A Model for Risk Prediction of Fracture in Diabetic Patients With Osteoporosis
- Conditions
- Healthcare; Risk Prediction; Diabetic Patients With Osteoporosis
- Registration Number
- NCT04534166
- Brief Summary
The fracture risk of diabetic patients proves to be higher than those without diabetesdue to thehyperglycemia, usage of diabetes drugs, the changes in insulin levels and excretion, and this risk begins as early as adolescence.Many factors may be related to bone metabolism in patients with diabetes, including demographic data (e.g. age, height, weight, gender), medical history (e.g. smoking, drinking, menopause) and examination (e.g. bone mineral density, blood routine), urine routine).However, most of existing methods are qualitative assessments and do not take the interactions of the physiological factors of humans into consideration. In addition, the fracture risk of diabetic patients with osteoporosis has not been further studied before. In order to investigate the effect of patients' physiological factors on fracture risk, in the paper, we used a hybrid model combining XGBoost with deep neural network to predict the fracture risk of diabetic patients with osteoporosis.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- Not specified
- Patients in Hospital's outpatient and inpatient His database between July 2012 and November 2022, diabetic patients were combined with osteoporosis.
- Patients with fractures before diagnosis of diabetes; patients with fractures before diagnosis of osteoporosis; patients with hyroid disease and other diseases that seriously affect bone metabolism.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Fracture 2-10 year
- Secondary Outcome Measures
Name Time Method