Abstract

OBJECTIVENew-onset diabetes after kidney transplantation (NODAT) has adverse clinical and economic implications. A risk score for NODAT could help identify research subjects for intervention studies.RESEARCH DESIGN AND METHODSWe conducted a single-center retrospective cohort study using pretransplant clinical and laboratory measurements to construct a risk score for NODAT. NODAT was defined by hemoglobin A1c (HbA1c) ≥6.5%, fasting serum glucose ≥126 mg/dL, or prescribed therapy for diabetes within 1 year posttransplant. Three multivariate logistic regression models were constructed: 1) standard model, with both continuous and discrete variables; 2) dichotomous model, with continuous variables dichotomized at clinically relevant cut points; and 3) summary score defined as the sum of the points accrued using the terms from the dichotomous model.RESULTSA total of 316 subjects had seven pretransplant variables with P < 0.10 in univariate logistic regression analyses (age, planned corticosteroid therapy posttransplant, prescription for gout medicine, BMI, fasting glucose and triglycerides, and family history of type 2 diabetes) that were selected for multivariate models. Areas under receiver operating curves for all three models were similar (0.72, 0.71, and 0.70). A simple risk score calculated as the sum of points from the seven variables performed as well as the other two models in identifying risk of NODAT.CONCLUSIONSA risk score computed from seven simple pretransplant variables can identify risk of NODAT.

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