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Worthing physiological scoring system: derivation and validation of a physiological early-warning system for medical admissions. An observational, population-based single-centre study† ‡

TLDR
The Worthing PSS was developed from the regression coefficients associated with each variable and showed good discrimination with an area under the receiver operating characteristic curve, 0.74, excluding age as a variable.
Abstract
Background Several physiological scoring systems (PSS) have been proposed for identifying those at risk of deterioration. However, the chosen specific physiological values chosen and the scores allocated have not been prospectively validated. In this study, we investigate the relative contributions of the ventilatory frequency, heart rate, arterial pressure, temperature, oxygen saturation, and conscious level to mortality in order to devise a robust scoring system. All data were collected on admission to the emergency unit. Precise ‘intervention-calling scores’ could then be derived to trigger interventions. Methods Our observational, population-based single-centred study took place in a 602-bedded district general hospital. Patients admitted to the emergency care unit at Worthing general hospital during an initial study period between July and November 2003 (n = 3184) and a further validation period between October and November 2005 (n = 1102) were included. Results Multivariate logistic regression analysis demonstrated that a ventilatory frequency ≥20 min−1, heart rate ≥102 min−1, systolic blood pressure ≤99 mm Hg, temperature Conclusions A simple validated scoring system to predict mortality in medical patients with precise ‘intervention-calling scores’ has been developed.

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European Resuscitation Council Guidelines for Resuscitation 2010 Section 4 Adult advanced life support

TL;DR: Cardiothoracic anesthetic, Southampton General Hospital, Southampton, UK Anesthesia and Intensive Care Medicine, Royal United Hospital, Bath, UK Anaesthesia and intensive care medicine, Southmead Hospital, Bristol, UK Surgical ICU, Oslo University Hospital Ulleval, Oslo, Norway Department of Cardiology, Academic Medical Center, Amsterdam, The Netherlands Critical Care and Resuscitation, University of Warwick, Warwick Medical School, Warwick, UK
Journal ArticleDOI

European Resuscitation Council Guidelines for Resuscitation 2015: Section 3. Adult advanced life support.

TL;DR: Anaesthesia and Intensive Care Medicine, Southmead Hospital, Bristol, UK Anaesthesia and intensive care Medicine, Royal United Hospital, Bath, UK School of Clinical Sciences, University of Bristol, United Kingdom, UK Department of Anesthesiology, and intensive care medicine, The National Institute for Mental Health (NIMH), London, UK NHS Foundation Trust, Coventry, UK The National Health Service (NHS), Coventry and Birmingham, UK Heart of England (HSE), Birmingham, Birmingham and The Royal National Institute of Neurological and Women's Health Service
References
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Book

Applied Logistic Regression

TL;DR: Hosmer and Lemeshow as discussed by the authors provide an accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets.
Journal ArticleDOI

Applied Logistic Regression.

TL;DR: Applied Logistic Regression, Third Edition provides an easily accessible introduction to the logistic regression model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.
Journal ArticleDOI

A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

James A. Hanley, +1 more
- 01 Sep 1983 - 
TL;DR: This paper refines the statistical comparison of the areas under two ROC curves derived from the same set of patients by taking into account the correlation between the areas that is induced by the paired nature of the data.
Journal ArticleDOI

Validation of a modified Early Warning Score in medical admissions

TL;DR: The ability of a modified Early Warning Score (MEWS) to identify medical patients at risk of catastrophic deterioration in a busy clinical area was investigated and could be created, using nurse practitioners and/or critical care physicians, to respond to high scores and intervene with appropriate changes in clinical management.
Journal ArticleDOI

What do we mean by validating a prognostic model

TL;DR: How to validate a model is considered and it is suggested that it is desirable to consider two rather different aspects - statistical and clinical validity - and some general approaches to validation are examined.
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