High cholesterol predicts lower mortality in dialysis patients but is not protective

Kidney dialysis patients with higher cholesterol levels die at a lower rate than those with lower cholesterol levels, which is opposite of the general public. However, a study by researchers at the John Hopkins Bloomberg School of Public Health determined that the lower mortality rate of those with higher cholesterol is likely due to the cholesterol-lowering effects of inflammation and malnutrition, two serious complications of kidney dialysis, and not a benefit of high cholesterol. The study is published in the January 28, 2004, edition of the Journal of the American Medical Association (JAMA).

"Using multiple blood tests we were able to show that the majority of dialysis patients have inflammation and/or malnutrition and these conditions distort the meaning of serum cholesterol. This explains why patients with lower cholesterol have higher mortality," said Josef Coresh, MD, PhD, the study's senior investigator and an associate professor in the Department of Epidemiology at the School of Public Health. "We were able to show that when dialysis patients don't have inflammation or malnutrition, higher cholesterol predicted a progressively higher risk of total and cardiovascular mortality. This is important since it undermines the idea that high cholesterol can be protective in dialysis patients and emphasizes the importance of cholesterol treatment," explained Dr. Coresh.

The study included 823 dialysis patients from 79 clinics in the United States. Inflammation and/or malnutrition were detected by looking for abnormalities in any one of three laboratory tests (C-reactive protein, interleukin-6 or serum albumin) since any one test can miss patients with abnormalities. Participants with inflammation or malnutrition had lower cholesterol levels than those without either condition. Overall, higher cholesterol was incrementally associated with lower mortality, a finding which confirms other studies in dialysis patients and other sick populations such as sm

Contact: Tim Parsons or Kenna Brigham
Johns Hopkins University Bloomberg School of Public Health

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