Articles: trauma.
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Recent evidence suggests that frailty may be a more reliable measure than age to predict outcomes following trauma. Frailty leads to prolonged hospitalisation and increased burden on the hospital system in older patients. The aim of this study is to review the prevalence of frailty in our trauma patients and the association of frailty with hospital-based and twelve-month outcomes. ⋯ After adjusting for confounding factors, frailty is associated with nearly five times the increase in odds of a discharge to further inpatient care. Long term outcomes are also significantly poorer for patients with frailty. Identifying frailty on admission may help outcomes by targeting this patient group and optimising healthcare resource usage.
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Collecting patient-reported outcomes in a systematic fashion is important to understand recovery trajectories and compare performance between different services and fields of care. These outcomes can be collected through a variety of means, but studies comparing different follow-up methods in patients with a variety of injury types are scarce. This study aimed to compare follow-up data from three injury registries to quantify patient preference for telephone versus online follow-up, determine factors associated with choosing online follow-up, and compare response rates based on the patient's preferred follow-up method. ⋯ While follow-up preference and completion were higher for telephone-based follow-ups, the findings suggest a patient's preference for completing post-injury follow-ups differs according to the type of injury they sustained, and that allowing patients a choice of their preferred follow-up method is important. The variety of follow-up methods offered should therefore reflect the needs of different patient groups, which may allow for the development of algorithms or workflow processes. Directing certain patients towards a particular follow-up method could deliver higher and more efficient follow-up rates.
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Introduction: Unplanned intensive care unit (ICU) admissions are associated with increased morbidity and mortality. This study uses interpretable machine learning to predict unplanned ICU admissions for initial nonoperative trauma patients admitted to non-ICU locations. Methods: TQIP (2020-2021) was queried for initial nonoperative adult patients admitted to non-ICU locations. ⋯ Dependency plots showed greater SHAP values for greater ISS, age, and presence of comorbidities. Conclusions: Machine learning may outperform prior attempts at predicting the risk of unplanned ICU admissions in trauma patients while identifying unique predictors. Despite this progress, further research is needed to improve predictive performance by addressing class imbalance limitations.
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Background: Mechanical ventilation (MV) is a clinically important measure for respiratory support in critically ill patients. Although moderate tidal volume MV does not cause lung injury, it can further exacerbate lung injury in a pathological state such as sepsis. This pathological process is known as the "two-hit" theory, whereby an initial lung injury (e.g., infection, trauma, or sepsis) triggers an inflammatory response that activates immune cells, presenting the lung tissue in a fragile state and rendering it more susceptible to subsequent injury. ⋯ Different species of HMGB1 knockout mice have different lung-protective mechanisms in the two-hit model, and location is the key to function. Specifically, LysM HMGB1 -/- mice due to the deletion of HMGB1 in myeloid cells resulted in a pulmonary-protective mechanism that was associated with a downregulation of the inflammatory response. EC-HMGB1 -/- mice are deficient in HMGB1 owing to endothelial cells, resulting in a distinct pulmonary-protective mechanism independent of the inflammatory response and more relevant to the improvement of alveolar-capillary permeability. iHMGB1 -/- mice, which are systemically HMGB1-deficient, share both of these lung-protective mechanisms.
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The "July Effect" hypothesizes increased morbidity and mortality after the addition of inexperienced physicians at the beginning of an academic year. However, the impact of newer members on neurosurgical teams managing patients with traumatic brain injury (TBI) has yet to be examined. This study conducted a nationwide analysis to evaluate the existence of the "July Effect" in the setting of patients with TBI. ⋯ The findings suggested that there is no "July Effect" on patients with TBI treated at teaching hospitals in the United States.