Critical care medicine
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Critical care medicine · Nov 2020
ReviewSociety of Critical Care Medicine's International Consensus Conference on Prediction and Identification of Long-Term Impairments After Critical Illness.
After critical illness, new or worsening impairments in physical, cognitive, and/or mental health function are common among patients who have survived. Who should be screened for long-term impairments, what tools to use, and when remain unclear. ⋯ Beginning with an assessment of a patient's pre-ICU functional abilities at ICU admission, clinicians have a care coordination strategy to identify and manage impairments across the continuum. As hospital discharge approaches, clinicians should use brief, standardized assessments and compare these results to patient's pre-ICU functional abilities ("functional reconciliation"). We recommend serial assessments for post-intensive care syndrome-related problems continue within 2-4 weeks of hospital discharge, be prioritized among high-risk patients, using the identified screening tools to prompt referrals for services and/or more detailed assessments.
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Critical care medicine · Nov 2020
Randomized Controlled Trial Multicenter StudyA Randomized Controlled Trial of Antithrombin Supplementation During Extracorporeal Membrane Oxygenation.
Supplementation of antithrombin might decrease the amount of heparin needed to achieve a given anticoagulation target during extracorporeal membrane oxygenation. However, exogenous antithrombin itself may increase the risk of bleeding. We conceived a study to evaluate the effect of antithrombin supplementation in adult patients requiring venovenous extracorporeal membrane oxygenation for respiratory failure on heparin dose, adequacy of anticoagulation, and safety. ⋯ Antithrombin supplementation may not decrease heparin requirement nor diminish the incidence of bleeding and/or thrombosis in adult patients on venovenous extracorporeal membrane oxygenation.
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Critical care medicine · Nov 2020
Multicenter StudyGraph Convolutional Networks-Based Noisy Data Imputation in Electronic Health Record.
A deep learning-based early warning system is proposed to predict sepsis prior to its onset. ⋯ Using Physionet Challenge 2019, the proposed method can accurately and early predict the onset of sepsis. The proposed method can be a practical early warning system in the environment of real hospitals.
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Critical care medicine · Nov 2020
Multicenter StudyThe Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.
Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results at the time of the blood culture order using routine data in the electronic health record. ⋯ Our novel models identified patients at low and high-risk for bacteremia and fungemia using routinely collected electronic health record data. Further research is needed to evaluate the cost-effectiveness and impact of model implementation in clinical practice.
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Concise "synthetic" review of the state of the art of management of acute ischemic stroke. ⋯ Appropriate treatment of ischemic stroke is essential in the reduction of mortality and morbidity. Management of stroke involves a multidisciplinary approach that starts and extends beyond hospital admission.