Articles: intensive-care-units.
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J Clin Monit Comput · Oct 2022
Multicenter StudyPredicting hypoglycemia in critically Ill patients using machine learning and electronic health records.
Hypoglycemia is a common occurrence in critically ill patients and is associated with significant mortality and morbidity. We developed a machine learning model to predict hypoglycemia by using a multicenter intensive care unit (ICU) electronic health record dataset. Machine learning algorithms were trained and tested on patient data from the publicly available eICU Collaborative Research Database. ⋯ The best-performing predictive model was the eXtreme gradient boosting model (XGBoost), which achieved an area under the received operating curve (AUROC) of 0.85, a sensitivity of 0.76, and a specificity of 0.76. The machine learning model developed has strong discrimination and calibration for the prediction of hypoglycemia in ICU patients. Prospective trials of these models are required to evaluate their clinical utility in averting hypoglycemia within critically ill patient populations.
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Intensive care medicine · Oct 2022
ReviewDelivering optimal renal replacement therapy to critically ill patients with acute kidney injury.
Critical illness is often complicated by acute kidney injury (AKI). In patients with severe AKI, renal replacement therapy (RRT) is deployed to address metabolic dysfunction and volume excess until kidney function recovers. ⋯ Recently completed trials have enhanced the evidence base regarding several RRT practices, most notably the timing of RRT initiation and anticoagulation for continuous therapies. Better evidence is still needed to clarify several aspects of care including optimal targets for ultrafiltration and effective strategies for RRT weaning and discontinuation.
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Critical illness is common throughout the world and is associated with high costs of care and resource intensity. The Corona virus disease 2019 (COVID-19) pandemic created a sudden surge of critically ill patients, which in turn led to devastating effects on health care systems worldwide and more so in Africa. This narrative report describes how an attempt was made at bridging the existing gaps in quality of care for critically ill patients at national and regional levels for COVID and the postpandemic era in a low income country.
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The appropriate level of postoperative critical care for patients undergoing emergency surgery is unknown. We aimed to assess the outcomes of postoperative patients treated in the intensive care unit (ICU) and high dependency care unit (HDU) after emergency surgery. ⋯ In this national registry study, postoperative critical care in ICU was associated with lower in-hospital mortality than in HDU for patients undergoing medium-risk and high-risk emergency surgery. Further research is needed to understand the role of critical care for surgical patients.
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Intensive care medicine · Oct 2022
ReviewElectroencephalogram in the intensive care unit: a focused look at acute brain injury.
Over the past decades, electroencephalography (EEG) has become a widely applied and highly sophisticated brain monitoring tool in a variety of intensive care unit (ICU) settings. The most common indication for EEG monitoring currently is the management of refractory status epilepticus. In addition, a number of studies have associated frequent seizures, including nonconvulsive status epilepticus (NCSE), with worsening secondary brain injury and with worse outcomes. ⋯ Increasingly, EEG is not just qualitatively described, but also quantitatively analyzed together with other modalities to generate innovative measurements with possible clinical relevance. In this review, we discuss the current knowledge and emerging applications of EEG in the ICU, including seizure detection, ischemia monitoring, detection of cortical spreading depolarizations, assessment of consciousness and prognostication. We also review some technical aspects and challenges of using EEG in the ICU including the logistics of setting up ICU EEG monitoring in resource-limited settings.