Cumulative and Incremental Value of Sarcopenia Components on Predicting Adverse Outcomes.

OBJECTIVES

To examine the incremental value of sarcopenia components, following the diagnosis algorithm of the Asian consensus, on predicting adverse outcomes.

DESIGN

A prospective cohort study.

SETTING AND PARTICIPANTS

Four thousand community-dwelling Chinese adults (2000 men) aged 65 years or older in Hong Kong (mean age = 72.5 ± 5.2).

METHODS

SARC-F was used as the initial predictor of 9 adverse outcomes. In step 2, muscle strength (ie, grip strength) and/or functions (ie, chair-stand, walking speed) were added on top of SARC-F. In step 3, height-, weight-, and body mass index-adjusted appendicular skeletal mass (ASM) measured by dual-energy x-ray absorptiometry (DXA) were added separately to all models formulated in step 2. The areas under the receiver operating characteristic curve (AUCs) were calculated for the models formulated in all steps. Each cumulative AUC would be compared with the AUC yielded in the previous step to evaluate the incremental prediction value.

RESULTS

On top of SARC-F, assessing grip strength, walking speed, or 5-time chair-stand significantly increased the AUC for most adverse outcomes. In particular, assessing both grip strength and gait speed yielded the highest AUC in most prediction models (AUC = 0.539-0.770) and significantly increased the AUC for all outcomes except for recurrent falls. With both muscle strength and function assessed, adding ASM failed to significantly increase the AUC except for 2 conditions. In the 2 conditions, however, a higher height-adjusted ASM was associated with a higher risk of having worsened physical limitations [OR 1.25, 95% confidence interval (CI) 1.12-1.40] and decline in the physical quality of life (OR 1.18, 95% CI 1.06-1.33) in women.

CONCLUSIONS AND IMPLICATIONS

Assessing muscle strength and function provides additional power to predict adverse outcomes on top of SARC-F. Further assessment of muscle mass with DXA provides no extra constructive value ito bettering the prediction regardless of the adjustment parameters. Alternative technologies to measure muscle mass might be required.