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Many triage algorithms exist for use in mass-casualty incidents (MCIs) involving pediatric patients. Most of these algorithms have not been validated for reliability across users.
Investigators sought to compare inter-rater reliability (IRR) and agreement among five MCI algorithms used in the pediatric population.
A dataset of 253 pediatric (<14 years of age) trauma activations from a Level I trauma center was used to obtain prehospital information and demographics. Three raters were trained on five MCI triage algorithms: Simple Triage and Rapid Treatment (START) and JumpSTART, as appropriate for age (combined as J-START); Sort Assess Life-Saving Intervention Treatment (SALT); Pediatric Triage Tape (PTT); CareFlight (CF); and Sacco Triage Method (STM). Patient outcomes were collected but not available to raters. Each rater triaged the full set of patients into Green, Yellow, Red, or Black categories with each of the five MCI algorithms. The IRR was reported as weighted kappa scores with 95% confidence intervals (CI). Descriptive statistics were used to describe inter-rater and inter-MCI algorithm agreement.
Of the 253 patients, 247 had complete triage assignments among the five algorithms and were included in the study. The IRR was excellent for a majority of the algorithms; however, J-START and CF had the highest reliability with a kappa 0.94 or higher (0.9-1.0, 95% CI for overall weighted kappa). The greatest variability was in SALT among Green and Yellow patients. Overall, J-START and CF had the highest inter-rater and inter-MCI algorithm agreements.
The IRR was excellent for a majority of the algorithms. The SALT algorithm, which contains subjective components, had the lowest IRR when applied to this dataset of pediatric trauma patients. Both J-START and CF demonstrated the best overall reliability and agreement.
Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between different tools designed for this purpose.
This study is to compare agreement between the Criteria Outcomes Tool (COT) to previously published outcomes tools in assessing the triage category applied to a simulated set of pediatric MCI patients.
An MCI triage category (black, red, yellow, and green) was applied to patients from a pre-collected retrospective cohort of pediatric patients under 14 years of age brought in as a trauma activation to a Level I trauma center from July 2010 through November 2013 using each of the following outcome measures: COT, modified Baxt score, modified Baxt combined with mortality and/or length-of-stay (LOS), ambulatory status, mortality alone, and Injury Severity Score (ISS). Descriptive statistics were applied to determine agreement between tools.
A total of 247 patients were included, ranging from 25 days to 13 years of age. The outcome of mortality had 100% agreement with the COT black. The “modified Baxt positive and alive” outcome had the highest agreement with COT red (65%). All yellow outcomes had 47%-53% agreement with COT yellow. “Modified Baxt negative and <24 hours LOS” had the highest agreement with the COT green at 89%.
Assessment of algorithms for triaging pediatric MCI patients is complicated by the lack of a gold standard outcome tool and variability between existing measures.
It remains unclear which mass-casualty incident (MCI) triage tool best predicts outcomes for child disaster victims.
The primary objective of this study was to compare triage outcomes of Simple Triage and Rapid Treatment (START), modified START, and CareFlight in pediatric patients to an outcomes-based gold standard using the Criteria Outcomes Tool (COT). The secondary outcomes were sensitivity, specificity, under-triage, over-triage, and overall accuracy at each level for each MCI triage algorithm.
Singleton trauma patients under 16 years of age with complete prehospital, emergency department (ED), and in-patient data were identified in the 2007-2009 National Trauma Data Bank (NTDB). The COT outcomes and procedures were translated into ICD-9 procedure codes with added timing criteria. Gold standard triage levels were assigned using the COT based on outcomes, including mortality, injury type, admission to the hospital, and surgical procedures. Comparison triage levels were determined based on algorithmic depictions of the three MCI triage tools.
A total of 31,093 patients with complete data were identified from the NTDB. The COT was applied to these patients, and the breakdown of gold standard triage levels, based on their actual clinical outcomes, was: 17,333 (55.7%) GREEN; 11,587 (37.3%) YELLOW; 1,572 (5.1%) RED; and 601 (1.9%) BLACK. CareFlight had the best sensitivity for predicting COT outcomes for BLACK (83% [95% confidence interval, 80%-86%]) and GREEN patients (79% [95% CI, 79%-80%]) and the best specificity for RED patients (89% [95% CI, 89%-90%]).
Among three prehospital MCI triage tools, CareFlight had the best performance for correlating with outcomes in the COT. Overall, none of three tools had good test characteristics for predicting pediatric patient needs for surgical procedures or hospital admission.
The Sort, Access, Life-saving interventions, Treatment and/or Triage (SALT) mass-casualty incident (MCI) algorithm is unique in that it includes two subjective questions during the triage process: “Is the victim likely to survive given the resources?” and “Is the injury minor?”
Given this subjectivity, it was hypothesized that as casualties increase, the inter-rater reliability (IRR) of the tool would decline, due to an increase in the number of patients triaged as Minor and Expectant.
A pre-collected dataset of pediatric trauma patients age <14 years from a single Level 1 trauma center was used to generate “patients.” Three trained raters triaged each patient using SALT as if they were in each of the following scenarios: 10, 100, and 1,000 victim MCIs. Cohen’s kappa test was used to evaluate IRR between the raters in each of the scenarios.
A total of 247 patients were available for triage. The kappas were consistently “poor” to “fair:” 0.37 to 0.59 in the 10-victim scenario; 0.13 to 0.36 in the 100-victim scenario; and 0.05 to 0.36 in the 1,000-victim scenario. There was an increasing percentage of subjects triaged Minor as the number of estimated victims increased: 27.8% increase from 10- to 100-victim scenario and 7.0% increase from 100- to 1,000-victim scenario. Expectant triage categorization of patients remained stable as victim numbers increased.
Overall, SALT demonstrated poor IRR in this study of increasing casualty counts while triaging pediatric patients. Increased casualty counts in the scenarios did lead to increased Minor but not Expectant categorizations.
ST-segment elevation myocardial infarction (STEMI) is a time-sensitive entity that has been shown to benefit from prehospital diagnosis by electrocardiogram (ECG). Current computer algorithms with binary decision making are not accurate enough to be relied on for cardiac catheterization lab (CCL) activation.
An algorithmic approach is proposed to stratify binary STEMI computerized ECG interpretations into low, intermediate, and high STEMI probability tiers.
Based on previous literature, a four-criteria algorithm was developed to rule out/in common causes of prehospital STEMI false-positive computer interpretations: heart rate, QRS width, ST elevation criteria, and artifact. Prehospital STEMI cases were prospectively collected at a single academic center in Salt Lake City, Utah (USA) from May 2012 through October 2013. The prehospital ECGs were applied to the algorithm and compared against activation of the CCL by an emergency department (ED) physician as the outcome of interest. In addition to calculating test characteristics, linear regression was used to look for an association between number of criteria used and accuracy, and logistic regression was used to test if any single criterion performed better than another.
There were 63 ECGs available for review, 39 high probability and 24 intermediate probability. The high probability STEMI tier had excellent test characteristics for ruling in STEMI when all four criteria were used, specificity 1.00 (95% CI, 0.59-1.00), positive predictive value 1.00 (0.91-1.00). Linear regression showed a strong correlation demonstrating that false-positives increased as fewer criteria were used (adjusted r-square 0.51; P <.01). Logistic regression showed no significant predictive value for any one criterion over another (P = .80). Limiting physician overread to the intermediate tier only would reduce the number of ECGs requiring physician overread by a factor of 0.62 (95% CI, 0.48-0.75; P <.01).
Prehospital STEMI ECGs can be accurately stratified to high, intermediate, and low probabilities for STEMI using the four criteria. While additional study is required, using this tiered algorithmic approach in prehospital ECGs could lead to changes in CCL activation and decreased requirements for physician overread. This may have significant clinical and quality implications.
A simple, portable capillary refill time (CRT) simulator is not commercially available. This device would be useful in mass-casualty simulations with multiple volunteers or mannequins depicting a variety of clinical findings and CRTs. The objective of this study was to develop and evaluate a prototype CRT simulator in a disaster simulation context.
A CRT prototype simulator was developed by embedding a pressure-sensitive piezo crystal, and a single red light-emitting diode (LED) light was embedded, within a flesh-toned resin. The LED light was programmed to turn white proportionate to the pressure applied, and gradually to return to red on release. The time to color return was adjustable with an external dial. The prototype was tested for feasibility among two cohorts: emergency medicine physicians in a tabletop exercise and second year medical students within an actual disaster triage drill. The realism of the simulator was compared to video-based CRT, and participants used a Visual Analog Scale (VAS) ranging from “completely artificial” to “as if on a real patient.” The VAS evaluated both the visual realism and the functional (eg, tactile) realism. Accuracy of CRT was evaluated only by the physician cohort. Data were analyzed using parametric and non-parametric statistics, and mean Cohen’s Kappas were used to describe inter-rater reliability.
The CRT simulator was generally well received by the participants. The simulator was perceived to have slightly higher functional realism (P=.06, P=.01) but lower visual realism (P=.002, P=.11) than the video-based CRT. Emergency medicine physicians had higher accuracy on portrayed CRT on the simulator than the videos (92.6% versus 71.1%; P<.001). Inter-rater reliability was higher for the simulator (0.78 versus 0.27; P<.001).
A simple, LED-based CRT simulator was well received in both settings. Prior to widespread use for disaster triage training, validation on participants’ ability to accurately triage disaster victims using CRT simulators and video-based CRT simulations should be performed.
ChangTP, SantillanesG, Claudius I, PhamPK, KovedJ, CheyneJ, Gausche-HillM, KajiAH, SrinivasanS, DonofrioJJ, BirC. Use of a Novel, Portable, LED-Based Capillary Refill Time Simulator within a Disaster Triage Context. Prehosp Disaster Med. 2017;32(4):451–456.
Using the pediatric version of the Simple Triage and Rapid Treatment (JumpSTART) algorithm for the triage of pediatric patients in a mass-casualty incident (MCI) requires assessing the results of each step and determining whether to move to the next appropriate action. Inappropriate application can lead to performance of unnecessary actions or failure to perform necessary actions.
To report overall accuracy and time required for triage, and to assess if the performance of unnecessary steps, or failure to perform required steps, in the triage algorithm was associated with inaccuracy of triage designation or increased time to reach a triage decision.
Medical students participated in an MCI drill in which they triaged both live actors portraying patients and computer-based simulated patients to the four triage levels: minor, delayed, immediate, and expectant. Their performance was timed and compared to intended triage designations and a priori determined critical actions.
Thirty-three students completed 363 scenarios. The overall accuracy was 85.7% and overall mean time to assign a triage designation was 70.4 seconds, with decreasing times as triage acuity level decreased. In over one-half of cases, the student omitted at least one action and/or performed at least one action that was not required. Each unnecessary action increased time to triage by a mean of 8.4 seconds and each omitted action increased time to triage by a mean of 5.5 seconds.
Increasing triage level, performance of inappropriate actions, and omission of recommended actions were all associated with increasing time to perform triage.
ClaudiusI, KajiAH, SantillanesG, CiceroMX, DonofrioJJ, Gausche-HillM, SrinivasanS, ChangTP. Accuracy, Efficiency, and Inappropriate Actions Using JumpSTART Triage in MCI Simulations. Prehosp Disaster Med. 2015;30(5):457–460.
Multiple modalities for simulating mass-casualty scenarios exist; however, the ideal modality for education and drilling of mass-casualty incident (MCI) triage is not established.
Medical student triage accuracy and time to triage for computer-based simulated victims and live moulaged actors using the pediatric version of the Simple Triage and Rapid Treatment (JumpSTART) mass-casualty triage tool were compared, anticipating that student performance and experience would be equivalent.
The victim scenarios were created from actual trauma records from pediatric high-mechanism trauma presenting to a participating Level 1 trauma center. The student-reported fidelity of the two modalities was also measured. Comparisons were done using nonparametric statistics and regression analysis using generalized estimating equations.
Thirty-three students triaged four live patients and seven computerized patients representing a spectrum of minor, immediate, delayed, and expectant victims. Of the live simulated patients, 92.4% were given accurate triage designations versus 81.8% for the computerized scenarios (P=.005). The median time to triage of live actors was 57 seconds (IQR=45-66) versus 80 seconds (IQR=58-106) for the computerized patients (P<.0001). The moulaged actors were felt to offer a more realistic encounter by 88% of the participants, with a higher associated stress level.
While potentially easier and more convenient to accomplish, computerized scenarios offered less fidelity than live moulaged actors for the purposes of MCI drilling. Medical students triaged live actors more accurately and more quickly than victims shown in a computerized simulation.
ClaudiusI, KajiA, SantillanesG, CiceroM, DonofrioJJ, Gausche-HillM, SrinivasanS, ChangTP.
Comparison of Computerized Patients versus Live Moulaged Actors for a Mass-casualty Drill. Prehosp Disaster Med.2015; 30(5): 438–442.
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