Compliance with sepsis care bundles can significantly reduce death in hospital. However compliance rates are generally low.
Introducing automated drug dispensing systems on ICUs may have a high return on investment for hospitals.
In ICU patients with fever and known or suspected infection, paracetamol (1g IV every six hours) did not reduce the number of ICU-free days (23 versus 22 days in the placebo group; P=0.07).
New England Journal of Medicine
The review considers the physiological principles that guide the appropriate selection of intravenous fluids, as well as the recent literature evaluating their safety with respect to their composition and rate of administration.
Contact the library for a copy of this article
National Institute for Health and Care Excellence
NICE said there is not enough evidence to recommend 3 new blood tests for speeding up the identification of bloodstream bacteria and fungi for routine use in the NHS (LightCycler SeptiFast Test MGRADE, SepsiTest and IRIDICA BAC BSI assay).
Annals of Intensive Care 2015, 5:24
Hypovolemia, anemia and hypoxemia may cause critical deterioration in the oxygen delivery (DO2 ). Their early detection followed by a prompt and appropriate intervention is a cornerstone in the care of critically ill patients. And yet, the remedies for these life-threatening conditions, namely fluids, blood and oxygen, have to be carefully titrated as they are all associated with severe side-effects when administered in excess.
New technological developments enable us to monitor the components of DO 2 in a continuous non-invasive manner via the sensor of the traditional pulse oximeter. The ability to better assess oxygenation, hemoglobin levels and fluid responsiveness continuously and simultaneously may be of great help in managing the DO 2 .
The non-invasive nature of this technology may also extend the benefits of advanced monitoring to wider patient populations.
Intensive care units gather huge amounts of patient data, but much of it just gets thrown away. Give it to me, says Thomas Heldt
Interview from New Scientist Magazine issue 3040 published 26 September 2015
You’re trying to start a data revolution in hospitals. Why?
I’m interested in clinical environments such as intensive care units, operating rooms and emergency rooms. These are places where huge amounts of data is gathered from patients at great expense. What surprised me when I entered this field is that this data is collected and displayed on a monitor, but after a holding period of between 48 and maybe 96 hours, it just gets deleted. It never becomes part of the medical record. I see that as a wasted opportunity.
What happens to the data while it is collected and temporarily stored?
Clinical staff might look at the monitors to check the data as it is collected. They might scroll back to see what happened 8, 12 or 24 hours earlier. Occasionally they might want that kind of information if something really bad or unexpected happens, but even then they would probably rely on the medical notes rather than the real-time physiological data that came off the monitors. So usually not much is done with this data after it has been collected and displayed.
Which types of patients are you targeting?
People with brain injuries and very premature babies are two examples. Most babies go on to be just fine but some develop severe brain injuries or serious complications that affect their gut or lungs. A day or so before it happens, you might have no idea there’s anything wrong. It’s only when you see a massive bleed in the head on a scan, or when you send them to the imaging department and you discover that their gut has become necrotic. The aim of my approach is not only to analyse the data coming off the monitors but also to use it to predict and prevent these kinds of injuries and complications.
How do you make sense of the data?
It is coming out of a system that has been studied for over 200 years: our physiology. Physiologists are very good at rooting their understanding in the language of basic mathematics or in engineering principles such as conservation of momentum, flow or energy. Using these kinds of principles one can quantify in a mathematical sense what is going on in patients and build models to describe it. Such models will enable us to warn doctors, “OK, so this is about to happen”. Not only that, we will be able to say: “This is about to happen because of X, Y and Z, and here’s how you could intervene.”
Are we on the cusp of a transformation in how hospitals deal with this data?
I think we are. For example, Boston Children’s Hospital now captures all of the data from every bedside monitor routinely. We recently had the luxury of rolling back up to 48 hours into the intensive care data, and we did see trends. We saw how patients could deteriorate very, very slowly – something that you probably wouldn’t be able to pick up over the course of a single nursing shift. When we presented this to clinicians it was a revelation to them.
By Jessica Griggs via I can use intensive-care data to save people’s lives | New Scientist.