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Predicting mortality in acutely hospitalized older patients: a retrospective cohort study

Overview of attention for article published in Internal and Emergency Medicine, January 2016
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Title
Predicting mortality in acutely hospitalized older patients: a retrospective cohort study
Published in
Internal and Emergency Medicine, January 2016
DOI 10.1007/s11739-015-1381-7
Pubmed ID
Authors

Jelle de Gelder, Jacinta A. Lucke, Noor Heim, Antonius J. M. de Craen, Shantaily D. Lourens, Ewout W. Steyerberg, Bas de Groot, Anne J. Fogteloo, Gerard J. Blauw, Simon P. Mooijaart

Abstract

Acutely hospitalized older patients have an increased risk of mortality, but at the moment of presentation this risk is difficult to assess. Early identification of patients at high risk might increase the awareness of the physician, and enable tailored decision-making. Existing screening instruments mainly use either geriatric factors or severity of disease for prognostication. Predictive performance of these instruments is moderate, which hampers successive interventions. We conducted a retrospective cohort study among all patients aged 70 years and over who were acutely hospitalized in the Acute Medical Unit of the Leiden University Medical Center, the Netherlands in 2012. We developed a prediction model for 90-day mortality that combines vital signs and laboratory test results reflecting severity of disease with geriatric factors, represented by comorbidities and number of medications. Among 517 patients, 94 patients (18.2 %) died within 90 days after admission. Six predictors of mortality were included in a model for mortality: oxygen saturation, Charlson comorbidity index, thrombocytes, urea, C-reactive protein and non-fasting glucose. The prediction model performs satisfactorily with an 0.738 (0.667-0.798). Using this model, 53 % of the patients in the highest risk decile (N = 51) were deceased within 90 days. In conclusion, we are able to predict 90-day mortality in acutely hospitalized older patients using a model with directly available clinical data describing disease severity and geriatric factors. After further validation, such a model might be used in clinical decision making in older patients.

X Demographics

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 17%
Student > Ph. D. Student 6 15%
Other 5 12%
Student > Postgraduate 4 10%
Student > Doctoral Student 2 5%
Other 6 15%
Unknown 11 27%
Readers by discipline Count As %
Medicine and Dentistry 15 37%
Nursing and Health Professions 3 7%
Computer Science 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Business, Management and Accounting 1 2%
Other 3 7%
Unknown 14 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 July 2016.
All research outputs
#14,984,029
of 25,217,627 outputs
Outputs from Internal and Emergency Medicine
#543
of 1,082 outputs
Outputs of similar age
#203,433
of 408,301 outputs
Outputs of similar age from Internal and Emergency Medicine
#16
of 26 outputs
Altmetric has tracked 25,217,627 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,082 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 408,301 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.