Prediction at First Year of Incident New-Onset Diabetes After Kidney Transplantation by Risk Prediction Models

نویسندگان

  • Emilio Rodrigo
  • Lidia Santos
  • Celestino Piñera
  • Juan Carlos Ruiz San Millán
  • Maria Estrella Quintela
  • Carmen Toyos
  • Natalia Allende
  • Carlos Gómez-Alamillo
  • Manuel Arias
چکیده

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.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Assessment of Risk Factors for Hospital Readmission after Kidney Transplantation

Background and Purpose: Hospital readmission after kidney transplantation is a real challenge for both patients and healthcare systems. Assessment of the risk factors of readmission after kidney transplantation is vital and can reduce morbidity and cost in transplant recipients and donors. The aim of the current study was to determine the risk factors of hospital readmission in patients undergo...

متن کامل

Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

متن کامل

Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

متن کامل

Validation of a Pretransplant Risk Score for New-Onset Diabetes After Kidney Transplantation

OBJECTIVE Identification of patients at high risk for new-onset diabetes after kidney transplantation (NODAT) will facilitate clinical trials for its prevention. RESEARCH DESIGN AND METHODS We previously described a pretransplant predictive risk model for NODAT using seven pretransplant variables (age, planned use of maintenance corticosteroids, prescription for gout medicine, BMI, fasting gl...

متن کامل

پیش‌بینی بقای پنج ساله پیوند کلیه با استفاده از مدل شبکه عصبی مصنوعی: گزارش 22 سال پی‌گیری از 316 بیمار در اصفهان

Background: Kidney transplantation had been evaluated in some researches in Iran mainly with clinical approach. In this research we evaluated graft survival in kidney recipients and factors impacting on survival rate. Artificial neural networks have a good ability in modeling complex relationships, so we used this ability to demonstrate a model for prediction of 5yr graft survival after ki...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 35  شماره 

صفحات  -

تاریخ انتشار 2012