Low skeletal muscle mass by computerized tomography is associated with increased mortality risk in end-stage kidney disease patients on hemodialysis View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-10-07

AUTHORS

Alice Sabatino, Giuseppe Regolisti, Giuseppe Benigno, Francesca Di Mario, Carla Maria Avesani, Enrico Fiaccadori

ABSTRACT

Background and aimsSkeletal muscle (SM) area, as measured by abdominal CT at the level of the third lumbar vertebra (L3), has been proposed as a proxy of whole body muscle mass. However, population-specific reference values are lacking. In the present study we aimed at: (1) detecting low SM area on abdominal CT images in patients on hemodialysis by applying cut-offs derived from a group of healthy subjects, and (2) estimating the independent risk of all-cause mortality associated with low SM area.MethodsWe retrospectively enrolled 212 adult patients on hemodialysis, undergoing abdominal CT scan (study group), and 87 healthy kidney donors (reference group). We obtained the gender-specific 5th percentile values of the abdominal SM area distribution from both the whole control group and the subgroup of younger (29–60 years) subjects, which we used as reference cut-offs. Then we applied those cut-offs in the study group to identify patients with low SM area. We used survival and Cox regression analysis to evaluate the risk of all-cause mortality associated with low abdominal SM area.ResultsIn the fully adjusted Cox regression analysis, the patients with low abdominal SM area had a higher risk of death than the patients with values above the reference cut-off derived in the subgroup of younger controls (adjHR = 1.79 (1.21; 2.67), P = 0.004).ConclusionsAbdominal CT imaging can be used to detect low abdominal SM area in patients on hemodialysis by applying cut-offs derived from healthy subjects sharing a similar ethnic background. Low SM area as assessed by CT is independently associated with all-cause mortality in ESKD patients on hemodialysis.Graphic abstract More... »

PAGES

1-13

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40620-021-01167-y

DOI

http://dx.doi.org/10.1007/s40620-021-01167-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1141721738

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/34622417


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