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The prevalence and health consequences of frailty in a population-based older home care cohort: a comparison of different measures

Overview of attention for article published in BMC Geriatrics, July 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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1 news outlet
policy
1 policy source
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11 X users

Citations

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73 Dimensions

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109 Mendeley
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Title
The prevalence and health consequences of frailty in a population-based older home care cohort: a comparison of different measures
Published in
BMC Geriatrics, July 2016
DOI 10.1186/s12877-016-0309-z
Pubmed ID
Authors

Michael A. Campitelli, Susan E. Bronskill, David B. Hogan, Christina Diong, Joseph E. Amuah, Sudeep Gill, Dallas Seitz, Kednapa Thavorn, Walter P. Wodchis, Colleen J. Maxwell

Abstract

Evaluating different approaches to identifying frail home care clients at heightened risk for adverse health outcomes is an important but understudied area. Our objectives were to determine the prevalence and correlates of frailty (as operationally defined by three measures) in a home care cohort, the agreement between these measures, and their predictive validity for several outcomes assessed over one year. We conducted a retrospective cohort study with linked population-based administrative and clinical (Resident Assessment Instrument [RAI]) data for all long-stay home care clients (aged 66+) assessed between April 2010-2013 in Ontario, Canada (n = 234,552). We examined two versions of a frailty index (FI), a full and modified FI, and the CHESS scale, compared their baseline characteristics and their predictive accuracy (by calculating the area under the ROC curve [AUC]) for death, long-term care (LTC) admission, and hospitalization endpoints in models adjusted for age, sex and comorbidity. Frailty prevalence varied by measure (19.5, 24.4 and 44.1 %, for full FI, modified FI and CHESS, respectively) and was similar among female and male clients. All three measures were associated with a significantly increased risk of death, LTC admission and hospitalization endpoints in adjusted analyses but their addition to base models resulted in modest improvement for most AUC estimates. There were significant differences between measures in predictive accuracy, with the full FI demonstrating a higher AUC for LTC admission and CHESS a higher AUC for hospitalization - although none of the measures performed well for the hospitalization endpoints. The different approaches to detecting vulnerability resulted in different estimates of frailty prevalence among home care clients in Ontario. Although all three measures were significant predictors of the health outcomes examined, the gains in predictive accuracy were often modest with the exception of the full FI in predicting LTC admission. Our findings provide some support for the clinical utility of a comprehensive FI measure and also illustrate that it is feasible to derive such a measure at the population level using routinely collected data. This may facilitate further research on frailty in this setting, including the development and evaluation of interventions for frailty.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Unknown 108 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 19%
Other 13 12%
Researcher 13 12%
Student > Master 9 8%
Student > Bachelor 7 6%
Other 21 19%
Unknown 25 23%
Readers by discipline Count As %
Medicine and Dentistry 29 27%
Nursing and Health Professions 18 17%
Social Sciences 7 6%
Engineering 5 5%
Agricultural and Biological Sciences 3 3%
Other 14 13%
Unknown 33 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 21 December 2023.
All research outputs
#1,949,289
of 25,299,129 outputs
Outputs from BMC Geriatrics
#415
of 3,620 outputs
Outputs of similar age
#34,576
of 364,800 outputs
Outputs of similar age from BMC Geriatrics
#6
of 36 outputs
Altmetric has tracked 25,299,129 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,620 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done well, scoring higher than 88% 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 364,800 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.