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Screening strategies and predictive diagnostic tools for the development of new-onset diabetes mellitus after transplantation: an overview

New-onset diabetes mellitus after transplantation (NODAT) is a serious and common complication following solid organ transplantation. NODAT has been reported in 2% to 53% of all solid organ transplants. Kidney transplant recipients who develop NODAT have variably been reported to be at increased ris...

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Detalles Bibliográficos
Autores principales: Pham, Phuong-Thu T, Edling, Kari L, Chakkera, Harini A, Pham, Phuong-Chi T, Pham, Phuong-Mai T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496371/
https://www.ncbi.nlm.nih.gov/pubmed/23152690
http://dx.doi.org/10.2147/DMSO.S37039
Descripción
Sumario:New-onset diabetes mellitus after transplantation (NODAT) is a serious and common complication following solid organ transplantation. NODAT has been reported in 2% to 53% of all solid organ transplants. Kidney transplant recipients who develop NODAT have variably been reported to be at increased risk of fatal and nonfatal cardiovascular events and other adverse outcomes including infection, reduced patient survival, graft rejection, and accelerated graft loss compared with those who do not develop diabetes. Limited clinical studies in liver, heart, and lung transplants similarly suggested that NODAT has an adverse impact on patient and graft outcomes. Early detection and management of NODAT must, therefore, be integrated into the treatment of transplant recipients. Studies investigating the best screening or predictive tool for identifying patients at risk for developing NODAT early after transplantation, however, are lacking. We review the clinical predictive values of fasting plasma glucose, oral glucose tolerance test, and A1C in assessing the risk for NODAT development and as a screening tool. Simple diabetes prediction models that incorporate clinical and/or metabolic risk factors (such as age, body mass index, hypertriglyceridemia, or metabolic syndrome) are also presented.