Use of an Admission Early Warning Score to predict patient morbidity and mortality and treatment success—A prospective cohort study

Groarke, John D.; Gallagher, Joe; Stack, Janice; Aftab, AR; Dwyer, Cindy; McGovern, Rory; Courtney, Garry

doi:10.1016/j.ejim.2007.11.008

Cited by 3 publications

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“…In the same group of patients, however, we have noted that hospital stay correlates better with assistance parameters, ranging from a mean of 8.1 days, for the least dependent group to 11.1 days, for the most dependent one (data not shown). Only recently, Groarke et al (13) from Ireland have published a study of limited magnitude, regarding the use of an admission early warning score to predict early morbidity and mortality, reaching conclusions that are in agreement with our work.…”

Section: Discussionsupporting

confidence: 91%

In-hospital mortality and morbidity of elderly medical patients can be predicted at admission by the Modified Early Warning Score: a prospective study

Cei

Bartolomei

2009

International Journal of Clinical Practice

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Section: Discussionsupporting

confidence: 91%

In-hospital mortality and morbidity of elderly medical patients can be predicted at admission by the Modified Early Warning Score: a prospective study

Cei

Bartolomei

2009

International Journal of Clinical Practice

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Vital signs as determinants of immediate and longer term mortality outcome of patients admitted from Nursing Homes

et al. 2011

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A prognostic index for 1-year mortality can also predict in-hospital mortality of elderly medical patients

et al. 2015

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Elderly patients admitted to the hospital are at increased risk for both in-hospital and post-discharge mortality. Risk assessment models (RAMs) for in-hospital mortality are based mainly on physiological variables and a few laboratory data, whereas RAMs for late mortality usually include other domains such as disability and comorbidities. We aim to evaluate if a previous validated model for 1-year mortality (the Walter Score) would also work well in predicting in-hospital mortality. We retrospectively revised the medical records of patients admitted on our ward, from April to December, 2013. Data regarding gender, activities of daily living (ADLs), comorbidities, and routine laboratory tests were used to calculate a Modified Walter Score (MoWS). The main outcome measure was all cause, in-hospital mortality. The analysis involved 1,004 patients. Of these, 888 were discharged alive, and 116 (11.5 %) died during the hospitalization. The mean MoWS was 4.9 (±3.6) in the whole sample. Stratification into risk classes parallels with in-hospital mortality (Chi square for trend p < 0.001). When dichotomized, MoWS has a sensitivity of 97.4 % (95 % CI 92.1-99.3), and a specificity of 48.2 % (95 % CI 44.9-51.5) with a good prognostic accuracy (area under the ROC = 0.81; 95 % CI 0.78, 0.84). Subgroup analysis according to different age groups gives similar results. A simple RAM based on multiple domains, previously validated for predicting mortality of older adults within 1 year from the index hospitalization, can be useful at the moment of admission to Internal Medicine wards to accurately identify patients at low risk of in-hospital mortality.

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Use of an Admission Early Warning Score to predict patient morbidity and mortality and treatment success—A prospective cohort study

Cited by 3 publications

References 0 publications

In-hospital mortality and morbidity of elderly medical patients can be predicted at admission by the Modified Early Warning Score: a prospective study

In-hospital mortality and morbidity of elderly medical patients can be predicted at admission by the Modified Early Warning Score: a prospective study

Vital signs as determinants of immediate and longer term mortality outcome of patients admitted from Nursing Homes

A prognostic index for 1-year mortality can also predict in-hospital mortality of elderly medical patients

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