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Development and Validation of a Model for Predicting Diabetic Nephropathy in Chinese People.
Miao, Dan Dan; Pan, En Chun; Zhang, Qin; Sun, Zhong Ming; Qin, Yu; Wu, Ming.
Afiliação
  • Miao DD; Department of Chronic Disease Prevention and Control, Huai'an City Center for Disease Control and Prevention, Huai'an 223001, Jiangsu, China.
  • Pan EC; Department of Chronic Disease Prevention and Control, Huai'an City Center for Disease Control and Prevention, Huai'an 223001, Jiangsu, China.
  • Zhang Q; Department of Chronic Disease Prevention and Control, Huai'an City Center for Disease Control and Prevention, Huai'an 223001, Jiangsu, China.
  • Sun ZM; Department of Chronic Disease Prevention and Control, Huai'an City Center for Disease Control and Prevention, Huai'an 223001, Jiangsu, China.
  • Qin Y; Department of Chronic Disease Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, Jiangsu, China.
  • Wu M; Department of Chronic Disease Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, Jiangsu, China.
Biomed Environ Sci ; 30(2): 106-112, 2017 02.
Article em En | MEDLINE | ID: mdl-28292348
OBJECTIVE: To develop a risk model for predicting later development of diabetic nephropathy (DN) in Chinese people with type 2 diabetes mellitus (T2DM) and evaluate its performance with independent validation. METHODS: We used data collected from the project 'Comprehensive Research on the Prevention and Control of Diabetes', which was a community-based study conducted by the Jiangsu Center for Disease Control and Prevention in 2013. A total of 11,771 eligible participants were included in our study. The endpoint was a clear diagnosis of DN. Data was divided into two components: a training set for model development and a test set for validation. The Cox proportional hazard regression was used for survival analysis in men and women. The model's performance was evaluated by discrimination and calibration. RESULTS: The incidence (cases per 10,000 person-years) of DN was 9.95 (95% CI; 8.66-11.43) in women and 11.28 (95% CI; 9.77-13.03) in men. Factors including diagnosis age, location, body mass index, high-density-lipoprotein cholesterol, creatinine, hypertension, dyslipidemia, retinopathy, diet control, and physical activity were significant in the final model. The model showed high discrimination and good calibration. CONCLUSION: The risk model for predicting DN in people with T2DM can be used in clinical practice for improving the quality of risk management and intervention.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Nefropatias Diabéticas / Modelos Biológicos Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Nefropatias Diabéticas / Modelos Biológicos Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2017 Tipo de documento: Article