Development of a Predictive Model for Hyperglycemia in Nondiabetic Recipients After Liver Transplantation

Posttransplant hyperglycemia has been associated with increased risks of transplant rejection, infections, length of stay, and mortality.

To establish a predictive model to identify nondiabetic recipients at risk for developing postliver transplant (LT) hyperglycemia, we performed this secondary, retrospective data analysis of a single-center, prospective, randomized, controlled trial of glycemic control among 107 adult LT recipients in the inpatient period. Hyperglycemia was defined as a posttransplant glucose level greater than 200 mg/dL after initial discharge up to 1 month following surgery. Candidate variables with P less than 0.10 in univariate analyses were used to build a multivariable logistic regression model using forward stepwise selection. The final model chosen was based on statistical significance and additive contribution to the model based on the Bayesian Information Criteria.

Forty-three (40.2%) patients had at least 1 episode of hyperglycemia after transplant after the resolution of the initial postoperative hyperglycemia. Variables selected for inclusion in the model (using model optimization strategies) included length of hospital stay (odds ratio [OR], 0.83; P < 0.001), use of glucose-lowering medications at discharge (OR, 3.76; P = 0.03), donor female sex (OR, 3.18; P = 0.02) and donor white race (OR, 3.62; P = 0.01). The model had good calibration (Hosmer-Lemeshow goodness-of-fit test statistic = 9.74, P = 0.28) and discrimination (C-statistic = 0.78; 95% confidence interval, 0.65-0.81, bias-corrected C-statistic = 0.78).

Shorter hospital stay, use of glucose-lowering medications at discharge, donor female sex and donor white race are important determinants in predicting hyperglycemia in nondiabetic recipients after hospital discharge up to 1 month after liver transplantation.