1. Prediction at First Year of Incident New-Onset Diabetes After Kidney Transplantation by Risk Prediction Models
- Author
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Carlos Gómez-Alamillo, Lidia Santos, Natalia Allende, Celestino Piñera, Juan Carlos Ruiz San Millán, Emilio Rodrigo, Manuel Arias, Carmen Toyos, and Maria Estrella Quintela
- Subjects
Advanced and Specialized Nursing ,Research design ,medicine.medical_specialty ,Percentile ,Framingham Risk Score ,Receiver operating characteristic ,business.industry ,Endocrinology, Diabetes and Metabolism ,Hazard ratio ,Clinical Care/Education/Nutrition/Psychosocial Research ,medicine.disease ,Kidney Transplantation ,Transplantation ,Risk Factors ,Diabetes mellitus ,Internal medicine ,Diabetes Mellitus ,Internal Medicine ,medicine ,Humans ,Intensive care medicine ,business ,Kidney transplantation ,Original Research - Abstract
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.
- Published
- 2012