Neurocritical care
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The current terminology of delirium and encephalopathy is open to debate. As with any poorly understood disorder with an unknown mechanism, there is a range of opinions. Attention must be paid to a proliferation of new terms and the ease with which they were introduced. ⋯ Rather than expand the definitions of types of delirium and separate them from encephalopathy, we advocate a definition-encephalopathy with or without characteristics of delirium-with the understanding that agitated patients in a delirium are innately encephalopathic. We subscribe to the prevailing neurologic description of delirium. This would allow sufficient granularity for bedside use and prospective studies.
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Cardiac dysfunction is common in the days after severe traumatic brain injury (TBI) and may contribute to hypotension episodes, leading to worse outcomes. Little is known about cardiac function in the minutes and hours immediately following TBI. By using fluid percussion TBI in a swine model, we aimed to characterize the immediate post injury cardiac function. ⋯ Traumatic brain injury is associated with cardiac dysfunction and increased mortality, however there is still a limited understanding of the hemodynamic and echocardiographic response associated with TBI. In this study we demonstrate the hemodynamic and echocardiographic changes in the early stages of TBI in swine. The authors hope that these results may help better understanding on the management of patients with severe head injury.
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We aimed to identify continuous electroencephalogram (cEEG) markers associated with survival and death in patients with extracorporeal membrane oxygenation (ECMO) support under standardized sedation cessation protocol. ⋯ Although future multicenter studies with larger patient cohorts are certainly warranted, we were able to validate the feasibility of protocolized sedation cessation and cEEG analyses in the absence of a confounding effect from sedating medications. Moreover, we demonstrate some evidence that cEEG features of intact reactivity, present state changes, and fair/good variability in comatose patients on ECMO may be associated with survival at hospital discharge.
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Large and complex data sets are increasingly available for research in critical care. To analyze these data, researchers use techniques commonly referred to as statistical learning or machine learning (ML). The latter is known for large successes in the field of diagnostics, for example, by identification of radiological anomalies. ⋯ To conclude, there are important opportunities but also pitfalls to consider when performing clustering or predictive studies with ML techniques. We advocate careful valuation of new data-driven findings. More interaction is needed between the engineer mindset of experts in ML methods, the insight in bias of epidemiologists, and the probabilistic thinking of statisticians to extract as much information and knowledge from data as possible, while avoiding harm.