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Prediction at first year of incident new-onset diabetes after kidney transplantation by risk prediction models.

Authors :
Rodrigo E
Santos L
Piñera C
Ruiz San Millán JC
Quintela ME
Toyos C
Allende N
Gómez-Alamillo C
Arias M
Rodrigo, Emilio
Santos, Lidia
Piñera, Celestino
Millán, Juan Carlos Ruiz San
Quintela, Maria Estrella
Toyos, Carmen
Allende, Natalia
Gómez-Alamillo, Carlos
Arias, Manuel
Source :
Diabetes Care; Mar2012, Vol. 35 Issue 3, p471-473, 3p
Publication Year :
2012

Abstract

<bold>Objective: </bold>Our aim was to analyze the performance of two scores developed for predicting diabetes in nontransplant populations for identifying kidney transplant recipients with a higher new-onset diabetes mellitus after transplantation (NODAT) risk beyond the first year after transplantation.<bold>Research Design and Methods: </bold>We analyzed 191 kidney transplants, which had at least 1-year follow-up posttransplant. First-year posttransplant variables were collected to estimate the San Antonio Diabetes Prediction Model (SADPM) and Framingham Offspring Study-Diabetes Mellitus (FOS-DM) algorithm.<bold>Results: </bold>Areas under the receiver operating characteristic curve of FOS-DM and SADPM scores to predict NODAT were 0.756 and 0.807 (P < 0.001), respectively. FOS-DM and SADPM scores over 75 percentile (hazard ratio 5.074 and 8.179, respectively, P < 0.001) were associated with NODAT.<bold>Conclusions: </bold>Both scores can be used to identify kidney recipients at higher risk for NODAT beyond the first year. SADPM score detects some 25% of kidney transplant patients with an eightfold risk for NODAT. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01495992
Volume :
35
Issue :
3
Database :
Complementary Index
Journal :
Diabetes Care
Publication Type :
Academic Journal
Accession number :
104526425
Full Text :
https://doi.org/10.2337/dc11-2071