✦ LIBER ✦

THERM: the Resuscitation Management score. A prognostic tool to identify critically ill patients in the emergency department

✍ Scribed by Cattermole, G. N.; Liow, E. C. H.; Graham, C. A.; Rainer, T. H.

Book ID: 125477939
Publisher: BMJ Publishing Group
Year: 2013
Tongue: English
Weight: 584 KB
Volume: 31
Category: Article
ISSN: 1472-0205
DOI: 10.1136/emermed-2013-202772

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

The Performance of Prognostic Scores in

The Performance of Prognostic Scores in Predicting Outcome for Critically Ill Patients in the Emergency Department (ED)

✍ E. Liow; G.N. Cattermole; C.A. Graham; T.H. Rainer 📂 Article 📅 2009 🏛 Elsevier Science 🌐 English ⚖ 54 KB

Derivation of a Prognostic Score for Ide

Derivation of a Prognostic Score for Identifying Critically Ill Patients in an Emergency Department Resuscitation Room: Cattermole GN, Mak SKP, Liow CHE, et al. Resuscitation 2009;80:1000–5

✍ Janetta Iwanicki 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 76 KB

Designing a nursing role to meet the nee

Designing a nursing role to meet the needs of critically ill patients in a UK emergency department

✍ Heather Jarman 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 57 KB

Application of microcomputers in the eme

Application of microcomputers in the emergency department to aid in patient management and documentation of the critically ill

✍ SJ Januzik 📂 Article 📅 1984 🏛 Elsevier Science 🌐 English ⚖ 135 KB

nosis, they were asked to perform their analyses in the same fashion that they used in the emergency department. Although times varied widely, no physician spent more than 5 minutes on any problem. The physicians' correct response rates were 86%, 49%, and 17% for single, double, and triple disorders

A pilot of a tool for examining nurses'

A pilot of a tool for examining nurses' knowledge of illicit substances affecting the care of critically ill patients in the emergency department

📂 Article 📅 2004 🏛 Elsevier Science ⚖ 137 KB

Prediction of cardiac arrest in critical

Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score

✍ Hock Ong, Marcus Eng (author);Lee Ng, Christina Hui (author);Goh, Ken (author);L 📂 Article 📅 2012 🏛 Springer (Biomed Central Ltd.) 🌐 English ⚖ 264 KB