Composite measures of physical fitness to discriminate between healthy aging and heart failure: the COmPLETE Study

BackgroundAging 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...

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Main Authors: Wagner, Jonathan (Author) , Knaier, Raphael (Author) , Königstein, Karsten (Author) , Klenk, Christopher (Author) , Carrard, Justin (Author) , Lichtenstein, Eric (Author) , Scharnagl, Hubert (Author) , März, Winfried (Author) , Hanssen, Henner (Author) , Hinrichs, Timo (Author) , Schmidt-Trucksäss, Arno (Author) , Arbeev, Konstantin (Author)
Format: Article (Journal)
Language:English
Published: 15 December 2020
In: Frontiers in physiology
Year: 2020, Volume: 11, Pages: 1-16
ISSN:1664-042X
DOI:10.3389/fphys.2020.596240
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.3389/fphys.2020.596240
Verlag, lizenzpflichtig, Volltext: https://www.frontiersin.org/articles/10.3389/fphys.2020.596240
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Author Notes:Jonathan Wagner, Raphael Knaier, Karsten Königstein, Christopher Klenk, Justin Carrard, Eric Lichtenstein, Hubert Scharnagl, Winfried März, Henner Hanssen, Timo Hinrichs, Arno Schmidt-Trucksäss and Konstantin Arbeev

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520 |a BackgroundAging 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.MethodsThe 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.ResultsNine 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.ConclusionHD 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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