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Developing sarcopenia criteria and cutoffs for an older Caucasian cohort – a strictly biometrical approach

Overview of attention for article published in Clinical Interventions in Aging, August 2018
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Title
Developing sarcopenia criteria and cutoffs for an older Caucasian cohort – a strictly biometrical approach
Published in
Clinical Interventions in Aging, August 2018
DOI 10.2147/cia.s167899
Pubmed ID
Authors

Wolfgang Kemmler, Simon von Stengel, Matthias Kohl

Abstract

The aim of this strictly statistical approach was to provide a figure discrimination in a homogeneous cohort that is based on a main component, which includes disability, physical performance, and autonomy parameters. We used data of 939 community-dwelling men aged ≥70 years, living in the area of Erlangen-Nürnberg, Germany. Briefly, we conducted a scaled principal component analysis based on criteria related to "physical function", "disability", "weakness", and "autonomy" to identify men who are likely to have sarcopenia as per the recognized sarcopenia criteria. Next, we applied fast-and-frugal decision trees, logistic regression, and classification and regression decision trees to classify men with and without sarcopenia, applying the 5% prevalence rate identified for this cohort by recent studies. In summary, the best fast-and-frugal decision trees included gait velocity, handgrip strength, and two skeletal muscle mass indices (SMI) - appendicular skeletal muscle mass (ASMM)/body mass index (BMI) and ASMM/height2. Briefly, men below the cutoff point of 1.012 m/s for gait velocity were directly classified as sarcopenic. Faster men with a handgrip strength of >34.5 kg were excluded from further screening, while their weaker peers were assessed for SMI. Firstly, an ASMM/BMI-based exclusion criterion of >0.886 indicates no sarcopenia; while in men with a lower BMI-based SMI, an ASMM/height2 of <7.25 kg/m2 indicates sarcopenia. Of importance, about 72% of the participants can be classified without an SMI assessment. The present approach that applied recognized sarcopenia criteria and was based on a predominately functional understanding of sarcopenia provided a simple and feasible decision rule for sarcopenia discrimination. In summary, we consider our approach as a strictly biometrical contribution within the development of sarcopenia screening methods. However, our tool needs to be further evaluated to validate its appropriateness to discriminate sarcopenia in this relevant cohort.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 26%
Student > Master 6 18%
Student > Doctoral Student 3 9%
Researcher 3 9%
Student > Ph. D. Student 2 6%
Other 5 15%
Unknown 6 18%
Readers by discipline Count As %
Medicine and Dentistry 10 29%
Nursing and Health Professions 5 15%
Engineering 3 9%
Sports and Recreations 3 9%
Immunology and Microbiology 1 3%
Other 4 12%
Unknown 8 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 August 2018.
All research outputs
#10,253,279
of 13,444,886 outputs
Outputs from Clinical Interventions in Aging
#985
of 1,372 outputs
Outputs of similar age
#185,273
of 268,871 outputs
Outputs of similar age from Clinical Interventions in Aging
#20
of 27 outputs
Altmetric has tracked 13,444,886 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,372 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 19th percentile – i.e., 19% 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 268,871 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.