title: Prediabetes in patients receiving tacrolimus in the first year after kidney transplantation: a prospective and multicenter study.
abstract: BACKGROUND
  Tacrolimus-based immunosuppression, the most widely used regimen in kidney transplantation, increases the risk of new onset diabetes after transplantation (NODAT). However, the prevalence, evolution and risk factors of different prediabetic alterations: impaired fasting glucose, impaired glucose tolerance, and provisional diabetes, have not been established.
  
  
  METHODS
  In this multicenter and prospective study we evaluated 154 nondiabetic kidney transplant recipients receiving tacrolimus, mycophenolate mofetil and low dose steroids. An oral glucose tolerance test was performed 3 and 12 months after transplantation and prediabetes was defined by American Diabetes Association criteria.
  
  
  RESULTS
  Prediabetes was highly prevalent and showed little variation between 3 and 12 months (36% and 33%, respectively). Impaired glucose tolerance was the most frequent abnormality observed (23% and 25%, respectively) observed. In addition, 20% of recipients showed NODAT by 1 year. Multivariate analysis showed that age (odds ratio [OR]: 1.07, 95% confidence interval [CI]: 1.004-1.14), pretransplant body mass index (OR: 1.3, CI: 1.09-1.6) and triglyceride/high density lipoprotein-cholesterol ratio, a marker of insulin resistance, (OR: 1.4, CI: 1.05-1.9) were independent risk factors for prediabetes.
  
  
  CONCLUSIONS
  One in two recipients with tacrolimus-based immunosuppresion showed prediabetes or NODAT by 1 year posttransplantation when properly investigated. Older age and high pretransplant body mass index and triglyceride/high density lipoprotein-cholesterol ratio were risk factors for prediabetes. These findings may help applying early interventions to prevent the disorder.
authors.affiliation: Hospital Universitario de Canarias, La Laguna, Spain.
authors.forename: Esteban
authors.initials: E
authors.lastname: Porrini
authors.forename: Jose Manuel
authors.initials: JM
authors.lastname: Moreno
authors.forename: Antonio
authors.initials: A
authors.lastname: Osuna
authors.forename: Rocio
authors.initials: R
authors.lastname: Benitez
authors.forename: Ildefonso
authors.initials: I
authors.lastname: Lampreabe
authors.forename: Juan Manuel
authors.initials: JM
authors.lastname: Diaz
authors.forename: Irene
authors.initials: I
authors.lastname: Silva
authors.forename: Rosa
authors.initials: R
authors.lastname: Domínguez
authors.forename: Julio
authors.initials: J
authors.lastname: Gonzalez-Cotorruelo
authors.forename: Beatriz
authors.initials: B
authors.lastname: Bayes
authors.forename: Ricardo
authors.initials: R
authors.lastname: Lauzurica
authors.forename: Meritxell
authors.initials: M
authors.lastname: Ibernon
authors.forename: Francisco
authors.initials: F
authors.lastname: Moreso
authors.forename: Patricia
authors.initials: P
authors.lastname: Delgado
authors.forename: Armando
authors.initials: A
authors.lastname: Torres
mesh_terms: D000328:Adult; D000368:Aged; D015992:Body Mass Index; D008076:Cholesterol, HDL / Q000097:blood; D003920:Diabetes Mellitus / Q000139:chemically induced*; D005260:Female; D005951:Glucose Tolerance Test; D006801:Humans; D007166:Immunosuppressive Agents / Q000009:adverse effects*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012307:Risk Factors; D016559:Tacrolimus / Q000009:adverse effects*; D014280:Triglycerides / Q000097:blood
chemical_list: D008076:Cholesterol, HDL; D007166:Immunosuppressive Agents; D014280:Triglycerides; D016559:Tacrolimus