Endogenous insulin secretion in critically ill patients [PDF]
, 2012 1-pageGlucose-insulin system models can be used for improved glycemic control of critically ill patients. A key component of glucose-insulin models is pancreatic insulin secretion.
A Le Compte +7 more
core +3 more sources
Automated Detection of Rest Disruptions in Critically Ill Patients [PDF]
2020 42nd Annual International Conference of the IEEE Engineering
in Medicine & Biology Society (EMBC), Montreal, QC, Canada, 2020, pp.
5450-5454, 2020 Sleep has been shown to be an indispensable and important component of patients recovery process. Nonetheless, sleep quality of patients in the Intensive Care Unit (ICU) is often low, due to factors such as noise, pain, and frequent nursing care activities.
arxiv +1 more source
Reinforcement Learning For Survival, A Clinically Motivated Method For Critically Ill Patients [PDF]
arXiv, 2022 There has been considerable interest in leveraging RL and stochastic control methods to learn optimal treatment strategies for critically ill patients, directly from observational data. However, there is significant ambiguity on the control objective and on the best reward choice for the standard RL objective.
arxiv
Acute kidney injury in critically ill cancer patients : an update [PDF]
, 2016 Patients with cancer represent a growing group among actual ICU admissions (up to 20 %). Due to their increased susceptibility to infectious and noninfectious complications related to the underlying cancer itself or its treatment, these patients ...
Benoit, Dominique +3 more
core +2 more sources
Early KPC-Producing Klebsiella pneumoniae Bacteremia among Intensive Care Unit Patients Non-Colonized upon Admission [PDF]
Polish Journal of Microbiology, 2017 Among 140 patients colonized by KPC-producing Klebsiella pneumoniae (KPC-Kp) between fourth and seventh day of Intensive Care Unit stay, 24 developed bacteraemia immediately after colonization. Colistin-resistance of the colonizing isolate was the factor
Matthaios Papadimitriou-Olivgeris +10 more
doaj +1 more source
Classifying the evolution of COVID-19 severity on patients with combined dynamic Bayesian networks and neural networks [PDF]
arXiv, 2023 When we face patients arriving to a hospital suffering from the effects of some illness, one of the main problems we can encounter is evaluating whether or not said patients are going to require intensive care in the near future. This intensive care requires allotting valuable and scarce resources, and knowing beforehand the severity of a patients ...
arxiv
Transfusion thresholds and beyond [PDF]
, 2016 Comment on Liberal transfusion strategy improves survival in perioperative but not in critically ill patients. A meta-analysis of randomised trials.
Biancofiore, G +5 more
core +1 more source
Clinical practice guideline on gastrointestinal bleeding prophylaxis for critically ill patients : Endorsement by the Scandinavian Society of Anaesthesiology and Intensive Care Medicine [PDF]
, 2021 The Scandinavian Society of Anaesthesiology and Intensive Care Medicine Clinical practice Committee endorses the BMJ Rapid Recommendation Gastrointestinal bleeding prophylaxis for critically ill patients-a clinical practice guideline.
Chew, Michelle S. +5 more
core +1 more source
Smoking prevalence in Covid-19 patients [PDF]
arXiv, 2021 We investigate the prevalence rate of smoking in Covid-19 patients and examine whether there is a difference in the distribution of smokers between the two statistical populations of critically ill patients with Covid-19 and the entire Iranian population or not.
arxiv
DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning [PDF]
Scientific Reports (2019) 9:1879, 2018 Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging availability of streaming electronic health record data or capture time-sensitive individual ...
arxiv +1 more source