A four item scale based on gait for the immediate global assessment of acutely ill medical patients – one look is more than 1000 words

Kellett, John; Clifford, Mary; Ridley, Alan; Murray, Alan; Gleeson, Margaret

doi:10.1016/j.eurger.2013.11.011

Cited by 29 publications

(18 citation statements)

References 21 publications

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“…Nutritional status was assessed by measuring the mid‐upper arm circumference . Impaired mobility on presentation, defined as lack of a stable independent gait when first assessed, was also recorded …”

Section: Methodsmentioning

confidence: 99%

QRS voltage is a predictor of in‐hospital mortality of acutely ill medical patients

Kellett

Opio

2018

Clinical Cardiology

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Section: Methodsmentioning

confidence: 99%

QRS voltage is a predictor of in‐hospital mortality of acutely ill medical patients

Kellett

Opio

2018

Clinical Cardiology

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“…Patients with a National Early Warning Score (NEWS) of zero were deemed to have normal vital signs since these values have the lowest association with death within 24 hours and are consistent with current single parameter “track and trigger” systems . Impaired mobility on presentation (IMOP) was defined in both cohorts as lack of a stable independent gait when first assessed . Therefore, patient who were unsteady on their feet, needed a walking stick or other aid to steady themselves, needed help to walk, or were bedridden were considered to have IMOP.…”

Section: Methodsmentioning

confidence: 99%

“…20 Impaired mobility on presentation (IMOP) was defined in both cohorts as lack of a stable independent gait when first assessed. 21 Therefore, patient who were unsteady on their feet, needed a walking stick or other aid to steady themselves, needed help to walk, or were bedridden were considered to have IMOP. It was not considered whether IMOP was acute, temporary or permanent.…”

Section: Data Collectionmentioning

confidence: 99%

A simple prognostic score predicts one‐year mortality of alert and calm emergency department patients: A prospective two‐center observational study

et al. 2020

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Study Objective To derive and validate a prognostic score to predict 1‐year mortality using vital signs, mobility and other variables that are readily available at the bedside at no additional cost. Methods Post hoc analysis of two independent prospective observational studies in two emergency departments, one in Denmark and the other in Switzerland. Participants Alert and calm emergency department patients. Measurements The prediction of mortality from presentation to 365 days by vital signs, mobility and other variables that are readily available at the bedside at no additional cost. Results One thousand six hundred and eighteen alert and calm patients were in the Danish cohort and 1331 in the Swiss cohort. Logistic regression identified age >68 years, abnormal vital signs, impaired mobility and the decision to admit as significant predictors of 365‐day mortality. A simple prognostic score awarded one point to each of these predictors. Less than two of these predictors were present in 45.6% of patients, and only 0.4% of these patients died within a year. If two or more of these predictors were present, 365‐day mortality increased exponentially. Conclusion Age >68 years, the decision for hospital admission, any vital sign abnormality at presentation and impaired mobility at presentation are equally powerful predictors of 1‐year mortality in alert and calm emergency department patients. If validated by others these predictors could be used to discharge patients with confidence since nearly half of these patients had less than two predictors and none of them died within 30 days. However, when two or more predictors were present 365‐day mortality increased exponentially.

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“…The exception to this is a single study in the AMU setting in rural Ireland (170), which reported AUCs of >0.8 for 30 day mortality and functional decline but the results of this secondary analysis of a clinical database was not reproduced in prospective observational study at a large teaching centre in the UK(173). (130).…”

Section: Risk Prediction Model Based On Frailty Syndromesmentioning

confidence: 99%

“…The studies were geographically distributed worldwide: 4 in the North America (41,163,166,167), Canada (36,(168)(169)(170)(171) There was variation in sample size, with the 3 large outliers unsurprisingly utilising secondary analysis of previous data (43,172,178) as methodology within single secondary care centres in the general internal medicine and elderly care setting. The observational studies were of relatively modest size ( Figure 3).…”

Section: General Features and Quality Assessmentmentioning

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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A four item scale based on gait for the immediate global assessment of acutely ill medical patients – one look is more than 1000 words

Cited by 29 publications

References 21 publications

QRS voltage is a predictor of in‐hospital mortality of acutely ill medical patients

QRS voltage is a predictor of in‐hospital mortality of acutely ill medical patients

A simple prognostic score predicts one‐year mortality of alert and calm emergency department patients: A prospective two‐center observational study

Frailty Assessment in Acute Care

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