A Model for Risk Prediction of Fracture in Diabetic Patients With Osteoporosis

Shanghai Jiao Tong University

Status: Unknown

Conditions: Healthcare; Risk Prediction; Diabetic Patients With Osteoporosis

Treatments: Other: Risk Prediction of Fracture in Diabetic Patients with Osteoporosis

Study type: Observational

Funder types: Other

Identifiers

NCT04534166

XH-20-020

Details and patient eligibility

About

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.

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients in Hospital's outpatient and inpatient His database between July 2012 and November 2022, diabetic patients were combined with osteoporosis.

Exclusion criteria

• 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.