[HTML][HTML] Multicenter derivation and validation of an early warning score for acute respiratory failure or death in the hospital

MA Dziadzko, PJ Novotny, J Sloan, O Gajic… - Critical Care, 2018 - Springer
Background Acute respiratory failure occurs frequently in hospitalized patients and often
starts before ICU admission. A risk stratification tool to predict mortality and risk for …

[HTML][HTML] Prognostic accuracy of the Hamilton Early Warning Score (HEWS) and the National Early Warning Score 2 (NEWS2) among hospitalized patients assessed …

SM Fernando, AE Fox-Robichaud, B Rochwerg… - Critical care, 2019 - Springer
Abstract Background Rapid response teams (RRTs) respond to hospitalized patients
experiencing clinical deterioration and help determine subsequent management and …

[HTML][HTML] Effect of an automated notification system for deteriorating ward patients on clinical outcomes

CP Subbe, B Duller, R Bellomo - Critical Care, 2017 - Springer
Background Delayed response to clinical deterioration of ward patients is common. Methods
We performed a prospective before-and-after study in all patients admitted to two clinical …

[HTML][HTML] Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability …

MEH Ong, CH Lee Ng, K Goh, N Liu, ZX Koh… - Critical Care, 2012 - Springer
Introduction A key aim of triage is to identify those with high risk of cardiac arrest, as they
require intensive monitoring, resuscitation facilities, and early intervention. We aim to …

Modified early warning scores: inaccurate summation or inaccurate assignment of score?

M Edwards, H McKay, C Van Leuvan, I Mitchell - Critical Care, 2010 - Springer
Methods A prospective observational study of 9,672 vital sign sets and MEWS recordings in
315 adult medical and surgical patients admitted to four wards in both a tertiary and a …

[HTML][HTML] A deep learning model for real-time mortality prediction in critically ill children

SY Kim, S Kim, J Cho, YS Kim, IS Sol, Y Sung, I Cho… - Critical care, 2019 - Springer
Background The rapid development in big data analytics and the data-rich environment of
intensive care units together provide unprecedented opportunities for medical …

[HTML][HTML] Using Medical Emergency Teams to detect preventable adverse events

A Iyengar, A Baxter, AJ Forster - Critical Care, 2009 - Springer
Abstract Introduction Medical Emergency Teams (METs), also known as Rapid Response
Teams, are recommended as a patient safety measure. A potential benefit of implementing …

[HTML][HTML] Development of a new score for early mortality prediction in trauma ICU patients: RETRASCORE

L Serviá, JA Llompart-Pou, M Chico-Fernández… - Critical Care, 2021 - Springer
Background Severity scores are commonly used for outcome adjustment and benchmarking
of trauma care provided. No specific models performed only with critically ill patients are …

[HTML][HTML] 'Safety by DEFAULT': introduction and impact of a paediatric ward round checklist

S Sharma, MJ Peters - Critical Care, 2013 - Springer
Introduction Poor communication is a source of risk. This can be particularly significant in
areas of high clinical acuity such as intensive care. Ward rounds are points where large …

[HTML][HTML] The effect of treatment and clinical course during Emergency Department stay on severity scoring and predicted mortality risk in Intensive Care patients

BGJ Candel, W Raven, H Lameijer, WAMH Thijssen… - Critical Care, 2022 - Springer
Background Treatment and the clinical course during Emergency Department (ED) stay
before Intensive Care Unit (ICU) admission may affect predicted mortality risk calculated by …