Impact of Contextual Factors on the Attendance and Role in the Evidence-Based Chronic Disease Prevention Programs Among Primary Care Practitioners in Shanghai, China

Liu, Xin; Gong, Xia; Gao, Xiang; Wang, Zhaoxin; Lu, Shan; Chen, Chen; Jin, Hua; Chen, Ning; Yang, Yan; Cai, Meiyu; Shi, Jianwei

doi:10.3389/fpubh.2021.666135

Cited by 2 publications

(1 citation statement)

References 36 publications

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“…Community health workers play an important role in T2DM management. Strategies on how to further improve and strengthen the management of chronic diseases, such as T2DM, in the community, remain a current study hotspot [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Establishment and health management application of a prediction model for high-risk complication combination of type 2 diabetes mellitus based on data mining

et al. 2023

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In recent years, the prevalence of T2DM has been increasing annually, in particular, the personal and socioeconomic burden caused by multiple complications has become increasingly serious. This study aimed to screen out the high-risk complication combination of T2DM through various data mining methods, establish and evaluate a risk prediction model of the complication combination in patients with T2DM. Questionnaire surveys, physical examinations, and biochemical tests were conducted on 4,937 patients with T2DM, and 810 cases of sample data with complications were retained. The high-risk complication combination was screened by association rules based on the Apriori algorithm. Risk factors were screened using the LASSO regression model, random forest model, and support vector machine. A risk prediction model was established using logistic regression analysis, and a dynamic nomogram was constructed. Receiver operating characteristic (ROC) curves, harrell’s concordance index (C-Index), calibration curves, decision curve analysis (DCA), and internal validation were used to evaluate the differentiation, calibration, and clinical applicability of the models. This study found that patients with T2DM had a high-risk combination of lower extremity vasculopathy, diabetic foot, and diabetic retinopathy. Based on this, body mass index, diastolic blood pressure, total cholesterol, triglyceride, 2-hour postprandial blood glucose and blood urea nitrogen levels were screened and used for the modeling analysis. The area under the ROC curves of the internal and external validations were 0.768 (95% CI, 0.744−0.792) and 0.745 (95% CI, 0.669−0.820), respectively, and the C-index and AUC value were consistent. The calibration plots showed good calibration, and the risk threshold for DCA was 30–54%. In this study, we developed and evaluated a predictive model for the development of a high-risk complication combination while uncovering the pattern of complications in patients with T2DM. This model has a practical guiding effect on the health management of patients with T2DM in community settings.

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Section: Introductionmentioning

confidence: 99%

Establishment and health management application of a prediction model for high-risk complication combination of type 2 diabetes mellitus based on data mining

et al. 2023

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Influencing Factors and Symbiotic Mechanism of the Integration of Medical Care and Disease Prevention during the COVID-19 Pandemic: A Cross-Sectional Survey of Public Hospital Employees

Tian

et al. 2022

IJERPH

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Background: The COVID-19 outbreak has accelerated the huge difference between medical care and disease prevention in Chinese medical institutions. This study aimed to investigate the relationship between the symbiotic units, environments, models, and effects of the integration of medical care and disease prevention. Methods: This cross-sectional study involved 762 employees of public hospitals in 11 cities in Zhejiang Province by random stratified sampling. We analyzed the influence paths of elements in the mechanism of integration of medical care and disease prevention and the mediating effect of symbiotic models among symbiotic units, symbiotic environments, and effects on this integration. Results: The path coefficient of the symbiotic unit on the symbiosis model was 0.46 (p < 0.001), the path coefficient of the symbiotic environment on the symbiosis model was 0.52 (p < 0.001). The path coefficient of the symbiotic unit and the environment was 0.91 (p < 0.001). The symbiotic models exhibited a partial mediation effect between symbiotic units and the effect of this integration. Sobel test = 3.27, β = 0.152, and the mediating effect accounted for 34.6%. Conclusions: It is suggested that health policymakers and public hospital managers should provide sufficient symbiotic units, establish collaborative symbiotic models, and improve the effects of integration of medical care and disease prevention in public hospitals.

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Impact of Contextual Factors on the Attendance and Role in the Evidence-Based Chronic Disease Prevention Programs Among Primary Care Practitioners in Shanghai, China

Cited by 2 publications

References 36 publications

Establishment and health management application of a prediction model for high-risk complication combination of type 2 diabetes mellitus based on data mining

Establishment and health management application of a prediction model for high-risk complication combination of type 2 diabetes mellitus based on data mining

Influencing Factors and Symbiotic Mechanism of the Integration of Medical Care and Disease Prevention during the COVID-19 Pandemic: A Cross-Sectional Survey of Public Hospital Employees

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