Sarcopenia is associated with survival in patients awaiting kidney transplant.

BACKGROUND

The relationship of sarcopenia to frailty and other survival determinants in patients waitlisted for kidney transplant is not well characterized. Our goal was to evaluate the relationship of muscle area to functional and frailty metrics and its impact on survival in patients waitlisted for kidney transplant.

METHODS

Among 303 consecutively listed transplant candidates, 172 had a computed scan within 3 months of frailty and biochemical testing that permitted muscle area evaluation. Third lumbar level psoas muscle indices (total bilateral psoas area/height) were calculated. Testing included frailty metrics, treadmill and pedometer ability, troponin, and brain natriuretic peptide levels. Associations between muscle area, demographic, biochemical, and frailty measures were analyzed. Log-rank test was used to evaluate waitlist survival on the basis of muscle area, and multivariate Cox proportional hazards modeling was used to evaluate factors independently associated with survival.

RESULTS

Demographic factors associated with third lumbar level psoas muscle indices include male sex (P < .001), race (P = .02), age (P = .004), and body mass index (P < .0001). Grip strength, treadmill ability, and Sit-Stands positively correlated with third lumbar level psoas muscle indices (P < .01). Brain natriuretic peptide and Up and Go negatively correlated with third lumbar level psoas muscle indices (P < .01). Survival was significantly associated with third lumbar level psoas muscle indices (P = 0.02). Treadmill ability, Sit-Stands, Up and Go, race and muscle area were most closely associated with waitlist survival on multivariate modeling.

CONCLUSION

Sarcopenia as assessed with muscle area measurements is independently associated with kidney waitlist survival. Functional ability and muscle area may be overlapping, but noncongruent, determinants of waitlist outcomes and may need to be individually assessed to create the most predictive survival model.