Introduction: Cardiovascular disease is an important cause of morbidity and mortality in individuals with type 1 diabetes (T1D). The American Diabetes Association (ADA) has the ADA risk-assessment tool for cardiovascular risk (CVR) prediction in individuals with T1D. This study aims to evaluate the prevalence of novel and traditional cardiovascular risk factors (CVRF) and the CVR by the ADA risk-assessment tool: 10-year risk for diabetes complications in young adults with T1D.
Methods: Cross-sectional observational study of T1D individuals aged 18-40 years and T1D duration ≥1 year. The ADA risk-assessment tool was applied to predict CVR.
Results: 75 individuals, 61.3% male, with a median age of 30 (26.0-36.0) and 13.0 (6.0-20.0) years of T1D duration. Hypertension was found in 16% of individuals and dyslipidemia in 75.0%. 21.3% were active smokers, 30.7% sedentary, and 42.7% were at least overweight. Most individuals had a 10-year risk <1% for all complications except myocardial infarction (MI). In individuals who were outside the honeymoon period (T1D duration ≥ 5 years), most had a 10-year risk <1% for all complications except MI and amputation. Non-traditional CVRF homocysteine, apolipoprotein B, apolipoprotein B/apolipoprotein A1 ratio, magnesium, and vitamin D correlated with the ADA risk-assessment tool. 10-year risk for MI ≥1% was significantly more frequent in men.
Conclusion: To our knowledge, this is the first study to apply the ADA risk-assessment tool: 10-year risk for diabetes complications in T1D. Young adults with T1D have a worrying prevalence of CVRF and show suboptimal control. Most individuals with T1D duration ≥1 year have an estimated 10-year risk <1% for all complications, except for MI.
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http://dx.doi.org/10.7759/cureus.22574 | DOI Listing |
Eat Weight Disord
January 2025
Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
BMC Geriatr
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Department of Cardiology, The Second Hospital & Clinical Medical School, Lanzhou University, No. 82 Cuiyingmen, Lanzhou, 730000, China.
Objective: Constructing a predictive model for the occurrence of heart disease in elderly hypertensive individuals, aiming to provide early risk identification.
Methods: A total of 934 participants aged 60 and above from the China Health and Retirement Longitudinal Study with a 7-year follow-up (2011-2018) were included. Machine learning methods (logistic regression, XGBoost, DNN) were employed to build a model predicting heart disease risk in hypertensive patients.
J Hum Hypertens
January 2025
Department of Pediatrics and Child Health, University of Ilorin, Ilorin, Nigeria.
Sci Rep
January 2025
Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Sci Rep
January 2025
Department of Cardiology, Taian 88 Hospital, China RongTong Medical Healthcare Group Co.Ltd, Taian, 271000, China.
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