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Mean Corpuscular Volume and Mortality in Incident Hemodialysis Patients

Published Web Location

https://doi.org/10.1159/000495726Creative Commons 'BY' version 4.0 license
Abstract

Background/aims

Anemia is common in patients with advanced chronic kidney disease (CKD). A proportion of patients present with macrocytic anemia, manifested by elevated mean corpuscular volume (MCV), which has been associated with worse outcomes in CKD patients. However, it is unknown whether elevated MCV is associated with higher mortality risk in incident hemodialysis (HD) patients.

Methods

This retrospective observational cohort study examined all-cause, cardiovascular, and infectious mortality associations with both baseline and time-varying MCV in 109,501 incident HD patients using Cox proportional hazards models with 3 levels of hierarchical multivariable adjustment. Odds ratios of high versus low baseline MCV were evaluated using logistic regression.

Results

The mean age of patients was 65 ± 15 (standard deviation) years and the cohort was 44% female, 58% diabetic, and 31% African American. Higher MCV was associated with older age, female sex, non-Hispanic White race-ethnicity, alcohol consumption, and having a decreased albumin or protein intake. Patients with higher MCV levels (> 98 fL) had a higher all-cause, cardiovascular, and infectious mortality risk in both baseline and time varying models, and across all levels of adjustment. In the fully adjusted models, compared to a reference of MCV 92-< 94 fL, patients with a baseline MCV > 100+ fL had a 28% higher risk of all-cause mortality (hazard ratio [HR] 1.28, 95% CI 1.22-1.34), 27% higher risk of cardiovascular mortality (HR 1.27, 95% CI 1.18-1.36), and 18% higher risk of infectious mortality (HR 1.18, 95% CI 1.02-1.38). Associations of higher MCV with these adverse outcomes persisted across all examined subgroups of clinical characteristics.

Conclusions

Higher MCV was associated with higher all-cause, cardiovascular, and infectious mortality in HD patients. Further investigation is necessary to understand the underlying nature of the observed association.

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