The Critical Care Weekly Pulse™, a weekly e-news publication packed with career empowerment resources including the latest clinical, industry, and product news, clinical education, market research, and of course, the most recently posted jobs requiring expertise in the critical care nursing and medicine. Over 10,000 clinicians now receive the Critical Care Weekly Pulse.
Receive your own complimentary subscription to the Critical Care Weekly Pulse™
The faster fluid is removed using continuous dialysis from patients with failing kidneys, the higher the likelihood they will die in the next several months, according to a study published today in JAMA Network Open by University of Pittsburgh School of Medicine researchers.Nearly two-thirds of critically ill patients with acute kidney injury have extra fluid accumulating in their bodies, which can put pressure on their lungs and cause injury to other organs. To relieve that pressure, clinicians routinely remove the excess fluid from the blood while performing dialysis in the intensive care unit. Read More
A team of Japanese scientists has used facial recognition technology to develop an automated system that can predict when patients in the intensive care unit (ICU) are at high risk of unsafe behaviour such as accidentally removing their breathing tube, with moderate (75%) accuracy. The new research, being presented at this year's Euroanaesthesia congress (the annual meeting of the European Society of Anaesthesiology) in Vienna, Austria (1-3 June), suggests that the automated risk detection tool has the potential as a continuous monitor of patient's safety and could remove some of the limitations associated with limited staff capacity that make it difficult to continuously observe critically-ill patients at the bedside. Read More
After cardiac arrest and resuscitation, some patients will still be in a coma and treated at an intensive care unit. Their prospects are uncertain. Clinicians seek a reliable method to predict their outcomes. Researchers of the University of Twenty and the Medisch Spectrum Twenty hospitals have developed a learning network that is capable of interpreting EEG patterns. Artificial intelligence (AI) can give a reliable outcome prediction, providing a valuable extra source of information for decision-making. The researchers present their approach in Critical Care Medicine. Read More
William T. McGee, M.D., from the Baystate Medical Center in Springfield, Massachusetts, and colleagues retrospectively analyzed inpatient data from 2,723 adult patients in a 24-bed medical-surgical intensive care unit in a large level I trauma center from 2010 to 2012. The authors sought to evaluate the association between pressure injuries and length of stay and mortality.The researchers found that 6.6 percent of patients had a pressure injury at admission. Compared with patients without a pressure injury at admission, patients with a pressure injury had a longer mean unadjusted stay (15.6 versus 10.5 days) and higher in-hospital mortality rate (32.2 percent versus 18.3 percent). The association between pressure injuries and mean increase in length of stay remained with adjustment for other variables (mean difference, 3.1 days). Read More