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Prediction at First Year of Incident New-Onset Diabetes After Kidney Transplantation by Risk Prediction Models
OBJECTIVE: 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. RESEAR...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Diabetes Association
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3322708/ https://www.ncbi.nlm.nih.gov/pubmed/22279030 http://dx.doi.org/10.2337/dc11-2071 |
Sumario: | OBJECTIVE: 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. RESEARCH DESIGN AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. |
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