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Derivation of a frailty index from the interRAI acute care instrument

Overview of attention for article published in BMC Geriatrics, March 2015
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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 (82nd percentile)

Mentioned by

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13 tweeters

Citations

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79 Dimensions

Readers on

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117 Mendeley
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1 CiteULike
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Title
Derivation of a frailty index from the interRAI acute care instrument
Published in
BMC Geriatrics, March 2015
DOI 10.1186/s12877-015-0026-z
Pubmed ID
Authors

Ruth E Hubbard, Nancye M Peel, Mayukh Samanta, Leonard C Gray, Brant E Fries, Arnold Mitnitski, Kenneth Rockwood

Abstract

A better understanding of the health status of older inpatients could underpin the delivery of more individualised, appropriate health care. 1418 patients aged ≥ 70 years admitted to 11 hospitals in Australia were evaluated at admission using the interRAI assessment system for Acute Care. This instrument surveys a large number of domains, including cognition, communication, mood and behaviour, activities of daily living, continence, nutrition, skin condition, falls, and medical diagnosis. Variables across multiple domains were selected as health deficits. Dichotomous data were coded as symptom absent (0 deficit) or present (1 deficit). Ordinal scales were recoded as 0, 0.5 or 1 deficit based on face validity and the distribution of data. Individual deficit scores were summed and divided by the total number considered (56) to yield a Frailty index (FI-AC) with theoretical range 0-1. The index was normally distributed, with a mean score of 0.32 (±0.14), interquartile range 0.22 to 0.41. The 99% limit to deficit accumulation was 0.69, below the theoretical maximum of 1.0. In logistic regression analysis including age, gender and FI-AC as covariates, each 0.1 increase in the FI-AC increased the likelihood of inpatient mortality twofold (OR: 2.05 [95% CI 1.70 - 2.48]). Quantification of frailty status at hospital admission can be incorporated into an existing assessment system, which serves other clinical and administrative purposes. This could optimise clinical utility and minimise costs. The variables used to derive the FI-AC are common to all interRAI instruments, and could be used to precisely measure frailty across the spectrum of health care.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Canada 2 2%
Estonia 1 <1%
Spain 1 <1%
Unknown 111 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 20%
Student > Master 19 16%
Student > Doctoral Student 13 11%
Other 12 10%
Student > Postgraduate 9 8%
Other 23 20%
Unknown 18 15%
Readers by discipline Count As %
Medicine and Dentistry 51 44%
Nursing and Health Professions 18 15%
Biochemistry, Genetics and Molecular Biology 5 4%
Computer Science 3 3%
Psychology 3 3%
Other 16 14%
Unknown 21 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 27 October 2018.
All research outputs
#3,024,594
of 19,211,930 outputs
Outputs from BMC Geriatrics
#720
of 2,343 outputs
Outputs of similar age
#42,165
of 236,774 outputs
Outputs of similar age from BMC Geriatrics
#1
of 1 outputs
Altmetric has tracked 19,211,930 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,343 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 69% 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 236,774 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them