Prehospital and Disaster Medicine最新文献

Introduction: Innovative large language model (LLM)-powered chatbots, which are extremely popular nowadays, represent potential sources of information on resuscitation for the general public. For instance, the chatbot-generated advice could be used for purposes of community resuscitation education or for just-in-time informational support of untrained lay rescuers in a real-life emergency.

Study objective: This study focused on assessing performance of two prominent LLM-based chatbots, particularly in terms of quality of the chatbot-generated advice on how to give help to a non-breathing victim.

Methods: In May 2023, the new Bing (Microsoft Corporation, USA) and Bard (Google LLC, USA) chatbots were inquired (n = 20 each): "What to do if someone is not breathing?" Content of the chatbots' responses was evaluated for compliance with the 2021 Resuscitation Council United Kingdom guidelines using a pre-developed checklist.

Results: Both chatbots provided context-dependent textual responses to the query. However, coverage of the guideline-consistent instructions on help to a non-breathing victim within the responses was poor: mean percentage of the responses completely satisfying the checklist criteria was 9.5% for Bing and 11.4% for Bard (P >.05). Essential elements of the bystander action, including early start and uninterrupted performance of chest compressions with adequate depth, rate, and chest recoil, as well as request for and use of an automated external defibrillator (AED), were missing as a rule. Moreover, 55.0% of Bard's responses contained plausible sounding, but nonsensical guidance, called artificial hallucinations, that create risk for inadequate care and harm to a victim.

Conclusion: The LLM-powered chatbots' advice on help to a non-breathing victim omits essential details of resuscitation technique and occasionally contains deceptive, potentially harmful directives. Further research and regulatory measures are required to mitigate risks related to the chatbot-generated misinformation of public on resuscitation.

Introduction: Effective response to a mass-casualty incident (MCI) entails the activation of hospital MCI plans. Unfortunately, there are no tools available in the literature to support hospital responders in predicting the proper level of MCI plan activation. This manuscript describes the scientific-based approach used to develop, test, and validate the PEMAAF score (Proximity, Event, Multitude, Overcrowding, Temporary Ward Reduction Capacity, Time Shift Slot [Prossimità, Evento, Moltitudine, Affollamento, Accorpamento, Fascia Oraria], a tool able to predict the required level of hospital MCI plan activation and to facilitate a coordinated activation of a multi-hospital network.

Methods: Three study phases were performed within the Metropolitan City of Milan, Italy: (1) retrospective analysis of past MCI after action reports (AARs); (2) PEMAAF score development; and (3) PEMAAF score validation. The validation phase entailed a multi-step process including two retrospective analyses of past MCIs using the score, a focus group discussion (FGD), and a prospective simulation-based study. Sensitivity and specificity of the score were analyzed using a regression model, Spearman's Rho test, and receiver operating characteristic/ROC analysis curves.

Results: Results of the retrospective analysis and FGD were used to refine the PEMAAF score, which included six items-Proximity, Event, Multitude, Emergency Department (ED) Overcrowding, Temporary Ward Reduction Capacity, and Time Shift Slot-allowing for the identification of three priority levels (score of 5-6: green alert; score of 7-9: yellow alert; and score of 10-12: red alert). When prospectively analyzed, the PEMAAF score determined most frequent hospital MCI plan activation (>10) during night and holiday shifts, with a score of 11 being associated with a higher sensitivity system and a score of 12 with higher specificity.

Conclusions: The PEMAAF score allowed for a balanced and adequately distributed response in case of MCI, prompting hospital MCI plan activation according to real needs, taking into consideration the whole hospital response network.

In May 2023, the Italian region Emilia-Romagna was hit by intense rainfall, which caused extensive floods in densely populated areas. On May 4, 2023, a 12-month state of emergency was declared in the region with the activation of response and recovery plans. This field report provides an overview of the health response to the floods, paying particular attention to the measures put in place to ensure care for displaced populations and raising interesting points of discussion regarding the role of the health system during extreme weather events (EWEs). The considerations that emerge from this report underline the need for a primary care approach to disasters, especially when these occur in areas with a high prevalence of elderly resident population, and underscore the importance of integration of different levels of care.

Objectives: Identifying early predictors of dialysis requirements in earthquake-related injuries is crucial for optimal resource allocation and timely intervention. This study aimed to develop a predictive scoring system, named SAFE-QUAKE (Seismic Assessment of Kidney Function to Rule Out Dialysis Requirement), to identify patients at high risk of developing acute kidney injury (AKI) and requiring dialysis.

Methods: A retrospective analysis was conducted on a cohort of 205 patients presenting with earthquake-related injuries. Patients were divided into two groups based on their need for dialysis: the no dialysis group (n = 170) and the dialysis group (n = 35). Demographic, clinical, and laboratory data were collected and compared between the two groups to identify significant predictors of dialysis requirements. The parameters that would form the score were determined by conducting an importance analysis using artificial neural networks (ANNs) to identify parameters that exhibited statistically significant differences in univariate analysis.

Results: The dialysis group had a significantly longer median duration of being trapped under debris (48 hours) compared to the no dialysis group (eight hours). Blood gas and laboratory analyses revealed significant differences in pH levels, lactate values, creatinine levels, lactate dehydrogenase (LDH) levels, and aspartate transaminase (AST)-to-alanine transaminase (ALT) ratio between the two groups. Based on these findings, the SAFE-QUAKE rule-out scoring system was developed, incorporating entrapment duration (<45 hours), pH levels (>7.31), creatinine levels (<2mg/dL), LDH levels (<1600mg/dL), and the AST-to-ALT ratio (<2.4) as key predictors of dialysis requirements. This score included 139 patients, and among them, only one patient required dialysis, resulting in a negative predictive value of 99.29%.

Conclusions: The SAFE-QUAKE scoring system demonstrated a high negative predictive value of 99.29% in ruling out the need for dialysis among earthquake-related injury cases. This scoring system offers a practical approach for health care providers to identify patients at high risk of developing AKI and requiring dialysis in earthquake-affected regions.

Introduction: The Russian invasion of Ukraine in 2022 has affected more people and destroyed a local public health facility. When some territories in Ukraine were de-occupied, national and international mobile clinics (MCs) were involved for medical assistance to local inhabitants. Knowledge about population health, medical, and humanitarian needs after they have been de-occupied has to improve planning for health system response.

Objective: The aim of this study was to summarized the MC experience at the first month after the area was de-occupied, as well as to show out-patient visits and to identify a need for medicines and medical equipment in the MC.

Methods: The information related to the missions was obtained by direct observation and estimation on empirical data gathering in the field during a twelve-day mission in April-May 2022. All patients were divided by age, sex, and diseases according to the International Classification of Diseases-10 (ICD-10). During the twelve-day MC mission, medical assistance was provided for 478 out-patients. Descriptive statistical methods were undertaken using Microsoft Office 2019, Excel with data analysis.

Interventions: All out-patients were evaluated clinically. Personal medical cards were completed for each patient. Glucose testing as well as tests for coronavirus disease 2019/COVID-19 had been done, if it was necessary. All sick persons were treated for their disease.

Results: The priority needs for emergency and primary medical care, medicines, and hygienic and sanitation supplies after the area was de-occupied were fixed. The most frequent reasons for visiting the МС were: hypertension (27.6%), musculoskeletal-related (arthritis) diseases (26.9%), heart and peripheral vascular diseases (12.1%), upper gastrointestinal disorder (5.4%), upper respiratory infection (5.0%), and diabetes Type-2 (3.7%). Other diagnoses such as lower respiratory tract infection, diagnoses of the digestive system (hemorrhoids and perianal venous thrombosis), chronic obstructive pulmonary disease/COPD or asthma, eye diseases, gynecology-related condition, menstrual condition, and urinary tract disorder were distributed almost equally (0.21%-2.51%) among the patient population.

Conclusions: In the de-occupied territories, a health responder could be ready for medical assistance to patients with noncommunicable diseases (NCDs) as well as to support a person with psychological reactions who asked for sedatives and sleep-inducing medicines. These data clearly demonstrate that MCs must be equipped by blood pressure (BP) monitor, stethoscope, pulse oximeter, and diabetes testing kit glucose with essential medicines. This study improves health response planning for local civilian populations in de-occupied territory.

Background: The occurrence of behavioral health emergencies (BHEs) in children is increasing in the United States, with patient presentations to Emergency Medical Services (EMS) behaving similarly. However, detailed evaluations of EMS encounters for pediatric BHEs at the national level have not been reported.

Methods: This was a secondary analysis of a national convenience sample of EMS electronic patient care records (ePCRs) collected from January 1, 2018 through December 31, 2021. Inclusion criteria were all EMS activations documented as 9-1-1 responses involving patients < 18 years of age with a primary or secondary provider impression of a BHE. Patient demographics, incident characteristics, and clinical variables including administration of sedation medications, use of physical restraint, and transport status were examined overall and by calendar year.

Results: A total of 1,079,406 pediatric EMS encounters were present in the dataset, of which 102,014 (9.5%) had behavioral health provider impressions. Just over one-half of BHEs occurred in females (56.2%), and 68.1% occurred in patients aged 14-17 years. Telecommunicators managing the 9-1-1 calls for these events reported non-BHE patient complaints in 34.7%. Patients were transported by EMS 68.9% of the time, while treatment and/or transport by EMS was refused in 12.5%. Prehospital clinicians administered sedation medications in 1.9% of encounters and applied physical restraints in 1.7%. Naloxone was administered for overdose rescue in 1.5% of encounters.

Conclusion: Approximately one in ten pediatric EMS encounters occurring in the United States involve a BHE, and the majority of pediatric BHEs attended by EMS result in transport of the child. Use of sedation medications and physical restraints by prehospital clinicians in these events is rare. National EMS data from a variety of sources should continue to be examined to monitor trends in EMS encounters for BHEs in children.

Background: Pediatric patients transferred by Emergency Medical Services (EMS) from urgent care (UC) and office-based physician practices to the emergency department (ED) following activation of the 9-1-1 EMS system are an under-studied population with scarce literature regarding outcomes for these children. The objectives of this study were to describe this population, explore EMS level-of-care transport decisions, and examine ED outcomes.

Methods: This was a retrospective review of patients zero to <15 years of age transported by EMS from UC and office-based physician practices to the ED of two pediatric receiving centers from January 2017 through December 2019. Variables included reason for transfer, level of transport, EMS interventions and medications, ED medications/labs/imaging ordered in the first hour, ED procedures, ED disposition, and demographics. Data were analyzed with descriptive statistics, X test, point biserial correlation, two-sample z test, Mann-Whitney U test, and 2-way ANOVA.

Results: A total of 450 EMS transports were included in this study: 382 Advanced Life Support (ALS) runs and 68 Basic Life Support (BLS) runs. The median patient age was 2.66 years, 60.9% were male, and 60.7% had private insurance. Overall, 48.9% of patients were transported from an office-based physician practice and 25.1% were transported from UC. Almost one-half (48.7%) of ALS patients received an EMS intervention or medication, as did 4.41% of BLS patients. Respiratory distress was the most common reason for transport (46.9%). Supplemental oxygen was the most common EMS intervention and albuterol was the most administered EMS medication. There was no significant association between level of transport and ED disposition (P = .23). The in-patient admission rate for transported patients was significantly higher than the general ED admission rate (P <.001).

Conclusion: This study demonstrates that pediatric patients transferred via EMS after activation of the 9-1-1 system from UC and medical offices are more acutely ill than the general pediatric ED population and are likely sicker than the general pediatric EMS population. Paramedics appear to be making appropriate level-of-care transport decisions.

Disasters or mass-casualty incidents are uncommon events. The use of simulation is an ideal training modality in full-scale exercises as it immerses the participants in a replication of the actual environment where they can respond to simulated casualties in accordance with existing protocols.The objective of this scoping review is to answer the research question: "How effective is simulation, as assessed in full-scale exercises, for response to disasters and mass-casualty incidents world-wide?" Studies on full-scale exercises, as defined in World Health Organization (WHO) simulation exercise toolbox, that were published in peer-reviewed journals using the English language from 2001 through 2021 were included. Twenty studies were included from searching PubMed, Embase, and Web of Science. Simulated casualties were the most common simulation modality. Using Kirkpatrick's levels of evaluation to synthesize the data, simulation was reported to be generally effective and mostly demonstrated at the levels of learning of individuals and/or systems, as well as reaction of individuals. Evaluations at levels of behavior and results were limited due to the uncommon nature of disasters and mass-casualty incidents. However, evaluation outcomes across the full-scale exercises were varied, leading to the inability to consolidate effectiveness of simulation into a single measure. It is recommended for best evidence-based practices for simulation to be adhered to in full-scale exercises so that the trainings could translate into better outcomes for casualties during an actual disaster or mass-casualty incident. In addition, the reporting of simulation use in full-scale exercises should be standardized using a framework, and the evaluation process should be rigorous so that effectiveness could be determined and compared across full-scale exercises.