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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.

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Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 12 21%
Researcher 7 12%
Student > Master 6 11%
Student > Ph. D. Student 3 5%
Student > Doctoral Student 3 5%
Other 7 12%
Unknown 19 33%
Readers by discipline Count As %
Medicine and Dentistry 12 21%
Nursing and Health Professions 7 12%
Sports and Recreations 5 9%
Agricultural and Biological Sciences 3 5%
Engineering 3 5%
Other 6 11%
Unknown 21 37%
Attention Score in Context

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
#20,110,957
of 25,584,565 outputs
Outputs from Clinical Interventions in Aging
#1,393
of 1,962 outputs
Outputs of similar age
#250,364
of 342,399 outputs
Outputs of similar age from Clinical Interventions in Aging
#33
of 44 outputs
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