Type 2 diabetes prediction method and system based on human body composition

A technology of type 2 diabetes and body composition, applied in the field of diabetes prediction, can solve the problem of reducing the willingness of patients, and achieve the effect of strong implementation, low cost and easy operation.

Pending Publication Date: 2021-11-12
SHANGHAI SIXTH PEOPLES HOSPITAL
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Problems solved by technology

However, due to differences in race, demographics, and living habits, these models may not be suitable for other populations
Most of the models currently studied are based on demographic indicators (age, gender, family history of diabetes, etc.), lifestyle (smoking, drinking, eating habits, etc.), anthropometric measurements (height, weight, waist circumference, waist-to-hip ratio, systolic blood pressure, Diastolic blood pressure, etc.), clinical test indicators (triglyceride, cholesterol, high-density cholesterol, low-density cholesterol, fasting blood, etc.), most models include clinical test indicators, which may reduce the patient’s voluntary sex

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  • Type 2 diabetes prediction method and system based on human body composition
  • Type 2 diabetes prediction method and system based on human body composition
  • Type 2 diabetes prediction method and system based on human body composition

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[0039]In this example, the area of ​​visceral fat was obtained using a body composition instrument (Indody720 model). The research population was selected from people aged 18-70 years old, without diabetes and who cooperated with the completion of the questionnaire. It was necessary to exclude malignant tumors and abnormal thyroid function. , postoperative gastrointestinal diseases, pregnant women, breastfeeding mothers, and secondary diabetes, and follow up blood glucose for 3 years for these groups, and eliminate lost or incomplete data information during data sorting to obtain the final data for analysis .

[0040] After the preliminary analysis and comparison of the research population according to step S1 and step S2, the variables were screened according to the requirements of the P value in step S3, and the results obtained are shown in Table 1:

[0041] Table 1

[0042]

[0043] It can be seen from Table 1 that compared with the non-type 2 diabetes group, the type ...

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Abstract

The invention discloses a type 2 diabetes prediction method and system based on the human body composition. The method comprises the following steps: acquiring basic information of a patient and related data of the human body composition; taking whether the follow-up visited patient suffers from type 2 diabetes or not as a dependent variable, taking the obtained factors as independent variables to carry out single-factor analysis, and screening factors with statistical difference according to the P value of each factor; carrying out multi-factor Logistic regression analysis on independent variables with statistical differences in a single-factor analysis result, selecting a model with the best fitting degree according to AIC values, determining a regression coefficient which is finally incorporated into the independent variables, and representing the regression coefficient by adopting a Nomogram column graph; and predicting the onset risk of the type 2 diabetes of the patient according to the predicted cut-off value of the column graph.

Description

technical field [0001] The invention relates to the technical field of diabetes prediction, in particular to a type 2 diabetes prediction method and system based on body composition. Background technique [0002] Diabetes is recognized as a major public health problem worldwide. In recent years, the incidence of type 2 diabetes has increased year by year, and the occurrence of type 2 diabetes and its complications has brought a significant economic burden to patients and is the main cause of death. [0003] Among diabetic patients, a large proportion of patients are undiagnosed (such as asymptomatic), but are still at high risk of serious complications such as cardiovascular disease, kidney damage, retinopathy, etc. Several intervention studies have found that for People at high risk of diabetes can prevent and delay the occurrence of type 2 diabetes through lifestyle improvement and drug intervention. In this context, it is particularly important to use simple and effecti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G16H50/20G06F17/18A61B5/00A61B5/107
CPCG16H50/30G16H50/20G06F17/18A61B5/4869A61B5/107
Inventor 葛声杨海燕冯晓慧孙文广马爱勤曹芸屠越华吕亭亭刘海丽华淑瑶罗泽华张丽岩
Owner SHANGHAI SIXTH PEOPLES HOSPITAL
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