Simple Triage And Rapid Treatment Research Articles

Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study.

The release of ChatGPT (OpenAI) in November 2022 drastically reduced the barrier to using artificial intelligence by allowing a simple web-based text interface to a large language model (LLM). One use case where ChatGPT could be useful is in triaging patients at the site of a disaster using the Simple Triage and Rapid Treatment (START) protocol. However, LLMs experience several common errors including hallucinations (also called confabulations) and prompt dependency. This study addresses the research problem: "Can ChatGPT adequately triage simulated disaster patients using the START protocol?" by measuring three outcomes: repeatability, reproducibility, and accuracy. Nine prompts were developed by 5 disaster medicine physicians. A Python script queried ChatGPT Version 4 for each prompt combined with 391 validated simulated patient vignettes. Ten repetitions of each combination were performed for a total of 35,190 simulated triages. A reference standard START triage code for each simulated case was assigned by 2 disaster medicine specialists (JMF and MV), with a third specialist (LC) added if the first two did not agree. Results were evaluated using a gage repeatability and reproducibility study (gage R and R). Repeatability was defined as variation due to repeated use of the same prompt. Reproducibility was defined as variation due to the use of different prompts on the same patient vignette. Accuracy was defined as agreement with the reference standard. Although 35,102 (99.7%) queries returned a valid START score, there was considerable variability. Repeatability (use of the same prompt repeatedly) was 14% of the overall variation. Reproducibility (use of different prompts) was 4.1% of the overall variation. The accuracy of ChatGPT for START was 63.9% with a 32.9% overtriage rate and a 3.1% undertriage rate. Accuracy varied by prompt with a maximum of 71.8% and a minimum of 46.7%. This study indicates that ChatGPT version 4 is insufficient to triage simulated disaster patients via the START protocol. It demonstrated suboptimal repeatability and reproducibility. The overall accuracy of triage was only 63.9%. Health care professionals are advised to exercise caution while using commercial LLMs for vital medical determinations, given that these tools may commonly produce inaccurate data, colloquially referred to as hallucinations or confabulations. Artificial intelligence-guided tools should undergo rigorous statistical evaluation-using methods such as gage R and R-before implementation into clinical settings.

The speed and accuracy of prehospital triage for simulated disaster patients: Comparing prehospital emergency triage rapid algorithm (PETRA) and simple triage and rapid treatment (START)

The speed and accuracy of prehospital triage for simulated disaster patients: Comparing prehospital emergency triage rapid algorithm (PETRA) and simple triage and rapid treatment (START)

A Low-Cost, Low-Tech Virtual Mass Casualty Training Simulation for Undergraduate Medical Education.

Mass casualty incident (MCI) training effectively increases trainees' knowledge and confidence when implemented in a live, in-person setting. In-person MCI training is resource-intensive, but virtual MCI training models are an alternative with similar effectiveness at a lesser cost. However, most of these validated virtual options are based on high-tech virtual reality (VR) programs. We designed and implemented a low-tech, low-cost virtual MCI training model for third-year medical students, using Google JamboardTM (Google, Mountain View, CA) and ZoomTM(Zoom Video Communications, Inc., San Jose, CA) as the primary technological platforms. Learners were instructed on the adult simple triage and rapid treatment (START) and the pediatric JumpSTART triage algorithms over ZoomTM. In small groups, students used a gameboard on Google JamboardTM to simulate a scene at an MCI where they were tasked with triaging 25 patients in 30 minutes, followed by a debriefing session. Students were surveyed on their perceived understanding of the triage algorithms and confidence before and after the event using a 5-point Likert scale (poor, fair, good, very good, and excellent). Pre- and post-event scores were compared using paired, two-sample, and two-tailed t-tests. We considered a p value of <0.01 significant to correct for multiplicity using the Bonferroni method. Learners reported an increased understanding of the triage algorithms (adult and pediatric), scene setup, andunderstanding of emergency medical servicetraining/transportation, as well as increased confidence in participating in an MCI (all p < 0.001). Virtual MCI training can be used as an alternative or supplement to in-person MCI training. Low-tech virtual MCI training models can increase the accessibility of these valuable training activities without sacrificing the quality of learning. Areas for further investigation include low-tech virtual MCI training models' ability to effectively recreate situational and environmental distractions and other challenges better simulated by in-person and high-tech VR training events.

Utilization of an Asynchronous Online Learning Module Followed by Simulated Scenario to Train Emergency Medicine Residents in Mass-Casualty Triage.

This is a combined independent study and simulation session designed to teach and drill Mass Casualty Incident (MCI) Triage and is intended for emergency medicine residents at all levels. The training of emergency medicine residents to assume leadership roles in disaster response is important. However, lack of accepted specific educational goals on the national level leads to significant variability between residencies. The purpose of this session is to train EM residents in the use of the Simple Triage and Rapid Treatment (START) and pediatric JumpSTART algorithms for triage in mass casualty incidents (MCIs) using an asynchronous model. By the end of this small group session, learners will be able to: 1) describe START triage for adult MCI victims; 2) describe JumpSTART triage for pediatric MCI victims; 3) demonstrate the ability to apply the START and JumpSTART triage algorithms in a self-directed learning environment; 4) demonstrate the ability to apply the START and JumpSTART triage algorithms in a simulated mass casualty scenario under time constraints; and 5) demonstrate appropriate use of acute life-saving interventions as dictated by the START and JumpSTART triage algorithms in a high-pressure simulated environment. This session utilizes an online independent study module that was created de novo for this specific purpose by the authors followed by a high-pressure in-person simulation session where learners practice applying the START triage model with multiple simulated patients under time constraint. Learner feedback was collected after completion of the session. Retention of learning objectives was tested at four months via multiple-choice quiz. The session was very well received by our residents, who appreciated the opportunity to practice applying START triage under pressure. The average score on the pretest was 49%. Response rates to the post-test were low, but residents scored an average of 73%, indicating a trend towards retention of learning objectives. Overall, the utilization of a de novo online learning module followed by simulation proved to be a well-received method of teaching MCI triage to emergency medicine residents. We consider this to be an effective way to train MCI Triage with minimal in-conference time utilization. We plan to implement this training annually to provide our residents with longitudinal reinforcement of this vital skill. Mass casualty, MCI, triage, START triage, JumpSTART Triage, disaster, disaster preparedness, disaster curriculum, prehospital, EMS.

THE START SORTING SYSTEM AND THE NURSE’S PARTICIPATION IN ITS IMPLEMENTATION

Introduction. This article highlights the problem of organizing the sorting of patients during mass admission to medical institutions and providing emergency medical care. The role of the nurse in conducting triage and providing emergency care at the early hospital stage is within the framework of limited resources. The urgency of working out the response protocol in the event of an emergency. The aim of the study – to determine the role of the nurse in the triage and provision of emergency care at the early hospital stage within the framework of a limited resource. To establish the relevance of the use of the START medical triage system in the practical activities of a nurse. The relevance of working out the response protocol in the event of an emergency among nurses. The main part. The medical triage system START (Simple Triage and Rapid Treatment) is an effective tool for organizing and accelerating the process of correct routing of patients in mass cases and crises when resources are limited and medical needs are high. Medical triage criteria also include signs of primary medical examination. As their professional responsibilities expand, nurses can use the ABCD algorithm to assess the patient’s condition. Knowledge of the principles of this medical triage system, the ability to provide emergency medical care, evenly and effectively distribute resources, follow the instructions of the coordinating physician, describe medical documentation, and label the patient’s category have become the duties of nurses due to the increasing frequency of emergencies. Conclusions. The START (Simple Triage and Rapid Treatment) triage system is used for prompt and efficient selection of victims during emergencies. The role of the nurse in this process is extremely important. First of all, the nurse must have skills in the application of the START triage technique and an understanding of its basics. During triage, the nurse can quickly assess the condition of each victim, determine the category, and assign the appropriate color tag. Provision of emergency medical care in conditions of limited resources, coordination, and reporting for further organization of medical care are key elements in the formation of nursing competence during triage. Using the principles of medical triage can help optimize treatment and save more lives in emergencies.

START Triage Sebagai Istrumen Penanganan Korban dalam Setting Bencana

Unexpected incidents that result in significant loss or destruction are called disasters. In general, this event is closely associated with natural phenomena. Ultimately, though, this is frequently linked to incidents brought about by human intervention that entail drastic lifestyle modifications and significant harm. Since it is vital to allocate comparatively few resources to specific, urgent medical needs, triage is a crucial component of contemporary medical treatment. When a patient's medical demands and the resources that are available are not met in a timely or convenient manner, this task becomes critical. The foundation of Simple Triage and Rapid Treatment (START) is a quick evaluation of mental status, breathing, and perfusion (RPM). This work was written using a literature study methodology. Reference books (textbooks), scientific journals, and other pertinent sources provide the literature that is used. According to calibration and discrimination data, RPM (STARt triage) is a more reliable indicator of the blunt trauma survival rate than the Trauma Severity Score and the Revised Trauma Score. SALT triage is inferior to START (SMART) triage. On the other hand, employing START triage has been shown to increase time efficiency. It has been scientifically demonstrated that using START triage can result in suitable assessments for disaster management. Through the development of the Mass Casualty Triage Pack (SMART Triage Pack), STRAT triage has been used to enhance its efficacy.

Field Triage Tools in Mass Casualty Incidents: A Narrative Review

Mass casualty incidents (MCIs) pose significant challenges to healthcare systems, requiring rapid and effective triage strategies to optimize patient outcomes and resource utilization. This narrative review explores the evolution, effectiveness, ethical considerations, global perspectives, and future directions of field triage tools in MCIs. Beginning with the historical perspective, milestones in triage development, such as the Simple Triage and Rapid Treatment (START) protocol and its adaptations like Jump START and Sort, Assess, Lifesaving Interventions, Treat/Transport (SALT), are discussed. Current field triage systems are evaluated, including their application, limitations, and impact on patient outcomes. Training and education programs, challenges in triage education, and ethical/legal considerations in resource allocation and informed consent are examined. Global variations in triage systems, cultural factors, collaboration efforts, and standardization initiatives are explored to understand regional differences and promote interoperability. Future directions emphasize enhancing triage accuracy, integrating triage with healthcare systems, and research priorities. The review concludes with implications for practice and policy, calling for continued research, collaboration, and innovation to advance field triage capabilities and improve emergency response worldwide.

February 6th, Kahramanmaraş earthquakes and the disaster management algorithm of adult emergency medicine in Turkey: An experience review.

This compilation covers emergency medical management lessons from the February 6th Kahramanmaraş earthquakes. The objective is to review relevant literature on emergency services patient management, focusing on Koenig's 1996 Simple Triage and Rapid Treatment (START) and Secondary Assessment of Victim Endpoint (SAVE) frameworks. Establishing a comprehensive seismic and mass casualty incident (MCI) protocol chain is the goal. The prehospital phase of seismic MCIs treats hypovolemia and gets patients to the nearest hospital. START-A plans to expedite emergency patient triage and pain management. The SAVE algorithm is crucial for the emergency patient secondary assessment. It advises using Glasgow Coma Scale, Mangled Extremity Severity Score, Burn Triage Score, and Safe Quake Score for admission, surgery, transfer, discharge, and outcomes. This compilation emphasizes the importance of using diagnostic tools like bedside blood gas analyzers and ultrasound devices during the assessment process, drawing from 6 February earthquake research. The findings create a solid framework for improving emergency medical response strategies, making them applicable in similar situations.

Usefulness of Self-Selected Scenarios for Simple Triage and Rapid Treatment Method Using Virtual Reality.

Repeated triage training is necessary to maintain and improve the accuracy of simple triage and rapid treatment (START), a popular triage method. Virtual reality (VR) may be more effective than conventional training methods. This study aimed to verify the educational usefulness of START using VR originally developed for students. A VR was initially developed with a function that allowed students to select the triage procedure and its evaluation. Triage was performed using a simple modified START method, and eight scenarios were developed. The participants included 70 paramedic students classified into VR and live lecture groups. They took a 20-question written test that evaluated their academic ability before the course. After the course, a practical test and a 20-question written test were conducted. The total score of the practical test was 43 points. Triage procedure (1 point), observation and evaluation (1-5 points), and triage categories (1 point) were evaluated in this test. The VR and live lecture groups consisted of 33 and 29 participants, respectively. No significant differences were observed pre- and post-test. In the practical test, the median (interquartile range) score was 29 (26-32) and 25 (23-29) for the VR and live lecture groups, respectively, with the VR group scoring significantly higher (P=0.03). Our results confirmed the educational usefulness of selective VR for active learning of START. Therefore, VR combined with live lectures and simulations would be an optimal educational technique.

An Assessment of Clinical Accuracy of Vital Sign-based Triage Tools Among U.S. and Coalition Forces.

Early appropriate allocation of resources for critically injured combat casualties is essential. This is especially important when inundated with an overwhelming number of casualties where limited resources must be efficiently allocated, such as during mass casualty events. There are multiple scoring systems utilized in the prehospital combat setting, including the shock index (SI), modified shock index (MSI), simple triage and rapid treatment (START), revised trauma score (RTS), new trauma score (NTS), Glasgow Coma Scale + age + pressure (GAP), and the mechanism + GAP (MGAP) score. The optimal score for application to the combat trauma population remains unclear. This is a secondary analysis of a previously described dataset from the Department of Defense Trauma Registry from January 1, 2007 through March 17, 2020. We constructed univariable analyses to determine the area under the receiving operator characteristic (AUROC) for the scoring systems of interest. Our primary outcomes were early death (within 24 hours) or early massive transfusion, as defined by ≥3 units. There were 12,268 casualties that met inclusion criteria. There were 168 (1%) who died within the first 24 hours and 2082 (17%) that underwent significant transfusion within the first 24 hours. When assessing the predictive capabilities for death within 24 hours, the AUROCs were 0.72 (SI), 0.69 (MSI), 0.89 (START), 0.90 (RTS), 0.83 (NTS), 0.90 (GAP), and 0.91 (MGAP). The AUROCs for massive transfusion were 0.89 (SI), 0.89 (MSI), 0.82 (START), 0.81 (RTS), 0.83 (NTS), 0.85 (MGAP), and 0.86 (GAP). This study retrospectively applied seven triage tools to a database of 12,268 cases from the Department of Defense Trauma Registry to evaluate their performance in predicting early death or massive transfusion in combat. All scoring systems performed well with an AUROC >0.8 for both outcomes. Although the SI and MSI performed best for predicting massive transfusion (both had an AUROC of 0.89), they ranked last for assessment of mortality within 24 hours, with the other tools performing well. START, RTS, NTS, MGAP and GAP reliably identified early death and need for massive transfusion, with MGAP and GAP performing the best overall. These findings highlight the importance of assessing triage tools to best manage resources and ultimately preserve lives of traumatically wounded warfighters. Further studies are needed to explain the surprising performance discrepancy of the SI and MSI in predicting early death and massive transfusion.

The effect of multiple triage points on the outcomes (time and accuracy) of hospital triage during mass casualty incidents

IntroductionDuring mass casualty incidents (MCIs), the accuracy and timing of the triage of patients by the emergency department (ED) triage officers are essential. The primary triage is performed at the event's location by paramedics and intends a quick evaluation of the victims. Secondary triage may be used when the transfer of the victim is delayed. In this study, we aimed to investigate the effectiveness of two-point triage in a simulated environment of an MCI in the hospital setting. Materials and methodsIn this case-control study, we used an online test module to assess single triage points (Group 1, n = 41) and two triage points (Group 2, n = 40). 60 vignettes for Group 1 and 55 vignettes (5 deceased cases removed) for Group 2 were used. The assessment utilized clinical MCI scenarios in a scheduled online meeting by using the Simple Triage and Rapid Treatment (START) system. Triage time and accuracy of the triage, along with the experience, and previous training of the participants, were assessed. ResultsA total of 81 triage officers participated in this study. The participants were divided into two independent groups homogenously according to their profession and experience. Groups were comparable primarily without any statistically significant difference in terms of the profession (p = 0.101), sex (p = 0.923), and MCI experience (p = 0.785). The difference between the two groups was not significant with regard to having received practical or theoretical triage training (p = 0.099). The mean time of a single vignette triage was 19.2 (SD 6.5) seconds and mean percentage of correct triage score was 65.0 (SD 12.6). The participants had a statistically significantly better performance in the single-point triage group regarding the median triage time (p < 0.001) and median percentages of under triage (p = 0.001), but a worse median percentage of over triage (p < 0.001). However, there was no significant difference between the two groups in terms of the percentage of accurate triage. Emergency residents performed better in accuracy and triage time than their non-physician colleagues (p = 0.019). ConclusionsTwo-point triage does not demonstrate better outcomes in terms of accuracy and timing. Triage officers should be trained frequently with the preferred training methodology to prevent improper triage accuracy and timing. Well-defined medical disaster planning should include frequent training of the triage officers with case scenarios.

Repeatability, Reproducibility, and Diagnostic Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage Using the Simple Triage and Rapid Treatment (START) Protocol

Abstract Objective The release of ChatGPT in November 2022 drastically lowered the barrier to artificial intelligence with an intuitive web-based interface to a large language model. This study addressed the research problem: “Can ChatGPT adequately triage simulated disaster patients using the Simple Triage and Rapid Treatment (START) tool?” Methods Five trained disaster medicine physicians developed nine prompts. A Python script queried ChatGPT Version 4 with each prompt combined with 391 validated patient vignettes. Ten repetitions of each combination were performed: 35190 simulated triages. Results A valid START score was returned In 35102 queries (99.7%). There was considerable variability in the results. Repeatability (use of the same prompt repeatedly) was responsible for 14.0% of overall variation. Reproducibility (use of different prompts) was responsible for 4.1% of overall variation. Accuracy of ChatGPT for START was 61.4% with a 5.0% under-triage rate and a 33.6% over-triage rate. Accuracy varied by prompt between 45.8% and 68.6%. Conclusions This study suggests that the current ChatGPT large language model is not sufficient for triage of simulated patients using START due to poor repeatability and accuracy. Medical practitioners should be aware that while ChatGPT can be a valuable tool, it may lack consistency and may provide false information.

ChatGPT's performance before and after teaching in mass casualty incident triage

Since its initial launching, ChatGPT has gained significant attention from the media, with many claiming that ChatGPT’s arrival is a transformative milestone in the advancement of the AI revolution. Our aim was to assess the performance of ChatGPT before and after teaching the triage of mass casualty incidents by utilizing a validated questionnaire specifically designed for such scenarios. In addition, we compared the triage performance between ChatGPT and medical students. Our cross-sectional study employed a mixed-methods analysis to assess the performance of ChatGPT in mass casualty incident triage, pre- and post-teaching of Simple Triage And Rapid Treatment (START) triage. After teaching the START triage algorithm, ChatGPT scored an overall triage accuracy of 80%, with only 20% of cases being over-triaged. The mean accuracy of medical students on the same questionnaire yielded 64.3%. Qualitative analysis on pre-determined themes on ‘walking-wounded’, ‘respiration’, ‘perfusion’, and ‘mental status’ on ChatGPT showed similar performance in pre- and post-teaching of START triage. Additional themes on ‘disclaimer’, ‘prediction’, ‘management plan’, and ‘assumption’ were identified during the thematic analysis. ChatGPT exhibited promising results in effectively responding to mass casualty incident questionnaires. Nevertheless, additional research is necessary to ensure its safety and efficacy before clinical implementation.

Performance of Google bard and ChatGPT in mass casualty incidents triage

AimThe objective of our research is to evaluate and compare the performance of ChatGPT, Google Bard, and medical students in performing START triage during mass casualty situations. MethodWe conducted a cross-sectional analysis to compare ChatGPT, Google Bard, and medical students in mass casualty incident (MCI) triage using the Simple Triage And Rapid Treatment (START) method. A validated questionnaire with 15 diverse MCI scenarios was used to assess triage accuracy and content analysis in four categories: “Walking wounded,” “Respiration,” “Perfusion,” and “Mental Status.” Statistical analysis compared the results. ResultGoogle Bard demonstrated a notably higher accuracy of 60%, while ChatGPT achieved an accuracy of 26.67% (p = 0.002). Comparatively, medical students performed at an accuracy rate of 64.3% in a previous study. However, there was no significant difference observed between Google Bard and medical students (p = 0.211). Qualitative content analysis of ‘walking-wounded’, ‘respiration’, ‘perfusion’, and ‘mental status’ indicated that Google Bard outperformed ChatGPT. ConclusionGoogle Bard was found to be superior to ChatGPT in correctly performing mass casualty incident triage. Google Bard achieved an accuracy of 60%, while chatGPT only achieved an accuracy of 26.67%. This difference was statistically significant (p = 0.002).

Assessment of three triage systems by medical undergraduate students using simulated disaster patients: a comparative study

BackgroundTriage is an initial important step in emergency medical rescues for mass casualty incidents, and different triage systems are used in practice. However, quantitative analysis-based evidence comparing these triage systems in mass casualty incidents is limited.ObjectiveTo compare the performance of three triage systems, simple triage and rapid treatment (START), abbreviated scoring method for combat casualty (ASMcc), and sort assess lifesaving interventions treatment/transport (SALT) system, for simulated disaster patients, as assessed by medical undergraduate students.MethodsMedical undergraduates were recruited and randomly divided into three groups to evaluate the performance of the three triage systems by using simulated disaster patient cards. The triage time, accuracy, and overtriage and undertriage rates were analyzed among groups. Furthermore, a questionnaire survey was used to investigate the responses of the participants regarding learning, practice, and satisfaction among the three triage systems.ResultsA total of 30 participants were included in the study. The participants were male medical undergraduate students with a mean age of 20.73 ± 0.45 years. ASMcc had the highest accuracy of 75% with the lowest over-triage rate of 20%, SALT had the lowest undertriage rate of 19%, and START had the shortest triage time of 12.68 ± 4.96 min (all P &amp;lt; 0.05). Furthermore, the results of the questionnaire survey showed that START was easy to learn and recall with high efficiency and, among the three systems, had the highest satisfaction ratings from the participants.ConclusionThe results of the study showed that the three triage systems had their own characteristics and advantages, and they are all suitable for use in mass casualty incidents. Further studies involving more triage systems with data based on real conditions are recommended.

Current Disaster Triage Methods in Mass Casualty Incidents

Introduction:Triage in a disaster scenario centers around doing the greatest good for the greatest number of people. There are a variety of triage systems, and to this date there is no US national endorsement of one system because triage is a dynamic procedure and there is no fixed rule for it. The Simple Triage and Rapid Treatment (START); Sort, Assess, Life-saving interventions, Treatment/Transport (SALT); Sacco; CareFlight; JumpSTART; and Pediatric Triage Tape (PTT) triage systems are discussed with emphasis on how they perform.Method:There are approximately 20 adult and two pediatric triage systems that exist for primary disaster triage. The focus is on six primary triage systems. A literature search was performed using textbooks and original research.Results:A basic assignment to immediate, delayed, minimal, or expectant can sort a large group of casualties in a matter of minutes, but improper category assignment can lead to under-triage or over-triage.When assessed by a trained paramedic arriving at a Level 1 pediatric trauma center, SALT was found to be the most accurate triage system at 59% compared to JumpSTART, CareFlight, and TriageSieve. All triage systems exhibited under-triage rates of at least 33% and SALT had the highest over-triage rate at 6%. In another study, the START triage system was found to be 85% sensitive and 86% specific in predicting critical injury in designated trauma patients.Conclusion:Mass casualty incidents are unfortunately becoming more common as the increasing numbers of violent attacks produce an overwhelming number of victims. One triage process may not work in all disasters, but first responders should be trained to evaluate for the most critical patients in a sea of evolving patient presentations. Furthermore, randomized, controlled trials in real-world conditions are nearly impossible to perform given the specific circumstances of disasters.

Accuracy of Trauma on Scene Triage Screening Tool (Shock Index, Reverse Shock Index Glasgow Coma Scale and National Early Warning Score) to Predict the Severity of Emergency Department Triage: A Retrospective Cross-Sectional Study.

Prehospital trauma care includes on-scene assessments, essential treatment, and facilitating transfer to an appropriate trauma center to deliver optimal care for trauma patients. While the Simple Triage and Rapid Treatment (START), Revised Triage Sieve (rTS), and National Early Warning Score (NEWS) tools are user-friendly in a prehospital setting, there is currently no standardized on-scene triage protocol in Thailand Emergency Medical Service (EMS). Therefore, this study aims to evaluate the precision of these tools (SI, rSIG, and NEWS) in predicting the severity of trauma patients who are transferred to the emergency department (ED). This study was a retrospective cross-sectional and diagnostic research conducted on trauma patients transferred by EMS to the ED of Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand, from January 2015 to September 2022. We compared the on-scene triage tool (SI, rSIG, and NEWS) and ED triage tool (Emergency Severity Index) parameters, massive transfusion protocol (MTP), and intensive care unit (ICU) admission with the area under ROC (univariable analysis) and diagnostic odds ratio (multivariable logistic regression analysis). The optimal cut-off threshold for the best parameter was determined by selecting the value that produced the highest area under the ROC curve. A total of 218 patients were traumatic patients transported by EMS to the ED, out of which 161 were classified as ESI levels 1-2, while the remaining 57 patients were categorized as levels 3-5 on the ESI triage scale. We found that NEWS was a more accurate triage tool to discriminate the severity of trauma patients than rSIG and SI. The area under the ROC was 0.74 (95% CI 0.70-0.79) (OR 18.98, 95% CI 1.06-337.25), 0.65 (95% CI 0.59-0.70) (OR 1.74, 95% CI 0.17-18.09) and 0.58 (95% CI 0.52-0.65) (OR 0.28, 95% CI 0.04-1.62), respectively (P-value <0.001). The cut point of NEWS to discriminate ESI levels 1-2 and levels 3-5 was >6 points. NEWS is the best on-scene triage screening tool to predict the severity at the emergency department, massive transfusion protocol (MTP), and intensive care unit (ICU) admission compared with other triage tools SI and rSIG.

Prehospital Mass Casualty Incident Response to a Fire in a Nursing Home in Milan, Italy: Actions Taken and Shortcomings

Abstract On July 7, 2023, at 1:21 am, a fire was declared in a retirement home in Milan, Italy. The number of casualties (n = 87) according to the Simple Triage and Rapid Treatment (START) triage system was categorized as 65 green, 14 yellow, 2 red, and 6 black; 75% were women, and the mean age was 85.1 years (± 9). Most patients were unable to walk. A total of 30 basic life support (BLS) ambulances, 3 advanced cardiac life support (ACLS) teams on fast cars, 2 buses, and 1 coordination team were deployed. A scoop and run approach was adopted with patients being transported to 15 health care facilities. The event was terminated at 5:43 am. Though the local mass casualty incident (MCI) response plan was correctly applied, the evacuation of the building was difficult due to the age and comorbidities of the patients. START failed to correctly identify patients categorized as minor. Communication problems arose on site that led to the late evacuation of critical patients.

Inter-Rater Reliability and Agreement Among Mass-Casualty Incident Algorithms Using a Pediatric Trauma Dataset: A Pilot Study

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.

Simple triage and rapid treatment protocol for emergency department mass casualty incident victim triage

Triage plays an essential role in emergency medical care. It is crucial to adopt appropriate triage in a mass casualty incident (MCI) when resources are limited. The simple triage and rapid treatment (START) protocol is commonly used worldwide; however, the effectiveness of the START protocol for emergency department (ED) triage is unclear. This study aimed to examine the accuracy of START for the ED triage of victims following a MCI. We retrospectively reviewed the records of victims who presented to our ED during a MCI response after a train crash. The ED nurses applied the START protocol upon patient arrival, and we used a consensus-based standard to determine the outcome-based categories of these same patients. We compared the START protocol and outcome-based categories. In addition, the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of START in terms of predicting surgery and ED disposition were determined. This study enrolled 47 patients (predominantly women, 68.1%; median age: 39.0years). Most victims were triaged into the START minor category (61.7%) and discharged from the ED (68.1%). Twenty-nine patients had matched START and outcome-based categories, whereas 2 patients were over-triaged and 16 patients were under-triaged. Additionally, the START system had acceptable AUC and sensitivities for predicting surgery and ED disposition (AUC/sensitivity/specificity for surgery: 0.850/100%/69.1%; AUC/sensitivity/specificity for admission: 0.917/93.3%/87.5%; AUC/sensitivity/specificity for intensive care unit (ICU)/ED death: 0.994/100%/97.8%). This study demonstrated poor agreement between START categories, as determined in the ED, and the consensus-based standard categories. However, the START protocol was acceptable in terms of identifying emergent patients (100% sensitivity for the immediate and deceased categories) and predicting ED disposition (surgery, admission, and ICU/ED mortality). Although START is not perfect, our findings suggest that it could be used for the ED triage of trauma-related MCI victims.