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Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database

Overview of attention for article published in Clinical Epidemiology, December 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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41 Mendeley
Title
Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database
Published in
Clinical Epidemiology, December 2017
DOI 10.2147/clep.s145530
Pubmed ID
Authors

Janet Sultana, Andrea Fontana, Francesco Giorgianni, Giorgio Basile, Elisabetta Patorno, Alberto Pilotto, Mariam Molokhia, Robert Stewart, Miriam Sturkenboom, Gianluca Trifirò

Abstract

Functional and cognitive domains have rarely been evaluated for their prognostic value in general practice databases. The aim of this study was to identify functional and cognitive domains in The Health Improvement Network (THIN) and to evaluate their additional value for the prediction of 1-month and 1-year mortality in elderly people. A cohort study was conducted using a UK nationwide general practitioner database. A total of 1,193,268 patients aged 65 years or older, of whom 15,300 had dementia, were identified from 2000 to 2012. Information on mobility, dressing and accommodation was recorded frequently enough to be analyzed further in THIN. Cognition data could not be used due to very poor recording of data in THIN. One-year and 1-month mortality was predicted using logistic models containing variables such as age, sex, disease score and functionality status. A significant but moderate improvement in 1-year and 1-month mortality prediction in elderly people was observed by adding accommodation to the variables age, sex and disease score, as the c-statistic (95% confidence interval [CI]) increased from 0.71 (0.70-0.72) to 0.76 (0.75-0.77) and 0.73 (0.71-0.75) to 0.79 (0.77-0.80), respectively. A less notable improvement in the prediction of 1-year and 1-month mortality was observed in people with dementia. Functional domains moderately improved the accuracy of a model including age, sex and comorbidities in predicting 1-year and 1-month mortality risk among community-dwelling older people, but they were much less able to predict mortality in people with dementia. Cognition could not be explored as a predictor of mortality due to insufficient data being recorded.

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X Demographics

The data shown below were collected from the profiles of 5 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 4 10%
Student > Ph. D. Student 4 10%
Other 3 7%
Student > Postgraduate 3 7%
Researcher 3 7%
Other 6 15%
Unknown 18 44%
Readers by discipline Count As %
Medicine and Dentistry 8 20%
Nursing and Health Professions 7 17%
Unspecified 2 5%
Psychology 2 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 3 7%
Unknown 18 44%
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 04 January 2018.
All research outputs
#14,407,575
of 25,584,565 outputs
Outputs from Clinical Epidemiology
#362
of 780 outputs
Outputs of similar age
#212,170
of 446,259 outputs
Outputs of similar age from Clinical Epidemiology
#14
of 31 outputs
Altmetric has tracked 25,584,565 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 780 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has gotten more attention than average, scoring higher than 53% of its peers.
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 446,259 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.