Pediatric Mass Casualty: Triage and Planning for the Prehospital Provider

Advancing the scientific study of prehospital mass casualty response through a Translational Science process: the T1 scoping literature review stage

PURPOSE

The European Union Horizon 2020 research and innovation funding program awarded the NIGHTINGALE grant to develop a toolkit to support first responders engaged in prehospital (PH) mass casualty incident (MCI) response. To reach the projects' objectives, the NIGHTINGALE consortium used a Translational Science (TS) process. The present work is the first TS stage (T1) aimed to extract data relevant for the subsequent modified Delphi study (T2) statements.

METHODS

The authors were divided into three work groups (WGs) MCI Triage, PH Life Support and Damage Control (PHLSDC), and PH Processes (PHP). Each WG conducted simultaneous literature searches following the PRISMA extension for scoping reviews. Relevant data were extracted from the included articles and indexed using pre-identified PH MCI response themes and subthemes.

RESULTS

The initial search yielded 925 total references to be considered for title and abstract review (MCI Triage 311, PHLSDC 329, PHP 285), then 483 articles for full reference review (MCI Triage 111, PHLSDC 216, PHP 156), and finally 152 articles for the database extraction process (MCI Triage 27, PHLSDC 37, PHP 88). Most frequent subthemes and novel concepts have been identified as a basis for the elaboration of draft statements for the T2 modified Delphi study.

CONCLUSION

The three simultaneous scoping reviews allowed the extraction of relevant PH MCI subthemes and novel concepts that will enable the NIGHTINGALE consortium to create scientifically anchored statements in the T2 modified Delphi study.

Advanced Automatic Crash Notification Algorithm for Children

BACKGROUND

Advanced automatic crash notification (AACN) can improve triage decision-making by using vehicle telemetry to alert first responders of a motor vehicle crash and estimate an occupant's likelihood of injury. The objective was to develop an AACN algorithm to predict the risk that a pediatric occupant is seriously injured and requires treatment at a Level I or II trauma center.

METHODS

Based on 3 injury facets (severity; time sensitivity; predictability), a list of Target Injuries associated with a child's need for Level I/II trauma center treatment was determined. Multivariable logistic regression of motor vehicle crash occupants was performed creating the pediatric-specific AACN algorithm to predict risk of sustaining a Target Injury. Algorithm inputs included: delta-v, rollover quarter-turns, belt status, multiple impacts, airbag deployment, and age. The algorithm was optimized to achieve under-triage ≤5% and over-triage ≤50%. Societal benefits were assessed by comparing correctly triaged motor vehicle crash occupants using the AACN algorithm against real-world decisions.

RESULTS

The pediatric AACN algorithm achieved 25% to 49% over-triage across crash modes, and under-triage rates of 2% for far-side, 3% for frontal and near-side, 8% for rear, and 14% for rollover crashes. Applied to real-world motor vehicle crashes, improvements of 59% in under-triage and 45% in over-triage are estimated: more appropriate triage of 32,320 pediatric occupants annually.

CONCLUSIONS

This AACN algorithm accounts for pediatric developmental stage and will aid emergency personnel in correctly triaging pediatric occupants after a motor vehicle crash. Once incorporated into the trauma triage network, it will increase triage efficiency and improve patient outcomes.

JumpSTART Triage Protocol in Disaster Pediatric Patients: A Systematic Literature Review

INTRODUCTION

In a mass-casualty incident (MCI) involving children, there is a need to apply accurate triage tools in order to help those who require important care, and at the same time, to avoid unnecessary use of resources. Thus, it is discussed which would be the best triage device to use in these situations. One of the most used is a modification of Simple Triage and Rapid Treatment, JumpSTART, whose performative quality this review focuses on.

STUDY OBJECTIVE

This review sought to compare the performance parameters of JumpSTART with other triage algorithms used in pediatric disaster victims.

METHODS

This systematic review was performed according to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and registered with the PROSPERO database of systematic reviews with the number CRD42021258415. The last update of the search in the databases was on August 12, 2021 and resulted in six documents to be analyzed. The inclusion criteria included the peer-reviewed academic papers in English, Portuguese, Spanish, and Italian languages, and the databases used were PubMed, Scopus, MEDLINE/Bireme (Virtual Library of Health), Web of Science, and CINAHL, which executes the query on the topic, keywords, or abstracts. Also to be included, documents that were available with full-text access through CAPES, Google, or Google Scholar. Books, non-academic research, and content in languages other than the presented ones were represented as exclusion criteria. The Joanna Briggs Institute (JBI) checklists were used to evaluate the methodological quality of the retrieved studies. The results were presented through narrative synthesis. This review was not funded.

RESULTS

Of the collected publications, five articles were used to carry out this review, with the addition of an extra article captured by citation tracking. The findings from the obtained results were that JumpSTART was the preferred tool and presented the fastest speed of use. Only one of the five studies that dealt with accuracy showed JumpSTART as the most accurate algorithm, while three of the other four showed its inferiority in most aspects. In one study, no significant difference was observed amongst the chosen protocols.

CONCLUSIONS

There is insufficient evidence to validate JumpSTART as a universal triage tool, given the disparities in the results obtained from the comparisons. No tool performed satisfactorily well, therefore there is an urgent need to create a reliable algorithm.

Pediatric Disaster Preparedness

Children can be victims of mass casualty or illness, but their needs, with respect to their care and recovery are substantially different from adults. Emergency or urgent care physicians must be prepared to evaluate and manage child victims presenting to their facility in numbers or acuity that could significantly overwhelm normal operations. This article presents the general approach to pediatric disaster preparation in the United States, the expectations of emergency department providers, and different methods of disaster triage, and introduces the most likely types of mass illness (some of which are bioweapons or chemical agents) and their management.

[And if it happened to children? Adapting medical care during terrorist attacks with multiple pediatric victims]

In light of the recent terrorist attacks in Europe, we need to reconsider the organization of rescue and medical management and plan for an attack involving multiple pediatric victims. To ensure quick surgical management, but also to minimize risk for on-site teams (direct threats from secondary terrorist attacks targeting deployed emergency services), it is crucial to evacuate patients in a swift but orderly fashion. Children are vulnerable targets in terrorist attacks. Their anatomical and physiological characteristics make it likely that pediatric victims will suffer more brain injuries and require more, often advanced, airway management. Care of multiple pediatric victims would also prove to be a difficult emotional challenge. Civilian medical teams have adapted the military-medicine principles of damage control in their medical practice using the MARCHE algorithm (Massive hemorrhage, Airway, Respiration [breathing], Circulation, Head/Hypothermia, Evacuation). They have also learned to adapt the level of care to the level of safety at the scene. Prehospital damage control principles should now be tailored to the treatment of pediatric patients in extraordinary circumstances. Priorities are given to hemorrhage control and preventing the lethal triad (coagulopathy, hypothermia, and acidosis). Managing hemorrhagic shock involves quickly controlling external bleeding (tourniquets, hemostatic dressing), using small volumes for fluid resuscitation (10-20ml/kg of normal saline), quickly introducing a vasopressor (noradrenaline 0.1μg/kg/min then titrate) after one or two fluid boluses, and using tranexamic acid (15mg/kg over 10min for loading dose, maximum 1g over 10min). Prehospital resources specifically dedicated to children are limited, and it is therefore important that everyone be trained and prepared for a scene with multiple pediatric patients.

Performance characteristics of five triage tools for major incidents involving traumatic injuries to children

Context Triage tools are an essential component of the emergency response to a major incident. Although fortunately rare, mass casualty incidents involving children are possible which mandate reliable triage tools to determine the priority of treatment.

OBJECTIVE

To determine the performance characteristics of five major incident triage tools amongst paediatric casualties who have sustained traumatic injuries.

DESIGN, SETTING, PARTICIPANTS

Retrospective observational cohort study using data from 31,292 patients aged less than 16 years who sustained a traumatic injury. Data were obtained from the UK Trauma Audit and Research Network (TARN) database. Interventions Statistical evaluation of five triage tools (JumpSTART, START, CareFlight, Paediatric Triage Tape/Sieve and Triage Sort) to predict death or severe traumatic injury (injury severity score >15). Main outcome measures Performance characteristics of triage tools (sensitivity, specificity and level of agreement between triage tools) to identify patients at high risk of death or severe injury.

RESULTS

Of the 31,292 cases, 1029 died (3.3%), 6842 (21.9%) had major trauma (defined by an injury severity score >15) and 14,711 (47%) were aged 8 years or younger. There was variation in the performance accuracy of the tools to predict major trauma or death (sensitivities ranging between 36.4 and 96.2%; specificities 66.0-89.8%). Performance characteristics varied with the age of the child. CareFlight had the best overall performance at predicting death, with the following sensitivity and specificity (95% CI) respectively: 95.3% (93.8-96.8) and 80.4% (80.0-80.9). JumpSTART was superior for the triaging of children under 8 years; sensitivity and specificity (95% CI) respectively: 86.3% (83.1-89.5) and 84.8% (84.2-85.5). The triage tools were generally better at identifying patients who would die than those with non-fatal severe injury.

CONCLUSION

This statistical evaluation has demonstrated variability in the accuracy of triage tools at predicting outcomes for children who sustain traumatic injuries. No single tool performed consistently well across all evaluated scenarios.

Poorer outcomes for mass casualty events victims: is it evidence based?

BACKGROUND

The sudden influx of patients during mass casualty events (MCEs) may compromise the quality of care provided and possibly impact on the medical outcomes of these patients. To test this assumption, a comparison must be made between injuries sustained in MCE and non-MCE events caused by the same mechanism. The mechanism of injury selected for this study was gunshot wounds, which occur in both types of event.

METHODS

A retrospective study was carried out using the Israel's National Trauma Registry data on patients hospitalized between November 1, 2000, and December 31, 2005, as a result of high-energy gunshot trauma. Descriptive statistics and bivariate analysis were used to characterize injury patterns, and multivariate analysis was used to determine factors influencing inpatient mortality.

RESULTS

Of 462 patients with gunshot wounds, 120 cases (26.38%) were defined as MCE and 342 (73.62%) as non-MCE. Both populations had ∼30% of severely injured patients (Injury Severity Score 16+). MCE patients had undergone significantly fewer operational procedures. No differences between MCE and non-MCE were found in intensive care units utilization. The likelihood of death as a result of MCE was 2.75 (CI 1.09-7.02) times higher than non-MCE. Factors influencing this difference are the number of injured regions and injuries to the brain, chest, and abdomen.

CONCLUSIONS

MCE patients have a significantly higher mortality than non-MCE patients, not manifesting substantial differences in the severity of injuries. The absence of difference in intensive care units utilization may be related to the effectiveness of existing protocols for dealing with MCEs.