Christian Martin-Gill

Over the past 2 decades, alpha-2 adrenergic agonists have emerged as common adulterants of the illicit opioid supply to potentiate their sedative effects (1,2). Xylazine, a veterinary tranquilizer,...

Aortic emergencies (AE) – aortic dissections (AD) and ruptured aortic aneurysms (AA) – are rare but potentially life-threatening diseases commonly encountered in emergency departments and during cr...

Providing high quality, evidence-based clinical care in the prehospital setting and establishing efficient and highly reliable prehospital systems of care has been identified as a priority for elev...

On March 25, 2026, the EMS Subboard of the American Board of Emergency Medicine (ABEM) approved modifications to the Core Content of Emergency Medical Services (EMS) Medicine, a subspecialty of Emergency Medicine. This revision was informed by growth and evolution of the subspecialty in conjunction with a job analysis survey that was distributed by ABEM to current EMS Medicine diplomates. The Core Content defines the foundational knowledge base for the delivery of healthcare in the out-of-hospital setting, the physician medical oversight of EMS clinicians, and the operation of EMS systems that is necessary to practice EMS Medicine. The Core Content is used to define the scope of the subspecialty of EMS Medicine and guide the Certification Examination blueprint for questions used in the subspecialty certification and maintenance of certification examinations. It also serves to inform EMS fellowship directors of the content that should comprise subspecialty training in EMS Medicine and informs candidates of the content of the clinical practice of the subspecialty. The 2026 update to the Core Content includes advances in EMS Medicine and expansion of topic areas identified in the job analysis survey to be of high importance and frequency to EMS physicians. The revised Core Content also involved restructuring of the major content areas and individual subtopics to align with the education framework of EMS Medicine physicians, reduce redundancy, and improve clarity on the content of each item.

Trauma is a leading cause of death among children the United States. Prehospital blood product administration is a potentially lifesaving measure for injured children. We evaluated how often injured children meet physiological criteria for transfusion, determined the use of prehospital blood products in this sample, and identified agency characteristics that can inform the implementation of additional prehospital transfusion programs. We conducted a retrospective analysis of the 2021-2024 National Emergency Medical Services Information System (NEMSIS) datasets. We included children (th centile for age and elevated heart rate above the 85^th centile or (b) a systolic blood pressure below the 1^st centile. We characterized encounters potentially eligible for prehospital blood transfusion, the use of blood products in this group, and the EMS agencies that cared for these patients. Of 2,492,731 encounters, 34,221 (1.37%, 95% confidence interval [CI] 1.36%, 1.39%) were potentially eligible for blood transfusion. Patients meeting these criteria were more frequently adolescents (71.1%) and were involved in falls (23.4%) or motor vehicle collisions (22.6%). Blood products were administered in 669 (0.027%; 95% CI 0.025%, 0.029%) encounters overall and to 1.01% (95% CI 0.91%, 1.13%) of encounters meeting criteria for blood transfusion eligibility. In agency-level analysis, 240/16,848 (1.4%) agencies provided blood products to children, and 84.4% of eligible patients were cared for by agencies whose most common level of service was advanced life support (ALS). In multivariable analysis, agencies caring for pediatric trauma patients meeting physiologic criteria for transfusion were more likely to have higher levels of service (ALS or critical care); rural; mixed volunteer/non-volunteer; and governmental non-fire, hospital, or private, non-hospital (vs fire departments). In a nationally representative prehospital sample, many injured children appeared eligible for transfusion. Prehospital blood product use was uncommon and varied by system factors. Expanding access will require implementation of blood programs among EMS agencies most likely to treat these patients, and consideration for equipment and protocols that allow for administration of blood to children.

Aims: AI in electrocardiography (ECG) has diverged into two paths: traditional signal processing with machine learning, and deep learning of raw waveforms. The former preserves physiological interpretability but may miss novel patterns, while the latter overlooks a century of ECG science. No framework yet integrates both. This study introduces a fusion model combining handcrafted feature-based random forest and waveform-based convolutional neural network to improve the diagnosis of acute coronary events. Methods and results: This prospective, multicentre cohort study included pre-hospital ECGs recorded on emergency medical services from patients with a chief complaint of chest pain. Using this dataset, we developed four fusion frameworks that integrate ECG features with waveform information: (1) decision-level fusion combining predictions from random forest and convolutional neural network (CNN); (2) decision-level fusion with retraining; (3) feature-level fusion by concatenating CNN embeddings with ECG features; and (4) feature-level fusion combining CNN embeddings with tree-level outputs from the random forest. This study comprised of 10 393 ECGs from 7397 patients. On both outcomes, acute coronary syndrome and occlusion myocardial infarction, the proposed decision fusion with retraining (Approach 2) achieved an AUROC of 0.878 (95% CI, 0.837–0.915) and 0.961 (95% CI, 0.934–0.983) on the test set and an average precision score of 0.749 (95% CI, 0.681–0.810) and 0.850 (95% CI, 0.763–0.918), respectively, outperforming all other proposed fusion and individual models. Conclusion: This study demonstrates the significance of fusion models that integrate complementary ECG representations to improve diagnostic accuracy in acute coronary events, highlighting a promising approach for real-time AI-augmented cardiovascular disease detection across diverse use cases.

Air medical transport (AMT) improves survival for selected trauma patients. Improving AMT triage is limited by a lack of evidence and a standardized definition for which patients and circumstances may warrant AMT. Our objective was to develop a consensus-based definition of AMT need. We recruited a multidisciplinary, nationally representative panel with expertise in AMT from trauma surgery, anesthesiology, critical care, emergency medicine, and emergency medical services (EMS). Panelists were presented with criteria from the literature representing the potential for AMT need that included patient injuries, time-sensitive interventions, and system factors. Panelists voted over 4 rounds to refine and select (≥70% agreement) a final set of criteria using a web-based Delphi methodology, including potential criteria combinations. A total of 32 of 45 (71.1%) invited panelists agreed to participate. From 66 initial criteria, panelists reached consensus on 18 patient factors, 6 time-sensitive interventions, 3 system factors, and 7 combinations of criteria. Two key themes emerged: the need for specialized care from air medical crews that may not be available from ground ambulance clinicians, as well as overall prehospital time-savings. After narrative feedback and refinement to eliminate redundant and overlapping criteria, an algorithm for AMT need was developed along with a decision flow diagram suitable for educational dissemination. We developed a consensus-based definition of AMT need for trauma patients that can be operationalized for AMT triage. Further validation of this concept with patient outcomes and identifying implementation barriers will contribute to field deployment of a useful AMT triage tool for EMS clinicians.