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Abstract: TH-PO608

Skeletal Muscle Index from CT Scans Can Predict Muscle Strength in CKD

Session Information

Category: Health Maintenance, Nutrition, and Metabolism

  • 1300 Health Maintenance, Nutrition, and Metabolism

Authors

  • Lampe, Samuel L., Indiana University Internal Medicine, Indianapolis, Indiana, United States
  • Cranor, Alissa Ann, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Swinney, Kimberly, Indiana University, Indianapolis, Indiana, United States
  • Imel, Erik, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Avin, Keith G., Indiana University, Indianapolis, Indiana, United States
  • Moe, Sharon M., Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Moorthi, Ranjani N., Indiana University School of Medicine, Indianapolis, Indiana, United States
Background

Sarcopenia is associated with poor clinical outcomes in chronic kidney disease, but is often under-recognized during clinical encounters. Muscle mass and intramuscular fat are measures of muscle quantity and quality but requires DXA and extremity MRIs or CTs. We hypothesize that muscle quantity and intramuscular adiposity, measured on abdominal CT scans done for clinical care, can be used to predict grip strength in patients with CKD stage 5-5D and in healthy patients.

Methods

We studied 19 patients with CKD stages 5-5D and 12 healthy individuals who had measures of grip strength. Records were reviewed for abdominal CT scans performed as part of their clinical care. The regions of interest were muscles at the level of the L3: psoas, erector spinae, quadratus lumborum, transversus abdominus, external and internal obliques and rectus abdominus. Skeletal muscle index (SKMI) and intra-muscular adipose tissue index (IMATI) were calculated as cross-sectional areas, corrected for height (cm2/m2) using Hounsfield unit ranges (skeletal muscle: -29 to 150 and adipose tissue: -190 to -30). We used linear regression to determine the independent relationship between SKMI and IMATI respectively with grip strength in univariate analyses and adjusted for covariates.

Results

Mean age was 48.5+/-12.5 y, BMI was 29.2+/-8.1kg/m2, 55% white and 52% were male. Mean SKMI was 48.9+/-9.1 cm2/m2 and was not significantly different between those with CKD and without CKD. On univariate analysis, age, presence of CKD, sex and SKMI were significantly associated with grip strength (all p<0.05). Using multivariate linear regression SKMI, adjusted for sex and presence of CKD was associated to be a significant predictor of grip strength (p=0.014), with the model containing these 3 variables explaining 68% of the variability in grip strength. IMATI was not a signficant predictor of grip strength in univariate or multivariate models.

Conclusion

Incidental CT scans can be used to assess skeletal muscle cross-sectional area which is a useful predictor of hand grip strength. Poor handgrip strength or weakness is a criteria for detecting sarcopenia in clinical practice and is associated with disability and frailty. Identifying those with probable sarcopenia during routine care provides an opportunity to attempt to intervene to regress or prevent worsening of sarcopenia.

Funding

  • NIDDK Support