Screening for Age-Related Skeletal Muscle Dysfunction



Status:Active, not recruiting
Conditions:Orthopedic
Therapuetic Areas:Orthopedics / Podiatry
Healthy:No
Age Range:45 - 85
Updated:9/22/2018
Start Date:October 2014
End Date:November 2019

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Creating a Model of Proactive Geriatric Care Within VISN 5: Screening for Age-Related Skeletal Muscle Dysfunction at the Washington DC VA Medical Center

This pilot study will aid the development of a sonographic screening method used to obtain
proxy measures of LBM and estimates of muscle composition that relate to Intramuscular
adipose tissue (IMAT), lipid metabolism, and insulin resistance. Typically, age-related
muscle loss is not assessed in older adults until they began to show signs of trouble
managing their own lives independently. In addition to the loss of independence that is
typically seen with diminished muscle mass and function (sarcopenia), age-related changes in
lean body mass can have negative effects on insulin sensitivity. The investigators central
hypothesis is that the muscle characteristics derived from ultrasound (US) will be
significantly associated with estimates of dual energy X-ray absorptiometry (DXA) LBM, CT
scan measures of IMAT, estimates of insulin homeostasis, and serum levels of inflammatory
cytokines.

The primary goals of this project are to: 1) develop and validate a rapid, portable,
cost-effective, screening method for sarcopenia using diagnostic ultrasound (US), and 2)
determine if the US screening method provides viable estimates of intramuscular adipose
tissue (IMAT) since muscle tissue age-related changes in muscle composition are associated
with low muscle torque and metabolic dysfunction. The proposed US screening method may be
used as a proxy measure of LBM and provide estimates of skeletal muscle composition that
relate to IMAT, lipid metabolism, insulin homeostasis and inflammation - important factors
that may impact impaired mobility and metabolic dysfunction in older African American
Veterans.

Aim 1:

Determine the association between a proxy measure of LBM obtained via portable, diagnostic,
musculoskeletal US and LBM as determined by dual energy X-ray absorptiometry (DXA).

The working hypothesis is that a 6-muscle model of LBM derived from US and DXA LBM values
will exhibit a significant positive association and attain a coefficient of determination >
.80.

Aim 2:

Determine the association between US echointensity features and IMAT as determined by CT
scan.

US echointensity values will be acquired from the rectus femoris and analyzed to determine
the association with IMAT. The working hypothesis is that higher echointensity values
measured with grayscale analysis will be negatively associated with the Hounsfield units
obtained from the CT scan (p < .05).

Aim 3:

Examine the association between US echointensity values and biologic factors that impair
insulin sensitivity.

Excessive IMAT and intra-myocellular triglyceride levels result in increased levels of
biologic factors such as inflammatory cytokines (TNF-α and IL-6), which may affect insulin
sensitivity. The investigators hypothesis is that proxy measures of IMAT via echointensity
values will be positively associated with biomarkers of inflammation and insulin homeostasis.

Inclusion Criteria: You are eligible to participate if:

1. You are registered to receive healthcare at the Washington DC VAMC through the
Geriatrics Extended Care Service and/or Primary Care Service.

2. You are a male.

3. You are between the ages of 45 - 85 years.

4. Must be able to stand comfortably for 10 minutes and walk a short distance (use of
assistive devices are acceptable).

Exclusion Criteria: You are not eligible to participate if:

1. You have uncontrolled hypertension.

2. Body Mass Index (BMI) <18.5 or >32.5.

3. Musculoskeletal conditions that would stop you from performing the physical assessment
test.

4. Muscle weakness due to neurological disease or injury (such as stroke or spinal cord
injury).

5. Moderate to severe sepsis (blood infection) or edema (such as swelling of a limb).

6. Currently prescribed medications that affect glucose or insulin.

7. Uncontrolled cardiovascular disease.

8. Hospitalization over the last three months.

9. Diagnosis of diabetes.
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