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Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models

Overview of attention for article published in Clinical Interventions in Aging, September 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

news
1 news outlet
twitter
2 X users

Citations

dimensions_citation
58 Dimensions

Readers on

mendeley
87 Mendeley
citeulike
1 CiteULike
Title
Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models
Published in
Clinical Interventions in Aging, September 2014
DOI 10.2147/cia.s65475
Pubmed ID
Authors

Jennifer M Stevenson, Josceline L Williams, Thomas G Burnham, A Toby Prevost, Rebekah Schiff, S David Erskine, J Graham Davies

Abstract

Adverse drug reaction (ADR) risk-prediction models for use in older adults have been developed, but it is not clear if they are suitable for use in clinical practice. This systematic review aimed to identify and investigate the quality of validated ADR risk-prediction models for use in older adults. Standard computerized databases, the gray literature, bibliographies, and citations were searched (2012) to identify relevant peer-reviewed studies. Studies that developed and validated an ADR prediction model for use in patients over 65 years old, using a multivariable approach in the design and analysis, were included. Data were extracted and their quality assessed by independent reviewers using a standard approach. Of the 13,423 titles identified, only 549 were associated with adverse outcomes of medicines use. Four met the inclusion criteria. All were conducted in inpatient cohorts in Western Europe. None of the models satisfied the four key stages in the creation of a quality risk prediction model; development and validation were completed, but impact and implementation were not assessed. Model performance was modest; area under the receiver operator curve ranged from 0.623 to 0.73. Study quality was difficult to assess due to poor reporting, but inappropriate methods were apparent. Further work needs to be conducted concerning the existing models to enable the development of a robust ADR risk-prediction model that is externally validated, with practical design and good performance. Only then can implementation and impact be assessed with the aim of generating a model of high enough quality to be considered for use in clinical care to prioritize older people at high risk of suffering an ADR.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Portugal 1 1%
Unknown 85 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 21%
Researcher 15 17%
Student > Master 11 13%
Other 10 11%
Student > Doctoral Student 6 7%
Other 14 16%
Unknown 13 15%
Readers by discipline Count As %
Medicine and Dentistry 26 30%
Pharmacology, Toxicology and Pharmaceutical Science 17 20%
Computer Science 6 7%
Nursing and Health Professions 4 5%
Agricultural and Biological Sciences 3 3%
Other 11 13%
Unknown 20 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 16 January 2019.
All research outputs
#3,415,510
of 25,374,917 outputs
Outputs from Clinical Interventions in Aging
#370
of 1,968 outputs
Outputs of similar age
#34,343
of 248,673 outputs
Outputs of similar age from Clinical Interventions in Aging
#12
of 43 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,968 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has done well, scoring higher than 80% 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 248,673 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 85% of its contemporaries.
We're also able to compare this research output to 43 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 72% of its contemporaries.