Muscle wasting and sarcopenia in heart failure and beyond: update 2017

Springer, Jochen; Springer, Joshua‐I.; Anker, Stefan D.

doi:10.1002/ehf2.12237

Cited by 180 publications

(154 citation statements)

References 116 publications

(215 reference statements)

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“…The links with long‐term conditions mean that sarcopenia is of growing interest to a wide range of clinical specialties . Studies highlight an increased prevalence of sarcopenia in those with chronic obstructive pulmonary disease, chronic heart failure, and chronic liver disease . Interactions with skeletal muscle may also be important in the pathogenesis of long‐term conditions, for example, osteoporosis and heart failure .…”

Section: Introductionmentioning

confidence: 99%

Sarcopenia, long‐term conditions, and multimorbidity: findings from UK Biobank participants

Dodds

Granic

Robinson

et al. 2019

J cachexia sarcopenia muscle

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Background Sarcopenia, the loss of muscle strength and mass, predicts adverse outcomes and becomes common with age. There is recognition that sarcopenia may occur at younger ages in those with long‐term conditions (LTCs) as well as those with multimorbidity (the presence of two or more LTCs), but their relationships have been little explored. Our aims were to describe the prevalence of sarcopenia in UK Biobank, a large sample of men and women aged 40–70 years, and to explore relationships with different categories of LTCs and multimorbidity. Methods We used data from 499 046 participants in the baseline of UK Biobank. Our main outcome was probable sarcopenia based on maximum grip strength below sex‐specific cut‐points. Participants' LTCs were recorded during an interview and categorized against a hierarchy. We used logistic regression to examine the independent associations between each category of LTCs and probable sarcopenia, including adjustment for age, sex, and body mass index. We also examined the association with multimorbidity. Results Probable sarcopenia had an overall prevalence of 5.3% and increased with age. The categories with the strongest associations with probable sarcopenia were musculoskeletal/trauma [OR 2.17 (95% CI: 2.11, 2.23)], endocrine/diabetes [OR 1.49 (95% CI: 1.45, 1.55)], and neurological/psychiatric [OR 1.39 (95% CI: 1.34, 1.43)] LTCs. Almost half of the sample (44.5%) had multimorbidity, and they were at nearly twice the odds of probable sarcopenia [OR 1.96 (95% CI: 1.91, 2.02)] compared with those without. Conclusions We have shown an overall prevalence of 5.3% of probable sarcopenia at ages 40–70 in UK Biobank. The risk of probable sarcopenia was higher in those with some categories of LTCs, suggesting that these groups may stand to benefit from assessment of sarcopenia, during mid‐life as well as old age.

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Section: Introductionmentioning

confidence: 99%

Sarcopenia, long‐term conditions, and multimorbidity: findings from UK Biobank participants

Dodds

Granic

Robinson

et al. 2019

J cachexia sarcopenia muscle

View full text Add to dashboard Cite

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“…Loss of skeletal muscle mass and strength with ageing is the hallmarks of increasingly recognized sarcopenia and dynapenia . These structural and functional senescence‐related changes in skeletal muscle are accompanied by an increased risk of morbidity and mortality …”

Section: Introductionmentioning

confidence: 99%

Improved strength prediction combining clinically available measures of skeletal muscle mass and quality

Bourgeois

Fan

Johannsen

et al. 2018

J cachexia sarcopenia muscle

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Background Measures of skeletal muscle function decline at a faster rate with ageing than do indices of skeletal muscle mass. These observations have been attributed to age‐related changes in muscle quality, another functional determinant separate from skeletal muscle mass. This study tested the hypothesis that improved predictions of skeletal muscle strength can be accomplished by combining clinically available measures of skeletal muscle mass and quality. Methods The participants included 146 healthy adult (age ≥ 18 years, range 18–77 years; X ± SD 47 ± 17 years and body mass index 16.5–51.8 kg/m 2 ; 27.7 ± 6.2 kg/m 2 ) men ( n = 60) and women ( n = 86) in whom skeletal muscle mass was estimated as appendicular lean soft tissue (LST) measured by dual‐energy X‐ray absorptiometry and skeletal muscle quality as bioimpedance analysis‐derived phase angle and B‐mode‐evaluated echogenicity of mid‐thigh skeletal muscle. Strength of the right leg and both arms was quantified as knee isokinetic extension and handgrip strength using dynamometers. The statistical significance of adding phase angle or echogenicity to strength prediction multiple regression models that included extremity‐specific LST and other covariates (e.g. age and sex) was evaluated to test the study hypothesis. Results Right leg LST mass alone was significantly ( P < 0.0001) correlated with isokinetic right leg strength ( R 2 = 0.57). The addition of segmental phase angle measured in the right leg at 50 kHz increased the R 2 of this model to 0.66 ( P < 0.0001); other phase angle frequencies (5 and 250 kHz) did not contribute significantly to these models. Results were similar for both right and left arm handgrip strength prediction models. Adding age and sex as model covariates increased the R 2 values of these models further (e.g. right leg strength model R 2 increased to 0.71), but phase angle continued to remain a significant (all P < 0.01) predictor of extremity strength. Similarly, when predicting isokinetic right leg strength, mid‐thigh skeletal muscle echogenicity added significantly ( P < 0.0001) to right leg LST, increasing R 2 from 0.57 to 0.64; age was a significant ( P < 0.0001) covariate in this model, increasing R 2 further to 0.68. Conclusions The hypothesis of the current study was confirmed, strongly supporting and extending earlier reports by quantifying the combined independent effects of skeletal muscle mass and quality on lo...

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“…[32][33][34][35][36][37] Moreover, exercise mimetics such as trimetazidine are of interest in the therapy of muscle atrophy, 38 but also need companion biomarkers. [32][33][34][35][36][37] Moreover, exercise mimetics such as trimetazidine are of interest in the therapy of muscle atrophy, 38 but also need companion biomarkers.…”

Section: Introductionmentioning

confidence: 99%