Friday, February 14, 2014

"...1 of 4 patients admitted to the acute care department were recognized to be sarcopenic."

 2014 Feb 6. pii: S1525-8610(13)00660-9. doi: 10.1016/j.jamda.2013.11.018. [Epub ahead of print]

Identifying Sarcopenia in Acute Care Setting Patients.

Author information

  • 1Division of Geriatrics, Department of Medicine, University of Verona, Verona, Italy. Electronic address: mauro.zamboni@univr.it.
  • 2Division of Geriatrics, Department of Medicine, University of Verona, Verona, Italy.
  • 3Department of Statistics, University of Trento, Trento, Italy.

Abstract


OBJECTIVES:

To evaluate the prevalence of sarcopenia by applying European Working Group on Sarcopenia in Older People (EWGSOP) flow chart in an acute care geriatric unit as well as to test a modified version of the EWGSOP diagnostic algorithm combining handgrip and gait speed test to identify subjects with low muscle mass.

DESIGN:

Observational cohort study.
SETTING:

Geriatric unit in an academic medical department.

PARTICIPANTS:

One hundred nineteen acutely ill persons (34.4% female), with mean age 80.4 ± 6.9 years and body mass index 26.3 ± 4.9 kg/m2.

MEASUREMENTS:

Assessment of muscle mass by bioimpedence analysis, muscle strength by handheld dynamometer, and gait speed with the 4-meter walking test.

RESULTS:

Using the EWGSOP classification for sarcopenia, 5.0% presented with sarcopenia and 21.0% with severe sarcopenia. Combining gait speed test and handgrip strength measurement, the highest predictive power in detecting subjects with low muscle mass was observed (sensitivity and specificity, 80.6% and 62.5%, respectively). Subjects presenting with both normal gait speed and handgrip showed normal values of muscle mass as assessed with bioimpedence analysis. By using the ROC method, when the 2 tests were combined, the AUC was statistically higher than when using each test separately (0.740; P = .018).

CONCLUSIONS:

Our study shows that 1 of 4 patients admitted to the acute care department were recognized to be sarcopenic. When a modifived version of the EWGSOP flow chart, obtained combining both gait speed and handgrip was used, sensitivity and specificity of algorithm to identify subjects with low muscle mass was improved.

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