Articles: trauma.
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Curr Opin Crit Care · Dec 2023
ReviewCurrent knowledge and availability of machine learning across the spectrum of trauma science.
Recent technological advances have accelerated the use of Machine Learning in trauma science. This review provides an overview on the available evidence for research and patient care. The review aims to familiarize clinicians with this rapidly evolving field, offer perspectives, and identify existing and future challenges. ⋯ Machine Learning holds promise for actionable decision support in trauma science, but rigorous proof-of-concept studies are urgently needed. Future research should assess workflow integration, human-machine interaction, and, most importantly, the impact on patient outcome. Machine Learning enhanced causal inference for observational data carries an enormous potential to change trauma research as complement to randomized studies. The scientific trauma community needs to engage with the existing challenges to drive progress in the field.
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To characterize the role of neutrophil extracellular traps (NETs) in heterotopic ossification (HO) formation and progression and to use mechanical and pharmacological methods to decrease NETosis and mitigate HO formation. ⋯ These data provide a further understanding of the ability of neutrophils to form NETs at the injury site, clarify the role of neutrophils in HO, and identify potential diagnostic and therapeutic targets for HO mitigation.
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Current practice following injury within the United Kingdom is to receive surgery, at the institution of first contact regardless of ability to provide timely intervention and inconsiderate of neighbouring hospital resource and capacity. This can lead to a mismatch of demand and capacity, delayed surgery and stress within hospital systems, particularly with regards to elective services. We demonstrate through a multicentre, multinational study, the impact of this at scale. ⋯ Most trauma patients in the United Kingdom are managed exclusively at the place of first presentation, with no consideration of alternative pathways to local hospitals that may, at that time, offer increased operative capacity and a shorter waiting time. There is no oversight of trauma workload per capacity at neighbouring hospitals within a regional trauma network. This leads to a marked disparity in waiting time to surgery, and subsequently it can be inferred but not proven, poorer patient experience and outcomes. This inevitably leads to a strain on the overall trauma system and across several centres can impact on elective surgery recovery. We propose the consideration of inter-regional network collaboration, aligned with the Major Trauma System.
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Surgical treatment of AO/OTA 43-C pilon fractures has not yet taken a standard form. We aimed to evaluate whether patients that appeared to be labelled as unsupported columns according to the four-column theory would affect long-term clinical and radiological outcomes. ⋯ Level III.