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Composite Measures of Physical Fitness to Discriminate Between Healthy Aging and Heart Failure: The COmPLETE Study

Overview of attention for article published in Frontiers in Physiology, December 2020
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Composite Measures of Physical Fitness to Discriminate Between Healthy Aging and Heart Failure: The COmPLETE Study
Published in
Frontiers in Physiology, December 2020
DOI 10.3389/fphys.2020.596240
Pubmed ID
Authors

Jonathan Wagner, Raphael Knaier, Karsten Königstein, Christopher Klenk, Justin Carrard, Eric Lichtenstein, Hubert Scharnagl, Winfried März, Henner Hanssen, Timo Hinrichs, Arno Schmidt-Trucksäss, Konstantin Arbeev

Abstract

Aging and changing age demographics represent critical problems of our time. Physiological functions decline with age, often ending in a systemic process that contributes to numerous impairments and age-related diseases including heart failure (HF). We aimed to analyze whether differences in composite measures of physiological function [health distance (HD)], specifically physical fitness, between healthy individuals and patients with HF, can be observed. The COmPLETE Project is a cross-sectional study of 526 healthy participants aged 20-91 years and 79 patients with stable HF. Fifty-nine biomarkers characterizing fitness (cardiovascular endurance, muscle strength, and neuromuscular coordination) and general health were assessed. We computed HDs as the Mahalanobis distance for vectors of biomarkers (all and domain-specific subsets) that quantified deviations of individuals' biomarker profiles from "optimums" in the "reference population" (healthy participants aged <40 years). We fitted linear regressions with HD outcomes and disease status (HF/Healthy) and relevant covariates as predictors and logistic regressions for the disease outcome and sex, age, and age2 as covariates in the base model and the same covariates plus combinations of one or two HDs. Nine out of 10 calculated HDs showed evidence for group differences between Healthy and HF (p ≤ 0.002) and most models presented a negative estimate of the interaction term age by group (p < 0.05 for eight HDs). The predictive performance of the base model for HF cases significantly increased by adding HD General health or HD Fitness [areas under the receiver operating characteristic (ROC) curve (AUCs) 0.63, 0.89, and 0.84, respectively]. HD Cardiovascular endurance alone reached an AUC of 0.88. Further, there is evidence that the combination of HDs Cardiovascular endurance and General health shows superior predictive power compared to single HDs. HD composed of physical fitness biomarkers differed between healthy individuals and patients with HF, and differences between groups diminished with increasing age. HDs can successfully predict HF cases, and HD Cardiovascular endurance can significantly increase the predictive power beyond classic clinical biomarkers. Applications of HD could strengthen a comprehensive assessment of physical fitness and may present an optimal target for interventions to slow the decline of physical fitness with aging and, therefore, to increase health span.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 24%
Researcher 3 14%
Other 2 10%
Student > Ph. D. Student 1 5%
Student > Bachelor 1 5%
Other 2 10%
Unknown 7 33%
Readers by discipline Count As %
Nursing and Health Professions 2 10%
Medicine and Dentistry 2 10%
Sports and Recreations 2 10%
Biochemistry, Genetics and Molecular Biology 1 5%
Computer Science 1 5%
Other 3 14%
Unknown 10 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 January 2021.
All research outputs
#6,028,989
of 23,269,984 outputs
Outputs from Frontiers in Physiology
#2,725
of 13,993 outputs
Outputs of similar age
#146,577
of 506,176 outputs
Outputs of similar age from Frontiers in Physiology
#99
of 431 outputs
Altmetric has tracked 23,269,984 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 13,993 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. 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 506,176 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 431 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.