A high red blood cell distribution width predicts failure of arteriovenous fistula

VASCULAR PHARMACOLOGY(2012)

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摘要
In hemodialysis patients, a native arteriovenous fistula (AVF) is the preferred form of permanent vascular access. Despite recent improvements, vascular access dysfunction remains an important cause of morbidity in these patients. In this prospective observational cohort study, we evaluated potential risk factors for native AVF dysfunction. We included 68 patients with chronic renal disease stage 5 eligible for AVF construction at the Department of General and Vascular Surgery, Central Clinical Hospital Ministry of Internal Affairs, Warsaw, Poland. Patient characteristics and biochemical parameters associated with increased risk for AVF failure were identified using Cox proportional hazards models. Vessel biopsies were analyzed for inflammatory cells and potential associations with biochemical parameters. In multivariable analysis, independent predictors of AVF dysfunction were the number of white blood cells (hazard ratio [HR] 1.67; 95% confidence interval [CI] 1.24 to 2.25; p<0.001), monocyte number (HR 0.02; 95% CI 0.00 to 0.21; p = 0.001), and red blood cell distribution width (RDW) (HR 1.44; 95% CI 1.17 to 1.78; p<0.001). RDW was the only significant factor in receiver operating characteristic curve analysis (area under the curve 0.644; CI 0.51 to 0.76; p = 0.046). RDW>16.2% was associated with a significantly reduced AVF patency frequency 24 months after surgery. Immunohistochemical analysis revealed CD45-positive cells in the artery/vein of 39% of patients and CD68-positive cells in 37%. Patients with CD68-positive cells in the vessels had significantly higher white blood cell count. We conclude that RDW, a readily available laboratory value, is a novel prognostic marker for AVF failure. Further studies are warranted to establish the mechanistic link between high RDW and AVF failure.
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关键词
chemistry,physics,cox proportional hazards model,biology,cohort studies,hazard ratio,medicine,confidence interval,multivariate analysis,prospective studies,risk factors,cohort study,engineering
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