期刊：
Frontiers in Public Health,2023年11:1293134 ISSN：2296-2565
通讯作者：
Song, Zhenyan;Cheng, SW
作者机构：
[Song, Zhenyan; Guo, Minhua; Cheng, Shaowu; Song, ZY; He, Jiawei; Cheng, SW; Wang, Shiwei] Hunan Univ Chinese Med, Sch Integrated Chinese & Western Med, Changsha, Peoples R China.;[Song, Zhenyan; Guo, Minhua; Cheng, Shaowu; Song, ZY; He, Jiawei; Cheng, SW; Wang, Shiwei] Hunan Univ Chinese Med, Coll Integrated Tradit Chinese & Western Med, Key Lab Hunan Prov Integrated Tradit Chinese & Wes, Changsha 410128, Peoples R China.;[Wang, Weijie] Hunan Univ Chinese Med, Sch Informat, Changsha, Peoples R China.
通讯机构：
[Song, ZY; Cheng, SW ] H;Hunan Univ Chinese Med, Sch Integrated Chinese & Western Med, Changsha, Peoples R China.;Hunan Univ Chinese Med, Coll Integrated Tradit Chinese & Western Med, Key Lab Hunan Prov Integrated Tradit Chinese & Wes, Changsha 410128, Peoples R China.
关键词：
Barthel Index (BI);activities of daily living;machine learning algorithm;memory-related diseases;the China health and retirement longitudinal survey
摘要：
INTRODUCTION: Memory-related diseases (MDs) pose a significant healthcare challenge globally, and early detection is essential for effective intervention. This study investigates the potential of Activities of Daily Living (ADL) as a clinical diagnostic indicator for MDs. Utilizing data from the 2018 national baseline survey of the China Health and Retirement Longitudinal Study (CHARLS), encompassing 10,062 Chinese individuals aged 45 or older, we assessed ADL using the Barthel Index (BI) and correlated it with the presence of MDs. Statistical analysis, supplemented by machine learning algorithms (Support Vector Machine, Decision Tree, and Logistic Regression), was employed to elucidate the relationship between ADL and MDs. BACKGROUND: MDs represent a significant public health concern, necessitating early detection and intervention to mitigate their impact on individuals and society. Identifying reliable clinical diagnostic signs for MDs is imperative. ADL have garnered attention as a potential marker. This study aims to rigorously analyze clinical data and validate machine learning algorithms to ascertain if ADL can serve as an indicator of MDs. METHODS: Data from the 2018 national baseline survey of the China Health and Retirement Longitudinal Study (CHARLS) were employed, encompassing responses from 10,062 Chinese individuals aged 45 or older. ADL was assessed using the BI, while the presence of MDs was determined through health report questions. Statistical analysis was executed using SPSS 25.0, and machine learning algorithms, including Support Vector Machine (SVM), Decision Tree Learning (DT), and Logistic Regression (LR), were implemented using Python 3.10.2. RESULTS: Population characteristics analysis revealed that the average BI score for individuals with MDs was 70.88, significantly lower than the average score of 87.77 in the control group. Pearson's correlation analysis demonstrated a robust negative association (r = -0.188, p < 0.001) between ADL and MDs. After adjusting for covariates such as gender, age, smoking status, drinking status, hypertension, diabetes, and dyslipidemia, the negative relationship between ADL and MDs remained statistically significant (B = -0.002, β = -0.142, t = -14.393, 95% CI = -0.002, -0.001, p = 0.000). The application of machine learning models further confirmed the predictive accuracy of ADL for MDs, with area under the curve (AUC) values as follows: SVM-AUC = 0.69, DT-AUC = 0.715, LR-AUC = 0.7. Comparative analysis of machine learning outcomes with and without the BI underscored the BI's role in enhancing predictive abilities, with the DT model demonstrating superior performance. CONCLUSION: This study establishes a robust negative correlation between ADL and MDs through comprehensive statistical analysis and machine learning algorithms. The results validate ADL as a promising diagnostic indicator for MDs, with enhanced predictive accuracy when coupled with the Barthel Index. Lower levels of ADL are associated with an increased likelihood of developing memory-related diseases, underscoring the clinical relevance of ADL assessment in early disease detection.
作者机构：
[Wang, Shan-Shan] Hunan Univ Chinese Med, Coll Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.;[Ge, Jin-Wen] Hunan Univ Chinese Med, Dept Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.;[Cheng, Shao-Wu] Hunan Univ Chinese Med, Dept Cytobiol & Mol Biotechnol, Changsha 410208, Hunan, Peoples R China.
会议名称：
International Conference on Biological Sciences and Technology (BST)
会议时间：
JAN 08-10, 2016
会议地点：
Guangzhou, PEOPLES R CHINA
会议主办单位：
[Wang, Shan-Shan] Hunan Univ Chinese Med, Coll Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.^[Ge, Jin-Wen] Hunan Univ Chinese Med, Dept Integrated Chinese & Western Med, Changsha 410208, Hunan, Peoples R China.^[Cheng, Shao-Wu] Hunan Univ Chinese Med, Dept Cytobiol & Mol Biotechnol, Changsha 410208, Hunan, Peoples R China.
摘要：
Coagulation factor XII (FXII) is a multidomain serine protease that is the starter of intrinsic coagulation pathway. FXII deficiency and clinical hemostasis are not associated with bleeding, so investigators have not considered FXII important in physiology for a long time. In seeking explanation for FXII-independent physiologic hemostasis, investigators found FXII is an essential constitute of contact system that mediates procoagulation and proinflammatory via the intrinsic coagulation pathway or the Kallikrein-kinin system, respectively. Date obtained in infectious inflammation have revealed FXII mediated clotting that limited bacterial or toxin spread in early phases, and regulated fibrinolysis in later. Moreover, FXII mediated two noninfectious inflammation Hereditary angioedema (HAE) and non-specific allergy via bradykinin (BK) formation. In the coagulation, thrombosis not only is involved with coagulation, but is redefined as thrombo-inflammatory disorder. This paper reviews in detail the progresses in roles of FXII intersection between inflammation and coagulation.
