Method, device, medium and program product for predicting osteoporosis risk of postmenopausal diabetic population

By obtaining specific predictors of postmenopausal type 2 diabetes patients and constructing a multi-factor regression model, the lag problem of traditional evaluation methods is solved, and accurate prediction and early intervention of the risk of osteoporosis in postmenopausal type 2 diabetes patients are achieved.

CN120388741APending Publication Date: 2025-07-29SHANDONG PROVINCE SECOND INCLUSIVE ARMY HOSPITAL
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Patent Information

Application Number
CN202510591245.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-08
Publication Date
2025-07-29

AI Technical Summary

Technical Problem

The prior art has lag in evaluating the risk of osteoporosis in postmenopausal type 2 diabetes patients. Traditional methods are difficult to accurately predict the risk of fracture and cannot meet the needs of early diagnosis and prevention.

Method used

A prediction method specifically targets patients with type 2 diabetes after menopause was adopted. By obtaining age, menopause age, diabetes course, PINP, CTX and FF scores, a multi-factor regression model was used to construct an osteoporosis risk prediction model and output risk probability.

Benefits of technology

It improves the accuracy of predicting the risk of osteoporosis in postmenopausal type 2 diabetes, provides the possibility of early intervention and preventing fractures, and improves the quality of life of patients.

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Abstract

The invention provides a method, equipment, medium and program product for predicting the osteoporosis risk of postmenopausal diabetes people, and relates to the field of intelligent medical treatment. The method comprises the following steps: acquiring one or more predictive factors of an age, a menopausal age, a diabetes disease course, PINP, CTX and an FF score of a subject; the subject is a postmenopausal diabetes patient; calculating a risk score based on the predictive factor, and outputting an auxiliary predictive result of the risk probability of osteoporosis of the subject according to the risk score; when the risk score is greater than a first threshold value, outputting an auxiliary prediction result that the probability of occurrence of osteoporosis risk of the subject is large; and when the risk score is smaller than a first threshold value, outputting an auxiliary prediction result with a small probability of occurrence of osteoporosis risk of the subject. The osteoporosis risk of postmenopausal diabetes people is predicted specifically aiming at the postmenopausal diabetes people.
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