Articles: trauma.
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Eur J Trauma Emerg Surg · Dec 2024
ReviewCan "Stop The Bleed" training courses for laypersons improve hemorrhage control knowledge, skills, and attitudes? A systematic review.
In many regions of the world, most trauma deaths occur within 1-2 h of injury due to uncontrolled bleeding. For this reason, training lay first-person responders in trauma care, focusing on hemorrhage control, has been recommended. We hypothesized that STOP THE BLEED (STB) training courses that teach laypersons how to stop traumatic compressible bleeding immediately are needed to potentially prevent deaths due to hemorrhage. This systematic review will analyze the effect of the STB training course on the knowledge, skill, and attitudes of lay first-person responders for hemorrhage control. ⋯ STB courses for laypersons have demonstrated significant improvements in knowledge, skill, confidence, and willingness to intervene to stop traumatic exsanguination. The evaluation of clinically relevant patient outcomes, specifically their effect on preventable deaths from traumatic exsanguination, is needed to strengthen further the evidence behind the recommendations for more widespread teaching of "STB" courses.
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Journal of neurosurgery · Dec 2024
Multicenter StudyDerivation of the Quebec Brain Injury Categories for complicated mild traumatic brain injuries.
Approximately 10% of patients with mild traumatic brain injury (TBI) present with intracranial bleeding, and only 3.5% eventually require neurosurgical intervention, which often necessitates interhospital transfer. Better guidelines and recommendations are needed to manage complicated mild TBI in the emergency department (ED). The main objective of this study was to derive a clinical decision rule, the Quebec Brain Injury Categories (QueBIC), to predict the risk of adverse outcomes for complicated mild TBI in the ED. The secondary objective was to compare the QueBIC's performance with those of other existing guidelines. ⋯ QueBIC is a safe and effective tool to guide the management of patients presenting to the ED with complicated mild TBI. It accurately identifies patients at low risk for specialized neurotrauma or neurosurgical care. Further validation is required before its use in EDs.
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The complex regional pain syndrome type 1 (CRPS-1) is one of the most discussed painful syndromes due to the variability and severity of its symptoms. CRPS-1 generally occurs after a trauma, a fracture or a sprain followed by an immobilization. Classical diagnostic criteria are not always clear; hence, the diagnosis is difficult. ⋯ Adenosine triphosphate (ATP) exerts a fundamental role in the activation of innate cutaneous immune system, in the proliferation of keratinocytes and mast cells, in the release of several proinflammatory cytokines and in the microglia activation. It is essential to intervene on this pathology as soon as possible with drugs, as clodronate, able to reduce bone marrow edema and pain through the inhibition of the primary inflammatory process and the immune reaction, limiting the activation of macrophages and the release of cytokines activating nuclear growth factor (NGF). In this review the role of ATP, bisphosphonates and rehabilitation are discussed.
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Eur J Trauma Emerg Surg · Dec 2024
ReviewAI for detection, classification and prediction of loss of alignment of distal radius fractures; a systematic review.
Early and accurate assessment of distal radius fractures (DRFs) is crucial for optimal prognosis. Identifying fractures likely to lose threshold alignment (instability) in a cast is vital for treatment decisions, yet prediction tools' accuracy and reliability remain challenging. Artificial intelligence (AI), particularly Convolutional Neural Networks (CNNs), can evaluate radiographic images with high performance. This systematic review aims to summarize studies utilizing CNNs to detect, classify, or predict loss of threshold alignment of DRFs. ⋯ AI models for DRF detection show promising performance, indicating the potential of algorithms to assist clinicians in the assessment of radiographs. In addition, AI models showed similar performance compared to clinicians. No algorithms for predicting the loss of threshold alignment were identified in our literature search despite the clinical relevance of such algorithms.