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Development of a cardiovascular diseases risk prediction model and tools for Chinese patients with type 2 diabetes mellitus: A population-based retrospective cohort study.
Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen.
Afiliação
  • Wan EYF; Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong.
  • Fong DYT; Department of Surgery, School of Nursing, The University of Hong Kong, Ap Lei Chau, Hong Kong.
  • Fung CSC; Department of Surgery, School of Nursing, The University of Hong Kong, Ap Lei Chau, Hong Kong.
  • Yu EYT; Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong.
  • Chin WY; Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong.
  • Chan AKC; Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong.
  • Lam CLK; Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong.
Diabetes Obes Metab ; 20(2): 309-318, 2018 02.
Article em En | MEDLINE | ID: mdl-28722290
AIMS: Evidence-based cardiovascular diseases (CVD) risk prediction models and tools specific for Chinese patients with type 2 diabetes mellitus (T2DM) are currently unavailable. This study aimed to develop and validate a CVD risk prediction model for Chinese T2DM patients. METHODS: A retrospective cohort study was conducted with 137 935 Chinese patients aged 18 to 79 years with T2DM and without prior history of CVD, who had received public primary care services between January 1, 2010 and December 31, 2010. Using the derivation cohort over a median follow-up of 5 years, the interaction effect between predictors and age were derived using Cox proportional hazards regression with a forward stepwise approach. Harrell's C statistic and calibration plot were used on the validation cohort to assess the discrimination and calibration of the models. The web calculator and chart were developed based on the developed models. RESULTS: For both genders, predictors for higher risk of CVD were older age, smoking, longer diabetes duration, usage of anti-hypertensive drug and insulin, higher body mass index, haemoglobin A1c (HbA1c), systolic and diastolic blood pressure, a total cholesterol to high-density lipoprotein-cholesterol (TC/HDL-C) ratio and urine albumin to creatinine ratio, and lower estimated glomerular filtration rate. Interaction factors with age demonstrated a greater weighting of TC/HDL-C ratio in both younger females and males, and smoking status and HbA1c in younger males. CONCLUSION: The developed models, translated into a web calculator and color-coded chart, served as evidence-based visual aids that facilitate clinicians to estimate quickly the 5-year CVD risk for Chinese T2DM patients and to guide intervention.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Cardiovasculares / Diabetes Mellitus Tipo 2 / Angiopatias Diabéticas / Cardiomiopatias Diabéticas / Modelos Cardiovasculares Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Diabetes Obes Metab Assunto da revista: ENDOCRINOLOGIA / METABOLISMO Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Hong Kong

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Cardiovasculares / Diabetes Mellitus Tipo 2 / Angiopatias Diabéticas / Cardiomiopatias Diabéticas / Modelos Cardiovasculares Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Diabetes Obes Metab Assunto da revista: ENDOCRINOLOGIA / METABOLISMO Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Hong Kong