30 research outputs found
Twenty articles that critical care clinicians should read about COVID-19
Infection with the severe acute respiratory syndrome coronavirus-
2 (SARS-CoV-2) was first identified in December
2019 and has since become a worldwide pandemic,
challenging and sometimes overwhelming healthcare
systems as well as causing more than a million deaths
thus far. In just 10 months, over 80,000 indexed publications
have appeared that reference SARS-CoV-2 and the
associated Coronavirus disease 2019 (COVID-19). In this
article, we highlight 20 papers that are of particular relevance
to the critical care clinician. The papers are divided
into four broad topics: manifestations of severe COVID-
19 disease, pharmacological therapy for COVID-19, ventilatory
support for COVID-19 acute respiratory distress
syndrome (ARDS), and healthcare system and worker
stress. This list is not designed to be comprehensive but
rather to give the reader an overview of important early
papers and their findings.info:eu-repo/semantics/publishedVersio
Using Machine Learning to Predict Operative Time and Enhance Operating Room Scheduling for Robotic Hysterectomies
Antimutagenicity of amifostine against the anticancer drug fotemustine in the Drosophila somatic mutation and recombination (SMART) test
COST-EFFECTIVENESS ANALYSIS OF USTEKINUMAB VERSUS ADALIMUMAB, INFLIXIMAB AND VEDOLIZUMAB FOR THE TREATMENT OF PATIENTS WITH MODERATELY TO SEVERE ACTIVE CROHN'S DISEASE FOR TURKEY
[Abstract Not Available
InfoMuNet: Information-theory-based Functional Muscle Network Tracks Sensorimotor Integration Post-stroke
ABSTRACTSensory information is critical for motor coordination. However, understanding sensorimotor integration is complicated, especially in individuals with nervous system impairment. This research presents a novel functional biomarker, based on a nonlinear network graph of muscle connectivity, called InfoMuNet, to quantify the role of sensory information in motor performance. Thirty-two individuals with post-stroke hemiparesis performed a grasp-and-lift task while muscle activities were measured using eight surface electromyography (sEMG) sensors. Subjects performed the task with their affected hand before and after exposure to the sensory stimulation elicited by performing the task with the less-affected hand. For the first time, this work shows that InfoMuNet robustly quantifies functional muscle connectivity improvements in the affected hand after exposure of the less-affected side to sensory information. >90% of the subjects conformed with the improvement resulting from this sensory exposure. InfoMuNet also shows high sensitivity to tactile, kinesthetic, and visual input alterations at the subject level, highlighting the potential use in precision rehabilitation interventions.</jats:p
