The Application Value of Internet Health Popularization for Community Patients with Hypertension.

Objective: To explore the effect of Internet health science popularization on the use of antihypertensive drugs in patients with hypertension in the community. Methods: Ninety-six community hypertensive patients treated in our hospital from May 2021 to May 2023 were selected as the subjects of the study. According to the different intervention schemes received by the patients, they were equally divided into a control group (n = 48) and a study group (n = 48). The control group was given routine intervention, while the study group was given Internet health science popularization intervention based on the control group. The blood pressure [diastolic blood pressure (DBP), systolic blood pressure (SBP)], medication compliance, self-management behavior, disease uncertainty, mastery of hypertension-related knowledge, and quality of life were compared between the two groups. Results: After the intervention, the levels of DBP and SBP and the score of disease uncertainty in the study group were lower than those in the control group (P < .05). After the intervention, the scores of medication compliance, self-management behavior, and quality of life in the study group were higher than those in the control group (P < .05). The mastery of disease knowledge in the study group was higher than that in the control group (P < .05). Conclusion: The application of Internet health science popularization to community hypertension patients can improve their medication compliance, effectively control the level of blood pressure, improve patients' mastery of hypertension-related knowledge, enhance their self-management ability, reduce disease uncertainty, and improve patients' quality of life.

Factors influencing catastrophic health expenditure of households with people with diabetes in Northwest China-an example from Gansu Province.

BACKGROUND: Diabetes is a chronic non-communicable disease that causes a substantial economic burden on diabetic suffers and their households. The aim of this study was to explore the prevalence, equity, and determinants of catastrophic health expenditure (CHE) among households with people with diabetes in Northwest China. METHODS: A total of 3,000 households were included in the 6th Health services survey in Gansu Province, China of which 270 households with people with diabetes. The equity of CHE was evaluated by concentration curve and concentration index (CI). We adopted the Pareto chart to analyze the main economic intervals of the occurrence of CHE. Finally, we combined the decision tree and logistic model and analyzed the determinants of the occurrence of CHE. RESULTS: The incidence of CHE at 15%, 25% and 40% were 75.19%, 58.89% and 35.19%, respectively. CHE tended to occur in households with a lower economic level, with the phenomenon being more pronounced at Z = 40%. The Pareto chart showed that households in the group with an annual per capita income of 0-740 USD (0-5,000 Chinese Yuan) were most likely to experience CHE. Both decision tree and logistic models suggested that economic level, comorbidities, and small household size were potential risk factors. In addition, the decision tree model also suggested the interaction between the influencing factor of health checks in the past 12 months and the number of chronic diseases. CONCLUSIONS: In summary, Households with people with diabetes were more likely to incur CHE. It is essential to focus on low- and middle-income households with people with diabetes, strengthen the management of patients with diabetes, and provide timely health interventions to reduce the occurrence of chronic comorbidity and the risk of CHE in households.

Research on Early Identification Model of Intravenous Immunoglobulin Resistant Kawasaki Disease Based on Gradient Boosting Decision Tree.

BACKGROUND: To construct a predictive model for intravenous immunoglobulin (IVIG) resistant Kawasaki disease (KD) based on the gradient boosting decision tree (GBDT), so as to early identify children with IVIG resistance and actively take additional treatment to prevent adverse events. METHODS: The case data of KD children hospitalized in the Pediatric Department of Lanzhou University Second Hospital from October 2015 to July 2020 were collected. All KD patients were divided into IVIG responsive group and IVIG resistant group. GBDT was used to explore the influencing factors of IVIG-resistant KD and to construct a prediction model. Then compared with previous models, the optimal model was selected. RESULTS: In the process of GBDT model construction, 80% of the data were used as the test set, and 20% of the data were used as the validation set. Among them, the verification set was used to adjust the hyperparameters in GDBT learning. The model performed best with a hyperparameter tree depth of 5. The area under the curve of the GBDT model constructed based on the best parameters was 0.87 (95% CI: 0.85-0.90), the sensitivity was 72.62%, the specificity was 89.04%, and the accuracy was 61.65%. The contribution degree of each feature value to the model was total bilirubin, albumin, C-reactive protein, fever time, and Na in order. CONCLUSION: The GBDT model is more suitable for the prediction of IVIG-resistant KD in this study area.

The Impact of Urbanization on the Relationship between Carbon Storage Supply and Demand in Mega-Urban Agglomerations and Response Measures: A Case of Yangtze River Delta Region, China.

Rapid urbanization in mega-urban agglomerations disturbs the balance of carbon storage supply and demand (CSD) and constrains the achievement of sustainable development goals. Here, we developed a socio-ecological system (SES) framework coupled with ecosystem services (ES) cascade and DPSIR model to systematically analyze the impacts and responses of urbanization affecting CSD. We quantified urbanization and CSD using multi-source remote sensing data, such as land use and night lighting, together with related socio-economic data, such as total energy consumption, population and GDP. We found that from 2000 to 2020, the urbanization of Yangtze River Delta region (YRD) led to a decrease of 2.75% in carbon storage supply and an increase of 226.45% in carbon storage demand. However, carbon storage supply was still larger than carbon storage demand, and the spatial mismatch of CSD is the most important problem at present. Therefore, it is necessary to explore the response measures from the comprehensive perspective of SES. We identified key ecological conservation areas using a Marxan model to protect the carbon storage capacity in ecological subsystems, and promoted a carbon compensation scheme based on both the grandfather principle and the carbon efficiency principle, reconciling the contradiction between ecological conservation and socio-economic development in the social subsystem. Finally, this study quantified the threshold of urbanization based on the carbon neutrality target at which CSD reaches an equilibrium state. This study proposed a SES framework, and a set of methodologies to quantify the relationship between urbanization and CSD, which will help mega-urban agglomerations to promote harmonious development of urbanization and ecological conservation and to achieve the carbon peak and carbon neutrality targets proposed by the Chinese government.