Abstract The intensification of global heat wave events is seriously affecting residents' emotional health. Based on social media big data, our research explored the spatial pattern of residents' sentiments during heat waves (SDHW). Besides, their association with urban functional areas (UFAs) was analyzed using the Apriori algorithm of association rule mining. It was found that SDHW in Beijing were characterized by obvious spatial clustering, with hot spots predominately dispersed in urban areas and far suburbs, and cold spots mainly clustered in near suburbs. As for the associations with urban function areas, green space and park areas had significant effects on the positive sentiment in the study area, while a higher percentage of industrial areas had a greater impact on negative SDHW. When it comes to combined UFAs, our results revealed that the green space and park area combined with other functional areas was more closely related to positive SDHW, indicating the significance of promoting positive sentiment. Subdistricts with a lower percentage of residential and traffic areas may have a more negative sentiment. There were two main combined UFAs that have greater impacts on SDHW: the combination of residential and industrial areas, and the combination of residential and public areas. This study contributes to the understanding of improving community planning and governance when heat waves increase, building healthy cities, and enhancing urban emergency management.
Urban consumption spatial structure has a direct impact on the sustainable development and quality of life of urban residents. This study investigates the impact of COVID-19 on Beijing’s urban consumption spatial structure within the Sixth Ring Road. Utilizing POI (Point of Interest) data and the Kernel Density method, the spatial distribution of commercial centers is analyzed. Consumption data from China UnionPay for 2019 and 2020, along with the Weighted Voronoi diagram method, are employed to assess changes in the radiation range of commercial centers. The findings indicate that: (1) owing to the pandemic’s repercussions, commercial centers at different levels and locations have different changes. (2) There is an overarching decline in UnionPay consumer spending across diverse streets in Beijing. (3) Following the epidemic, large-scale consumption hubs have maintained their dominance, ensuring the overall stability of the city’s consumption spatial pattern. In conclusion, the changes in commercial centers and the significant decrease in consumer spending underscore the dynamic interplay between urban consumption and external shocks like the pandemic. These insights are crucial for urban planning strategies aiming to enhance both resilience and sustainability in the face of unforeseen challenges. The spatial restructuring of traditional commercial centers requires nuanced urban planning. Recognizing the resilience and expansion of smaller centers suggests the importance of fostering localized economic activities. Policymakers could incentivize their development to promote community engagement and economic sustainability.
Aortic valve replacement (AVR) remains the gold standard treatment for symptomatic severe aortic stenosis (AS). For the past 10 years, transcatheter aortic valve implantation (TAVI) has been applied in patients with high surgical mortality and morbidity risks. The preliminary results of our TAVI patients are presented in this study.Ten high-risk patients with severe AS, for AVR, were referred and accepted for TAVI in the 6 month period from May 2010 to October 2010. The patient age, logistic EuroSCORE, femoral arterial diameter, aorta annulus size, aorta valve area (AVA), mean aortic pressure gradient (MPG), as well as coronary angiography results were all collected. Six patients were treated via the transapical approach in March 2010, whereas the other four were treated with the transfemoral approach, according to their femoral artery diameter and arterial quality. This study focuses on the immediate, 1 month, 3 month, and 1 year results of TAVI.The average age of the 10 patients receiving TAVI was 81.5 years. The mean calculated EuroSCORE was 28.3 ± 7.9%. The mean AVA was 0.61 ± 0.19 cm(2). The MPG was 48 ± 16 mmHg. The surgical technical success achieved 100%. There was no reported moderate to severe postoperative paravalvular aortic regurgitation, permanent complete atrioventricular block, major access site complication, or embolic stroke. Chronic renal failure, which necessitated permanent hemodialysis, developed in 10% of the patients. One acute myocardial infarction and one case of pneumonia developed postoperatively. The AVA was increased by 251%, whereas the MPG was decreased by 80% at the 3 month follow-up. The 30-day mortality rate was 10%. The all-cause 1-year mortality rate was 20%.This new technique and device requires greater caution and needs more practice to accumulate sufficient experience. The studied patients were very fragile, due to old age and multiple comorbidities. Our results are similar to findings of multicenter trials. With careful patient screening and selection, TAVI can be a promising treatment for high-risk severe AS patients.
To investigate the association between β1 adrenergic receptor autoantibodies (β1-AA) and angiotensin II type-1 receptor autoantibodies (AT1-AA) and cardiac function in patients with hypertension complicated with left ventricular diastolic function limitation.A total of 120 patients with essential hypertension who were not taking drug treatment and were hospitalised in the Department of Cardiology at the authors' hospital from April 2018 to December 2018 were enrolled in this study and divided into a diastolic dysfunction group (65 cases) and a normal diastolic group (55 cases) according to their left ventricular diastolic function. The levels of cardiac parameters, β1-AA, AT1-AA, and other indicators were compared. Logistic regression analysis was used to analyse the related factors affecting left ventricular diastolic dysfunction (LVDD). The diagnostic efficacy of related factors in the diagnosis of diastolic dysfunction was evaluated.Univariate analysis demonstrated that the left ventricular posterior wall diameter (10.29 ± 1.23 vs. 9.12 ± 1.53), left ventricular systolic dysfunction (10.56 ± 1.37 vs. 9.43 ± 1.44), systolic blood pressure (152.37 ± 10.24 vs. 140.33 ± 5.99), diastolic blood pressure (95.66 ± 6.34 vs. 87.33 ± 7.28), β1-AA (33 vs. 9 cases), and AT1-AA (35 cases vs. 12 cases) were higher in the dysfunction group than in the control group (all P < 0.05). Multivariate regression analysis showed that β1-AA (odds ratio (OR) = 1.96, 95% confidence interval (CI): 1.369-4.345) and AT1-AA (OR = 2.02, 95% CI: 1.332-6.720) were independent risk factors for cardiac diastolic dysfunction (P < 0.05). Both autoimmune antibodies had a certain predictive value, and the combined prediction value of the two was the highest, with an area under the curve of 0.942 (95% CI: 0.881~0.985).The positive rate of β1-AA and AT1-AA in essential hypertension patients with LVDD was higher than that in the normal group. Both β1-AA and AT1-AA could be used as early markers of LVDD in essential hypertension patients.
What is known and objective Previous studies have shown that various aspirin combinations might be beneficial for the treatment of acute cerebral infarction (ACI). The aim of this study was to evaluate the efficacy of six aspirin combinations in the treatment of ACI using network meta-analysis (NMA). The performance of these combinations is then ranked according to results of this analysis. Methods Multiple databases were consulted to find randomized controlled trials (RCT) of six different aspirin combinations for the treatment of ACI. NMA was conducted on the data using stata (13.0) software. The odds ratio (OR) was calculated. The studies included in this paper were divided into a control group (aspirin alone) and an observation group (one of six aspirin combinations). Results A total of 103 eligible RCTs were identified. A total of 13 317 cases were included in the study, and the results showed that the six types of aspirin combinations (aspirin with atorvastatin, ozagrel sodium, low molecular weight heparin [LMWH], clopidogrel, cilostazol and ginkgo damo) were all significantly superior (P < 0.05) to aspirin alone. The combination of aspirin with LMWH had the highest probability of being the most clinically efficacious intervention, with a surface under the cumulative ranking (SUCRA) curve of 79.1. The combination of aspirin with ozagrel sodium was the worst, with a SUCRA value of 29.7. What is new and conclusion A combination of aspirin with LMWH is the best option among the six aspirin combinations considered for the treatment of ACI. The combination of aspirin with ozagrel sodium was ranked the last
BACKGROUND Acute pancreatitis (AP), as a common acute abdomen disease, has a high incidence rate worldwide and is often accompanied by severe complications. Negative emotions lead to increased secretion of stress hormones, elevated blood sugar levels, and enhanced insulin resistance, which in turn increases the risk of AP and significantly affects the patient's quality of life. Therefore, exploring the intervention effects of narrative nursing programs on the negative emotions of patients with AP is not only helpful in alleviating psychological stress and improving quality of life but also has significant implications for improving disease outcomes and prognosis. AIM To construct a narrative nursing model for negative emotions in patients with AP and verify its efficacy in application. METHODS Through Delphi expert consultation, a narrative nursing model for negative emotions in patients with AP was constructed. A non-randomized quasi-experimental study design was used in this study. A total of 92 patients with AP with negative emotions admitted to a tertiary hospital in Nantong City of Jiangsu Province, China from September 2022 to August 2023 were recruited by convenience sampling, among whom 46 patients admitted from September 2022 to February 2023 were included in the observation group, and 46 patients from March to August 2023 were selected as control group. The observation group received narrative nursing plan, while the control group was given with routine nursing. Self-rating anxiety scale (SAS), self-rating depression scale (SDS), positive and negative affect scale (PANAS), caring behavior scale, patient satisfaction scale and 36-item short form health survey questionnaire (SF-36) were used to evaluate their emotions, satisfaction and caring behaviors in the two groups on the day of discharge, 1-and 3-month following discharge. RESULTS According to the inclusion and exclusion criteria, a total of 45 cases in the intervention group and 44 cases in the control group eventually recruited and completed in the study. On the day of discharge, the intervention group showed significantly lower scores of SAS, SDS and negative emotion (28.57 ± 4.52 vs 17.4 ± 4.44, P < 0.001), whereas evidently higher outcomes in the positive emotion score, Caring behavior scale score and satisfaction score compared to the control group (P < 0.05). Repeated measurement analysis of variance showed that significant between-group differences were found in time effect, inter-group effect and interaction effect of SAS and PANAS scores as well as in time effect and inter-group effect of SF-36 scores (P < 0.05); the SF-36 scores of two groups at 3 months after discharge were higher than those at 1 month after discharge (P < 0.05). CONCLUSION The application of narrative nursing protocols has demonstrated significant effectiveness in alleviating anxiety, ameliorating negative emotions, and enhancing satisfaction among patients with AP.
Meltblown nonwoven materials have gained attention due to their excellent filtration performance. The research on the performance of the intercalation meltblown preparation process is complex and a current research focus in the field of chemical production. Based on data related to intercalated and unintercalated meltblown materials under given process conditions, a product performance prediction model of intercalated meltblown materials was established under different process parameters (receiving distance, hot air velocity). The structural variables (thickness, porosity, and compressive resilience), the change in product performance, and the relationship between structural variables and product performance (filtration resistance, efficiency, air permeability) after intercalation were studied. Multiple regression analysis was used to analyze the structural variables, and evaluation of the regression results were made using R2, MSE, SSR, and SST. A BP neural network prediction model for product performance was established. The BP neural network model was used to find the maximum filtration efficiency. The study provides theoretical support for regulating product performance by solving the maximum filtration efficiency using BP neural network model.
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