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

Duckitt, Roger; Buxton-Thomas, R.; Walker, Jeffrey; Cheek, Elizabeth; Bewick, Viv; Venn, Richard; Forni, Lui G.

doi:10.1093/bja/aem097

Cited by 162 publications

(149 citation statements)

References 18 publications

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“…Advanced age is independently associated with death and cardiac arrest, and use of age further improves predictive accuracy of many of the physiology based risk models (117)(118)(119)(120)(121)(122).…”

Section: Physiologicalmentioning

confidence: 99%

Frailty Assessment in Acute Care

2015

The Gerontologist

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IntroductionFor some people, ageing is associated with the experience of increased co-morbidity, functional impairment, poor resilience and heightened vulnerability to external stressors, resulting in reduced lifespan as well as health-span. This frailty phenomenon poses challenges to health care systems in the form of increased patient complexity and resource utilisation. The acute care setting, characterised by time-pressure and high patient turn-over, is under strain and struggles to recognise and subsequently reliably intervene, to prevent, reverse or halt the decline of this vulnerable cohort. MethodsThis mixed-methods study probes existing evidence and 'real-world' processes with a systematic review of frailty assessments developed or validated in the acute care setting and a survey of contemporaneous clinical practice in London Acute Medical Units. Content validation and understanding of contextual factors for ideal frailty assessment in acute care is explored using Delphi consensus and Focus Group methodology respectively. The resultant model is developed on existing retrospective national Hospital Episode Statistics data, and prospectively tested on observational data in a local Acute Medical Unit setting. ResultsExisting frailty scores are preponderantly biophysical in nature, and have poor predictive power for adverse outcomes in the acute care setting. In clinical practice, single-dimension assessment tools predominate. Frailty syndromes and previous high resource utilisation in the form of a simple, clinically relevant tool useful to the multidisciplinary team gain consensus as optimal assessment for the setting. Retrospective testing of the frailty model displays moderate predictive powers for adverse events (inpatient mortality, emergency readmission and institutionalisation) and prospective testing provides concurrent (Frailty Index, Age, Co-Morbidity) and comparative predictive validity (Frailty Index, Co-Morbidity, 2 admission National Early Warning Score) with existing risk stratification models in this setting. ConclusionsA risk prediction model based on frailty syndromes and previous high resource utilisation is a valid, feasible and useful for the acute care setting.

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Section: Physiologicalmentioning

confidence: 99%

Frailty Assessment in Acute Care

2015

The Gerontologist

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“…Twelve (Bell et al 2006;Cuthbertson et al 2007;Duckitt et al 2007;Goldhill et al 1999b;Goldhill et al 2005;Goldhill & McNarry. 2004;Garcea et al 2006;Hodgetts et al 2002;Lam et al 2006;Subbe et al 2001;Subbe et al 2006) studies were identified that were concerned with the development and/or testing of track and trigger systems.…”

Section: Evidence Reviewmentioning

confidence: 99%

“…The majority of identified studies were set on hospital wards. Three studies had a hospital-wide setting (including critical care areas) Goldhill et al 2005;Hodgetts et al 2002), three studies were based on a medical admissions unit (Duckitt et al 2007;Subbe et al 2001;Subbe et al 2003) and two on an accident and emergency department observation ward (Lam et al 2006;Subbe et al 2006). Fifteen studies were based in the UK (Cuthbertson et al 2007;Duckitt et al 2007;Garcea et al 2006;Goldhill et al 1999b;Goldhill et al 2005;Goldhill and McNarry 2004;Hodgetts et al 2002;Odell et al 2002;Paterson et al 2006;Pittard 2003;Priestley et al 2004;Subbe et al 2001;Subbe et al 2003;Subbe et al 2006), five in Australia (Bellomo et al 2004;Bristow et al 2000;Buist et al 2004;Buist et al 2002;Hillman et al 2005), two in the United States (DeVita et al 2004;Foraida et al 2003), one in Hong Kong (Lam et al 2006) and one in Sweden (Bell et al 2006).…”

Section: Evidence Reviewmentioning

confidence: 99%

“…There were seven UK-based diagnostic studies (Duckitt et al 2007;Garcea et al 2006;Goldhill et al 1999b;Goldhill and McNarry 2004;Hodgetts et al 2002;Subbe et al 2001 (Goldhill et al 1999b;Subbe et al 2001) used critical care admission as an outcome measure, three (Garcea et al 2006;Goldhill and McNarry 2004;Subbe et al 2001) used mortality, one (Hodgetts et al 2002) used the need for cardiopulmonary resuscitation and one (Duckitt et al 2007) used mortality and cardiac arrest. There was also one study from Hong Kong (Lam et al 2006) that used mortality and critical care admission as outcome measures, and two studies (Buist et al 2004 Five specific diagnostic studies carried out in the UK were identified (Garcea et al 2006;Goldhill et al 1999b;Goldhill and McNarry 2004;Hodgetts et al 2002;Subbe et al 2001).…”

Section: (Ii) Physiological Track and Trigger Systems As Currently Umentioning

confidence: 99%

“…Five studies (Duckitt et al 2007;Garcea et al 2006;Hodgetts et al 2002;Lam et al 2006;Subbe et al 2001) used track and trigger tools with aggregate scoring systems, one of which was based on EWS and two on MEWS. There was also one study that validated a newly developed scoring system -the Worthing Physiological Scoring System (Duckitt et al 2007).…”

Section: Aggregate Weighted Scoring Systemsmentioning

confidence: 99%

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Effectiveness of Bradycardia as a Single Parameter in the Pediatric Acute Response System

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Lee

et al. 2014

Korean J Crit Care Med

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Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation

Churpek

Wendlandt

Zadravecz

et al. 2016

Journal of Hospital Medicine

101

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Background Previous research investigating the impact of delayed intensive care unit (ICU) transfer on outcomes has utilized subjective criteria for defining critical illness. Objective To investigate the impact of delayed ICU transfer using the electronic Cardiac Arrest Risk Triage (eCART) score, a previously published early warning score, as an objective marker of critical illness. Design Observational cohort study Setting Medical-surgical wards at five hospitals between November 2008 and January 2013 Patients Ward patients Intervention None Measurements eCART scores were calculated for all patients, and the threshold with a specificity of 95% for ICU transfer (eCART >=60) denoted critical illness. A logistic regression model adjusting for age, sex, and surgical status was used to calculate the association between time to ICU transfer from first critical eCART value and in-hospital mortality. Results A total of 3,789 patients met the critical eCART threshold before ICU transfer, and median time to ICU transfer was 5.4 hours. Delayed transfer (>6 hours) occurred in 46% of patients (n=1,734) and was associated with increased mortality compared to patients transferred early (33.2% vs. 24.5%, p<0.001). Each one-hour increase in delay was associated with an adjusted 3% increase in odds of mortality (p<0.001). In patients who survived to discharge, delayed transfer was associated with longer hospital length of stay (median 13 vs. 11 days, p<0.001). Conclusions Delayed ICU transfer is associated with increased hospital length of stay and mortality. Use of an evidence-based early warning score, such as eCART, could lead to timely ICU transfer and reduced preventable death.

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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 † ‡

Abstract: A simple validated scoring system to predict mortality in medical patients with precise 'intervention-calling scores' has been developed.

Cited by 162 publications

References 18 publications

Frailty Assessment in Acute Care

Frailty Assessment in Acute Care

Effectiveness of Bradycardia as a Single Parameter in the Pediatric Acute Response System

Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation

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