) or emergency procedural intervention (EOPI) or Injury Severity Score (ISS) greater than 15. Sensitivities, specificities, and 95% CIs were calculated for the ACS-6 alone and in combination with age-adjusted SI.

RESULTS

There were 8,078 patients included; 20% had an elevated age-adjusted SI and 17% met at least one ACS minimum criterion; 1% underwent EOPI; and 17% had ISS >15. Sensitivity and specificity of the ACS-6 for EOPI or ISS > 5 were 45% (95% confidence interval [CI], 41-50%) and 89% (95% CI, 81-96%). Inclusion of Pediatric Advanced Life Support-SI and SIPA resulted in sensitivities of 51% (95% CI, 47-56%) and 69% (95% CI, 65-72%), and specificities of 80% (95% CI, 71-89%) and 60% (95% CI, 53-68%), respectively. Similar trends were seen for each secondary outcome.

CONCLUSION

In this cohort of pediatric trauma registry patients, the addition of SIPA to the ACS-6 for trauma team activation resulted in significantly increased sensitivity for EOPI or ISS greater than 15 but poor specificity. Future investigation should explore using age-adjusted shock index in a two-tiered trauma activation system, or in combination with novel triage criteria, in a population-based cohort.

LEVEL OF EVIDENCE

Diagnostic Tests or Criteria; Level II.

Exploring the factors that influence trauma team activation in emergency department staff

Regional trauma networks enable the rapid and safe management and transfer of patients with traumatic injury between designated trauma units and one of 27 major trauma centres throughout the UK. Multispecialty trauma teams are available 24 hours a day, seven days a week, and are activated immediately upon receipt of a patient presenting with major trauma. With most serious trauma patients going direct to major trauma centres rather than a less specialised hospital-based trauma unit, it can be challenging for hospital-based trauma unit staff to gain experience and skill in this area, leading to potential inconsistencies in the process of activating the trauma team. The aim of this service evaluation was to identify factors influencing the decision to activate the trauma team in emergency department (ED) staff working within a 700-bed trauma unit. A questionnaire was sent to 107 staff and 70 completed it, a response rate of 65%. Results indicated that shortfalls in trauma-specific training, lack of clinical experience, undefined roles and responsibilities, department culture, ambulance handover, knowledge of clinical guidelines and previous experience of trauma team activation all affected the decision to activate the trauma team. Trauma-specific training and the support of senior staff could enhance confidence and appropriate trauma team activation rates.

Predicting morbidity and mortality in Australian paediatric trauma with the Paediatric Age-Adjusted Shock Index and Glasgow Coma Scale

BACKGROUND

Paediatric age-adjusted shock index (SIPA) has emerged as a predictor of morbidity and mortality in trauma. Poor sensitivity and low generalisability demonstrated in previous studies have limited its use. We evaluate the use of SIPA in the general Australian paediatric trauma population and the combination of SIPA with GCS.

METHODS

All patients from January 2015 to August 2020 at a major Australian paediatric trauma centre were reviewed. Pre-arrival SIPA (pSIPA) and arrival SIPA (aSIPA) were calculated. If SIPA was elevated or the Glasgow Coma Scale ≤ 13, SIPA with mental state (SIPAms) was marked positive for pre-arrival (pSIPAms) and arrival (aSIPAms) respectively.

RESULTS/DISCUSSION

Data from 480 patients were analysed. pSIPA and aSIPA poorly predicted outcomes of morbidity. Only aSIPA predicted mortality. However, both pre-arrival and arrival SIPAms variables predict mortality, major trauma (ISS≥12), hospital LOS, need for ICU admission, and major surgery. Furthermore, median ISS and lactate were significantly higher in positive pSIPA, aSIPA, pSIPAms, and aSIPAms groups than negative. aSIPAms has a sensitivity of 76% and specificity of 70% for major trauma.

CONCLUSION

Broad inclusion criteria reduce SIPA's ability to predict morbidity. Combining it with GCS improves this and is most valuable when calculated at arrival. In addition, the score is more reliable for major trauma (ISS≥12). Future studies should evaluate the use of SIPAms in activation criteria.

Assessing the Necessity for the "Joint Above and Below" Radiography Approach for Lower-extremity Long Bone Fractures in Children

OBJECTIVES

A common strategy for evaluation of extremity fractures is the "joint above and below" (JAB) radiograph approach, which includes dedicated imaging of the joint proximal and distal to a fracture independent of clinical suspicion for an injury involving the joint. The incidence of concomitant ipsilateral lower-extremity fractures or dislocations associated with lower-extremity long bone fractures in children has not been commonly reported and represents an evidential gap for determining a radiograph approach. Our purpose was to determine the frequency of and risk factors for concomitant ipsilateral lower-extremity fractures or dislocations.

METHODS

A retrospective study of children aged 1 to 17 years treated at an academic medical center emergency department from 2015 to 2018 with any fracture involving the tibia, fibula, or femur. Children with pathologic fractures, transferred from another facility, and/or designated as a level I trauma were excluded. The primary outcome was the prevalence of a concomitant bony injury (fracture or dislocation) at a distinct site in the same extremity. Differences between the concomitant bony injury group and single injury group were characterized using Fisher exact tests. Regression analysis was used to determine predictors of concomitant bony injuries, including age, sex, and mechanism of injury (with injuries requiring level II or III trauma activation classified as high risk).

RESULTS

During the study period, 241 patients with lower-extremity long bone fractures were included. Complete JAB radiographs, defined as dedicated orthogonal radiographs of the joint proximal to and distal to the fracture site, were taken in 85 (35.3%) of 241 patients. Concomitant bony injuries were found in 9 (3.73%) of 241 patients (95% confidence interval, 1.7-7.0%). No additional concomitant bony injuries were identified at follow-up. When comparing patients with and without concomitant bony injuries, there was no significant difference in age (P = 0.34) and sex (P = 0.73). However, patients with a high-risk injury were more likely to have a concomitant bony injury (P < 0.01; odds ratio, 21.9; 95% confidence interval, 3.6-131.5).

CONCLUSIONS

Concomitant ipsilateral lower-extremity fractures or dislocations are uncommon in children sustaining tibia, fibula, and/or femur fractures. Although the JAB approach to radiographs may be useful in identifying additional injuries in children with lower-extremity injuries resulting from a "high-risk" mechanisms, its overall yield is low. To provide safe, cost-effective care, providers should continue to value clinical suspicion, history, and physical examination findings to guide selection of radiographs in those with lower-extremity long bone fractures as significant fractures can typically be identified with limited imaging in patients with low-risk injury mechanisms.

Machine learning for outcome predictions of patients with trauma during emergency department care

OBJECTIVES

To develop and evaluate a machine learning model for predicting patient with trauma mortality within the US emergency departments.

METHODS

This was a retrospective prognostic study using deidentified patient visit data from years 2007 to 2014 of the National Trauma Data Bank. The predictive model intelligence building process is designed based on patient demographics, vital signs, comorbid conditions, arrival mode and hospital transfer status. The mortality prediction model was evaluated on its sensitivity, specificity, area under receiver operating curve (AUC), positive and negative predictive value, and Matthews correlation coefficient.

RESULTS

Our final dataset consisted of 2 007 485 patient visits (36.45% female, mean age of 45), 8198 (0.4%) of which resulted in mortality. Our model achieved AUC and sensitivity-specificity gap of 0.86 (95% CI 0.85 to 0.87), 0.44 for children and 0.85 (95% CI 0.85 to 0.85), 0.44 for adults. The all ages model characteristics indicate it generalised, with an AUC and gap of 0.85 (95% CI 0.85 to 0.85), 0.45. Excluding fall injuries weakened the child model (AUC 0.85, 95% CI 0.84 to 0.86) but strengthened adult (AUC 0.87, 95% CI 0.87 to 0.87) and all ages (AUC 0.86, 95% CI 0.86 to 0.86) models.

CONCLUSIONS

Our machine learning model demonstrates similar performance to contemporary machine learning models without requiring restrictive criteria or extensive medical expertise. These results suggest that machine learning models for trauma outcome prediction can generalise to patients with trauma across the USA and may be able to provide decision support to medical providers in any healthcare setting.

Critically Ill Children in a Swiss Pediatric Emergency Department With an Interdisciplinary Approach: A Prospective Cohort Study

Objective: Delivery of prompt and adequate care for critically ill and injured children presenting to the pediatric emergency department (PED) is paramount for optimal outcomes. Knowledge of the local epidemiology, patient profile, and presentation modes are key for organizational planning, staff education strategy, and optimal care in a PED. Our aim was to analyze the profile of critically ill and injured children admitted to a tertiary, non-academic Swiss PED, to investigate potential risk factors associated with admission to the pediatric intensive care unit (PICU), and the outcomes mortality and PICU admission. Methods: Prospective cohort study of critically ill and injured children presenting to the PED over a two-year period (2018-2019). Inclusion criteria were Australasian triage scale category (ATS) 1, trauma team activation (TTA), medical emergency response (MER) activation, additional critical care consult, and transfer to an outside hospital. Results: Of 42,579 visits during the two-year period, 347 presentations matched the inclusion criteria (0.81%). Leading presentations were central nervous system (CNS) disorders (26.2%), trauma (25.1%), and respiratory emergencies (24.2%). 288 out of 347 cases (83%) arrived during the day or evening with an even distribution over the days of the week. 128 out of 347 (37%) arrived unexpectedly as walk-ins. 233 (67.15%) were ATS category 1. 51% of the cohort was admitted to PICU. Australasian triage scale category 1 was significantly more common in this group (p = 0.0001). Infants with respiratory disease had an increased risk of PICU transfer compared to other age groups (OR 4.18 [95%CI 2.46, 7.09] p = 0.0001), and this age group presented mainly as walk-in (p = 0.0001). Pediatric intensive care unit admissions had a longer hospital stay (4 [2, 8] days vs. 2 [1, 4] days, p = 0.0001) compared to other patients. 0.045% of all PED patients had to be transferred out. Three deaths (0.86%) occurred in the PED, 10 patients died in the PICU (2.9%). Conclusions: High acuity presentations in the PED were rare, more likely to be young with CNS disorders, trauma and respiratory diseases. A significant proportion were unexpected walk-in presentations, mainly during day and evening shifts. Low exposure to high-acuity patients highlights the importance of deliberate learning and simulation for all professionals in the PED.

Pediatric trauma triage: A Pediatric Trauma Society Research Committee systematic review

BACKGROUND

Significant variability exists in the triage of injured children with most systems using mechanism of injury and/or physiologic criteria. It is not well established if existing triage criteria predict the need for intervention or impact morbidity and mortality. This study evaluated existing evidence for pediatric trauma triage. Questions defined a priori were as follows: (1) Do prehospital trauma triage criteria reduce mortality? (2) Do prehospital trauma scoring systems predict outcomes? (3) Do trauma center activation criteria predict outcomes? (4) Do trauma center activation criteria predict need for procedural or operative interventions? (5) Do trauma bay pediatric trauma scoring systems predict outcomes? (6) What secondary triage criteria for transfer of children exist?

METHODS

A structured, systematic review was conducted, and multiple databases were queried using search terms related to pediatric trauma triage. The literature search was limited to January 1990 to August 2019. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was applied with the methodological index for nonrandomized studies tool used to assess the quality of included studies. Qualitative analysis was performed.

RESULTS

A total of 1,752 articles were screened, and 38 were included in the qualitative analysis. Twelve articles addressed questions 1 and 2, 21 articles addressed question 3 to 5, and five articles addressed question 6. Existing literature suggest that prehospital triage criteria or scoring systems do not predict or reduce mortality, although selected physiologic parameters may. In contrast, hospital trauma activation criteria can predict the need for procedures or surgical intervention and identify patients with higher mortality; again, physiologic signs are more predictive than mechanism of injury. Currently, no standardized secondary triage/transfer protocols exist.

CONCLUSION

Evidence supporting the utility of prehospital triage criteria for injured children is insufficient, while physiology-based trauma system activation criteria do appropriately stratify injured children. The absence of strong evidence supports the need for further prehospital and secondary transfer triage-related research.

LEVEL OF EVIDENCE

Systematic review study, level II.

ISS alone, is not sufficient to correctly assign patients post hoc to trauma team requirement

Purpose

An injury severity score (ISS) ≥ 16 alone, is commonly used post hoc to define the correct activation of a trauma team. However, abnormal vital functions and the requirement of life-saving procedures may also have a role in defining trauma team requirement post hoc. The aim of this study was to describe their prevalence and mortality in severely injured patients and to estimate their potential additional value in the definition of trauma team requirement as compared to the definition based on ISS alone.

Methods

Retrospective analysis of a trauma registry including patients with trauma team activation from the years 2009 until 2015, who were 16 years of age or older and were brought to the trauma center directly from the scene. Patients were divided into a group with an ISS ≥ 16 vs. ISS < 16. For analysis a predefined list of abnormal vital functions and life-saving interventions was used.

Results

58,723 patients were included in the study (N = 32,653 with ISS ≥ 16; N = 26,070 with ISS < 16). From the total number of patients that required life-saving procedures or presented with abnormal vital functions 29.1% were found in the ISS < 16 group. From the ISS < 16 group, 36.7% of patients required life-saving procedures or presented with abnormal vital signs. The mortality of those was 8.1%.

Conclusions

Defining the true requirement of trauma team activation post hoc by using ISS ≥ 16 alone does miss a considerable number of subjects who require life-saving interventions or present with abnormal vital functions. Therefore, life-saving interventions and abnormal vital functions should be included in the definitions for trauma team requirement. Further studies have to evaluate, which life-saving procedures and abnormal vital functions are most relevant.