Articles: traumatic-brain-injuries.
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Skateboarding is a popular sport and U.S. trauma centers care for a significant number of skateboard-related injuries (SRIs). However, injury prevention strategies are still underdeveloped. This study was designed to compare the epidemiology, type, and location of skateboard injury as well as the use and influence of protective gear over two time periods. ⋯ Helmet use in patients with SRIs is low in all pediatric age groups. Helmet use and skate parks are protective against severe TBI. Older age children and male gender are at increased risk of severe TBI after skateboard-related injuries, and more targeted preventive education and legislation are needed.
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Minerva anestesiologica · May 2022
ReviewPerioperative management of severe brain injured patients.
Traumatic brain injury (TBI) is a leading cause of mortality and disability worldwide. Head injured patients may frequently require emergency neurosurgery. ⋯ This practical concise narrative review focused mainly on: 1) the management of severe TBI patients with neurosurgical lesions admitted to a spoke center (i.e. hospital without neurosurgery) and therefore needing a transfer to the hub center (i.e. hospital with neurosurgery); 2) the management of severe TBI patients with intracranial hypertension/brain herniation awaiting for neurosurgery; and 3) the neuromonitoring-oriented management in the immediate post-operative period. The proposals presented in this review mainly apply to severe TBI patients admitted to high-income countries.
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Patients with mild traumatic brain injury on CT scan are routinely admitted for inpatient observation. Only a small proportion of patients require clinical intervention. We recently developed a decision rule using traditional statistical techniques that found neurologically intact patients with isolated simple skull fractures or single bleeds <5 mm with no preinjury antiplatelet or anticoagulant use may be safely discharged from the emergency department. The decision rule achieved a sensitivity of 99.5% (95% CI 98.1% to 99.9%) and specificity of 7.4% (95% CI 6.0% to 9.1%) to clinical deterioration. We aimed to transparently report a machine learning approach to assess if predictive accuracy could be improved. ⋯ We found no clear advantages over the traditional prediction methods, although the models were, effectively, developed using a smaller data set, due to the need to divide it into training, calibration and validation sets. Future research should focus on developing models that provide clear advantages over existing classical techniques in predicting outcomes in this population.
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Observational Study
Validation of the Elderly Traumatic Brain Injury Score: an observational case-control study.
Traumatic brain injury (TBI) poses a particular health risk for the elderly. The recently developed elderly TBI (eTBI) score combines the prognostic information of the risk factors characteristic of the geriatric population. We aimed to determine its validity and reliability on an independent sample. ⋯ This is the first study confirming the validity of the eTBI Score and its close association with outcome of geriatric population after TBI. The novel 3-tier risk stratification scheme was applicable to both conservatively and surgically treated patients.
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Machine learning (ML) holds promise as a tool to guide clinical decision making by predicting in-hospital mortality for patients with traumatic brain injury (TBI). Previous models such as the international mission for prognosis and clinical trials in TBI (IMPACT) and the corticosteroid randomization after significant head injury (CRASH) prognosis calculators can potentially be improved with expanded clinical features and newer ML approaches. ⋯ We developed high-performing well-calibrated ML models for predicting in-hospital mortality for both the HIC and LMIC settings that have the potential to influence clinical management and traumatic brain injury patient trajectories.