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There is clear evidence that high sodium intake is associated with many health issues including hypertension and cardiovascular diseases (CVDs). Several national and worldwide studies have estimated deaths from CVDs attributable to high sodium. But how to evaluate the impact of high sodium intake on diseases using regional routine monitoring and investigation data is necessary and important. Our study aimed to quantitatively evaluate the high sodium intake attributed to CVDs deaths based on the routine monitoring data from China National Nutrition and Health Survey (CNNHS) in Tianjin, China. The population attributable fractions (PAF) were calculated by comparing the observed systolic blood pressure (SBP) distribution with the theoretical minimum or counterfactual distribution by sex and age groups. The results showed that CVDs deaths due to elevated SBP were 22728 (95% uncertainty intervals: 22679-23050), accounting for 62.8% of total CVDs deaths. According to sodium intake recommended by World Health Organization (WHO), PAF of CVDs deaths attributable to high sodium diet in our study was 14.6% of total CVDs deaths, accounting for 5228 (95% UI: 5005-5998) cases. The dietary sodium intake of residents is nearly three times than sodium intake recommended by WHO. If sodium intake was reduced to reference level, the potential avoidable CVD deaths attributable to the SBP-raising effect were more than 5200 among adults 25 aged and over in Tianjin. This evaluation method can be extended to other cities.

Improving green total factor productivity (GTFP) is an important theme. Whether collaborative agglomeration between logistics industry and manufacturing (LMCA) can effectively promote GTFP is worth further research. Based on the panel data of 284 cities in China from 2005 to 2018, GTFP is calculated by using the Biennial Malmquist-Luenberger productivity index (BMLPI), and this research investigates the impact of LMCA on GTFP by adopting the spatial Durbin model (SDM) and threshold regressive model (TRM). First, LMCA plays a significant role in promoting the improvement of GTFP in the local and surrounding areas through the knowledge spillover effect, scale economy effect, resource allocation effect and symbiotic economic effect, and the spillover effect is greater than the local effect. Second, the positive direct effect of LMCA on GTFP comes mainly from technological progress, and the positive indirect effect of LMCA on GTFP comes mainly from the positive spillover effect of technological progress and technical efficiency improvement. Finally, the Williamson hypothesis exists significantly in the collaborative agglomeration scenario of the logistics industry and manufacturing of China. With the improvement of the level of economic development, the impact of LMCA on GTFP changes from insignificant to promoting. However, when it is further improved, the promoting effect turns into an inhibiting effect, and this change is dominated mainly by the impact of LMCA on technical change.

Improving green total factor productivity (GTFP) is an important theme. Whether collaborative agglomeration between logistics industry and manufacturing (LMCA) can effectively promote GTFP is worth further research. Based on the panel data of 284 cities in China from 2005 to 2018, GTFP is calculated by using the Biennial Malmquist-Luenberger productivity index (BMLPI), and this research investigates the impact of LMCA on GTFP by adopting the spatial Durbin model (SDM) and threshold regressive model (TRM). First, LMCA plays a significant role in promoting the improvement of GTFP in the local and surrounding areas through the knowledge spillover effect, scale economy effect, resource allocation effect and symbiotic economic effect, and the spillover effect is greater than the local effect. Second, the positive direct effect of LMCA on GTFP comes mainly from technological progress, and the positive indirect effect of LMCA on GTFP comes mainly from the positive spillover effect of technological progress and technical efficiency improvement. Finally, the Williamson hypothesis exists significantly in the collaborative agglomeration scenario of the logistics industry and manufacturing of China. With the improvement of the level of economic development, the impact of LMCA on GTFP changes from insignificant to promoting. However, when it is further improved, the promoting effect turns into an inhibiting effect, and this change is dominated mainly by the impact of LMCA on technical change.

The logistics and manufacturing industries are basic industries that support social development. First, this study classifies the carbon emissions from the logistics industry and pollution emissions from the manufacturing industry as undesirable outputs and evaluates the ecological efficiency of the logistics and manufacturing industries in the Yangtze River Delta from 2006 to 2016 by using the unexpected slacks-based measure (SBM) model. Second, the study analyzes the spatial differences in industrial correlation efficiency by using the exploratory spatial data analysis method. Third, the spatial econometric model is used to analyze the driving factors of the linkage ecological efficiency between logistics industry and manufacturing industry. Finally, the neural network model is used to predict the linkage ecological efficiency. The results show that the ecological efficiency of the manufacturing industry has steadily improved. The ecological efficiency of the logistics industry presents the rising trend in fluctuation. The level of the linkage development between the logistics and manufacturing industries is high. The results of the spatial heterogeneity analysis show that the spatial differentiation of high–high agglomeration and low–low agglomeration is obvious. The spatial agglomeration characteristics are relatively stable, and the spatial diffusion effect is strong. In space, the linkage ecological efficiency shows a trend of development from multiple agglomeration areas to one agglomeration area. The results of driving factor analysis show that foreign direct investment (FDI), government intervention (GI), and human capital (HP) have positive effects on linkage ecological efficiency, while industrial structure (IS), environmental regulation (ER), and energy intensity (EI) have negative effects on linkage ecological efficiency. The results of the linkage development trend analysis show that the linkage ecological efficiency of the two industries will tend to be stable in the future.

Background The purpose of this study was to retrospectively analyze clinical characteristics and prognostic risk factors of urosepsis patients admitted to two intensive care units in Shanghai, China. Methods Clinical data from patients diagnosed with urosepsis were retrospectively retrieved and analyzed from ICU in two regional medical centers from January 2015 to December 2019. Results Two hundred two patients were included in the subsequent analysis eventually, with an average age of 72.02 ± 9.66 years, 79.21% of the patients were female and the mortality rate of 15.84%.The proportion of patients with chronic underlying diseases such as diabetes and hypertension was relatively high (56.44, 49.50%, respectively), and the incidence of shock was also high (41.58%) correspondingly. The most common pathogen isolated was Escherichia coli (79.20%), of which the extended-spectrumβ-lactamases (ESBLs)(+) accounted for 42.57%. In multivariate analysis, the strongest predictors for death were mechanical ventilation (OR 7.260, 95% CI 2.200–23.963; P = 0.001),chronic kidney disease (CKD) (OR 5.140, 95% CI 1.596–16.550; P = 0.006), APACHE II score (OR 1.321, 95% CI 1.184–1.473; P P = 0.020). Both APACHE II score and lactate had the ideal predictive value, with the area under the ROC curve (AUC) of 0.858 and 0.805 respectively. Conclusion The patients with urosepsis were characterized by a higher proportion of female, older age, more percentage of comorbidities in this region, and patients with ESBLs (+) Escherichia coli infection were more prone to shock. Mechanical ventilation, comorbidity with CKD, APACHE II score and lactate were independent risk factors for death in urosepsis patient, but lactate level and APACHE II score had better predictive value for prognosis.

BACKGROUND Evidence shows that simplified SOFA scoring system has better clinical practice. OBJECTIVE This study aimed to validate and compare the scores acquired with simplified organ dysfunction criteria optimized for electronic health records (eSOFA), and simplified and accurate sequential organ failure assessment (sa-SOFA) for their accuracies in predicting the prognosis of septic patients. METHODS This retrospective observational study was conducted at three major academic hospitals. Clinical data from 574 patients diagnosed with sepsis following the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)were retrospectively retrieved and analysed. Scores from the quick sequential organ failure assessment (qSOFA) and sequential organ failure assessment (SOFA) were used as reference scores. The area under the receiver operating characteristic curve (AUROC) was used to assess the performance of eSOFA and sa-SOFA scores in predicting in-hospital mortality. RESULTS AUROC analysis demonstrated the predictability of the four scoring systems for sepsis surveillance, listed in descending order as: sa-SOFA, 0.790 (95% confidence interval [CI]: 0.754-0.822); SOFA, 0.774 (95% CI: 0.738-0.808); eSOFA, 0.729 (95% CI: 0.691-0.765); and qSOFA, 0.618 (95% CI: 0.577-0.658). Moreover, sa-SOFA and SOFA scores (Z = 1.950, P = .051) did not significantly differ from each other in discriminatory power, but the sa-SOFA score had a higher power than eSOFA score (P values

According to the different organizational forms of logistics in manufacturing, the types of linkage development between the logistics and manufacturing industries include two different logistics service modes: logistics outsourcing and logistics self-operation. This study considers two manufacturing clusters for comparison: the northeast region in China, mainly state-owned and self-operated, and the Yangtze River Delta region in China, mainly focusing on logistics outsourcing services. First, we construct a parallel network system considering heterogeneity and an unexpected super-efficiency slacks-based measure: the Grey Relational Analysis model. Second, considering the unexpected output, this study evaluates the environmental performance of the linkage development of the logistics and manufacturing industries and explains the types of linkage development between them. Finally, the spatial and temporal characteristics of linkage efficiency under different linkage modes are studied using an exploratory spatial data analysis method. The research results show that the efficiency of the two-industry linkage in different linkage types that consider the unexpected output presents different development characteristics. Regarding time characteristics and trends, we compare the development efficiency of the two-industry linkage at the overall level of the northeast and the Yangtze River Delta regions from 2009 to 2016. The Yangtze River Delta region showed a higher state of linkage while the northeast region showed a medium linkage state. Regarding spatial pattern evolution, the effect of the technical efficiency of the linkage between the two industries in the three northeastern provinces showed continuous evolution from the medium linkage stage to the weak linkage stage, and the Yangtze River Delta showed continuous evolution from the medium linkage to the strong linkage stage.

Background: Evidence shows that simplified SOFA scoring system has better clinical practice. Objective: This study aimed to compare the scores acquired with the simplified sequential organ failure assessment (sSOFA), simplified organ dysfunction criteria optimized for electronic health records (eSOFA), and simplified and accurate sequential organ failure assessment (sa-SOFA) for their accuracies in predicting the prognosis of septic patients. Methods: This retrospective observational study was conducted at three major academic hospitals. Clinical data from 574 patients diagnosed with sepsis following the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)were retrospectively retrieved and analyzed. Scores from the quick sequential organ failure assessment (qSOFA) and sequential organ failure assessment (SOFA) were used as reference scores. The area under the receiver operating characteristic curve (AUROC) was used to compare the accuracies of eSOFA, sSOFA, and sa-SOFA scores in predicting in-hospital mortality. Results: AUROC analysis demonstrated the predictability of the five scoring systems for sepsis surveillance, listed in descending order as: sa-SOFA,0.790 (95% confidence interval [CI]: 0.754-0.822); SOFA, 0.774 (95% CI: 0.738-0.808); eSOFA,0.729 (95% CI: 0.691-0.765); sSOFA,0.681 (95% CI: 0.641- 0.719); and qSOFA,0.618(95% CI: 0.577-0.658). Moreover, sa-SOFA and SOFA scores (Z= 1.950, p = 0.051) did not significantly differ from each other in discriminatory power, but the sa-SOFA score had a higher power than either the sSOFA or eSOFA scores (p values

Based on the journal resource from the cqvip database, taking "cultural and creative industry" as the keyword, the paper retrieved all the relevant "CSSCI" documents from 1989 to 2012. After getting the keywords co-occurrence matrix through BIBCOMB software, the paper focused on the keywords analysis which was obtained by the software UCINET and NETDRAW. Then it comes to the conclusion, which shows that development countermeasures, cultural area, cultural creativity and influential factors are the hotspots in present research.