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Prediction model for diabetic mild cognitive impairment and nomogram construction method

A technology for cognitive dysfunction and prediction model, applied in computational models, medical simulations, medical images, etc., can solve the problems of different judgment standards, time-consuming, low sensitivity and other problems of testers, so as to avoid cognitive decline in diabetes, The effect of improving the accuracy and improving the detection rate

Pending Publication Date: 2022-04-15
NANJING DRUM TOWER HOSPITAL
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, it has the limitations of long time-consuming, low sensitivity to subclinical cognitive changes, and different judgment criteria for testers.

Method used

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  • Prediction model for diabetic mild cognitive impairment and nomogram construction method
  • Prediction model for diabetic mild cognitive impairment and nomogram construction method
  • Prediction model for diabetic mild cognitive impairment and nomogram construction method

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Embodiment 1

[0032] see Figure 1 to Figure 7 , the present embodiment provides a method for constructing a prediction model and a nomogram for mild cognitive impairment in diabetes, comprising the following steps:

[0033] Step S1: Collect demographic information, clinical laboratory examination and medical history information of diabetic patients, improve overall cognitive function assessment and olfactory function test;

[0034] Step S2: Collect the patient's daily life information through the intelligent monitoring device, and send the collected daily life information to the server, and the server saves the user's daily life information in the user's daily data record table;

[0035] Step S3: Confirm the risk factors of cognitive dysfunction in diabetes by using multi-factor regression model;

[0036] Step S4: Using the demographic information of all diabetic patients, clinical laboratory examination and medical history information, combined with the olfactory function test, and using...

Embodiment 2

[0080] Embodiment two, on the basis of embodiment one:

[0081] It also includes step S5: using the regression model in the field of machine learning algorithms, bringing the demographic information, daily life information, clinical laboratory examination and medical history information of diabetic patients into the regression model for information data training to obtain a physiological age prediction model. The regression models in the field of machine learning here may include: Catboost Regressor, GradientBoosting Regressor, Random Forest, and Ridge Regression.

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Abstract

The invention discloses a prediction model for diabetic mild cognitive impairment and a nomogram construction method, and relates to the technical field of prediction model construction and application, and the method comprises the following steps: collecting demographic information, clinical laboratory examination and medical history information of diabetic patients, and completing overall cognitive function evaluation and olfactory function test; determining risk factors of cognitive impairment of diabetes by adopting a multi-factor regression model method; according to the method, an olfactory function test is combined, a machine learning algorithm is applied, a prediction model and a nomogram for mild cognitive impairment of type 2 diabetes mellitus are established, and primary screening and risk layering of cognitive complications in diabetic patients are realized; the comprehensive evaluation of the olfactory function, the cognitive function, the brain structure function and the like of a high-risk patient suffering from mild cognitive impairment can be further improved for clear diagnosis, and screening and definite diagnosis of cognitive complications of diabetes mellitus in relatively large sample crowds are facilitated.

Description

technical field [0001] The invention relates to the technical field of prediction model construction and application, in particular to a method for constructing a prediction model and a nomogram for mild cognitive impairment in diabetes. Background technique [0002] Diabetic cognitive impairment is a complication of the central nervous system of diabetes. According to the development of the disease, it includes subclinical stage, mild cognitive impairment and dementia. The onset of cognitive impairment is hidden and there is no effective treatment drug. The key to the rate of dementia in old age, but because it is a research difficulty in cross-fields, there is a lack of early identification technology for diabetic cognitive impairment, especially mild cognitive impairment. Cognitive function in general and in each cognitive domain, screening method for MCI. However, it has the limitations of long time-consuming, low sensitivity to subclinical cognitive changes, and differ...

Claims

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Application Information

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IPC IPC(8): G16H50/50G16H50/70G16H50/80G16H10/60G16H50/30G16H30/00G06N20/00
Inventor 毕艳张洲
Owner NANJING DRUM TOWER HOSPITAL
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