Slowing the expansion of impervious surfaces: the key to promoting high-quality and sustainable regional development.

Sponge cities are disaster-resilient and sustainable infrastructure, and the emergence of impervious surfaces hinders the construction of sponge cities. In response to the United Nations' 2030 Sustainable Development Goals, the study of the spatio-temporal evolution and influencing factors of impervious surfaces provides an effective basis for the construction of sponge cities. In this paper, multi-source remote sensing images (Landsat 4-5 TM was used in 2000 and 2010, Landsat 8 OLI/TIRS was used in 2020) were used as data sources to construct a multi-feature impervious surface estimation model. By combining and refining the advantages of MISI, NDBI, and BUAI feature indices, we obtained the impervious surface cover of Nanchang City in 2000, 2010, and 2020. And its spatio-temporal evolution characteristics were analyzed by using the ESDA. The main factors of the impervious surface were analyzed by using the ordinary panel data model and the spatial durbin model. Results: (1) From 2000 to 2020, the impervious surface area of Nanchang City increased from 516.13 to 1075.12 km2. The overall impervious surface distribution in Nanchang City expressed a significant neighborhood distribution; (2) socio-economic factors had a positive role in promoting the impervious surface of Nanchang City. Among them, the correlation coefficient of the economic development index (0.2332), real estate investment (0.1518), and gross industrial output value (0.0453) were the most significant in the local areas; (3) the economic development index (0.2307), real estate investment (0.0251), and passenger volume (0.1679) stimulated the growth of impervious surfaces in adjacent areas, and the total population (-0.8074) had a buffering effect on adjacent areas. In order to promote the sustainable development of the region, it is necessary to propose corresponding measures and suggestions based on the impervious surface of Nanchang City.

Escore de Risco Clínico Simples para Prever a Mortalidade Pós-Alta Hospitalar em Pacientes Chineses Hospitalizados por Insuficiência Cardíaca / A Simple Clinical Risk Score to Predict Post-Discharge Mortality in Chinese Patients Hospitalized with Heart Failure

Resumo Fundamento Doenças cardiovasculares são a principal causa de morte na China. Entretanto, os esforços atuais para se identificar os fatores de risco de morte em pacientes hospitalizados com insuficiência cardíaca (IC) estão direcionados principalmente para a mortalidade durante a internação e a mortalidade após 30 dias nos Estados Unidos. Dessa forma, é necessário um modelo semelhante ao modelo utilizado para prever o risco considerado para procedimentos cirúrgicos cardiovasculares em pacientes para avaliar o risco de pacientes internados com diagnóstico de IC. Objetivo Identificar variáveis que podem prever a mortalidade por IC um ano após a alta hospitalar, e desenvolver um escore de risco para avaliar o risco de morte no período de um ano. Métodos No presente estudo, 1.742 pacientes chineses com IC foram divididos aleatoriamente em dois grupos: um grupo de amostra de derivação e um grupo de amostra de teste. O método de simulação Monte Carlo via Cadeias de Markov foi usado para identificar variáveis que podem prever a mortalidade um ano após a alta hospitalar. Variáveis com uma frequência >1% na análise bivariada, e que foram consideradas clinicamente significativas, foram qualificadas para análises de modelagens posteriores. A probabilidade posterior de que uma variável estava estatística e significativamente associada ao resultado foi calculada como o número total de vezes em que o IC de 95% da variável não coincidiu com 1 (ou seja, o ponto de referência), dividido pelo número total de iterações. Uma variável com uma probabilidade de 0,9 ou mais alta foi considerado um fator de risco robusto para prever o resultado, e foi incluída na lista final de variáveis. O nível de significância estatística adotado foi 5%. Resultados Cinco variáveis que pudessem prever de maneira robusta a mortalidade um ano após a alta hospitalar foram identificadas: idade, sexo feminino, escore da New York Heart Association (Associação de Cardiologia de Nova Iorque) >3, diâmetro do átrio esquerdo, e índice de massa corporal. Os modelos de derivação e de teste tiveram uma área de curva característica de operação do receptor de 0,79. Essas variáveis selecionadas foram utilizadas para avaliar o escore de risco de mortalidade por IC após um ano, e este foi dividido em três grupos (baixo, moderado e alto). O grupo de alto risco corresponde a aproximadamente 86% das mortes, e o grupo de risco moderado corresponde a 12% das mortes. Conclusão Um escore de risco de 5 variáveis simples pode ser utilizado para avaliar a mortalidade um ano após a alta hospitalar de pacientes internados com IC.

Abstract Background Cardiovascular diseases are the leading causes of death in China. However, present efforts to identify the risk factors for death in patients hospitalized with heart failure (HF) are primarily focused on in-hospital mortality and 30-day mortality in the United States. Thus, a model similar to the model used for predicting the risk in patients considered for cardiovascular surgical procedures is needed to evaluate the risk of the patients admitted with a diagnosis of HF. Objective To identify variables that can predict post-discharge one-year HF mortality and develop a risk score to assess the risk of dying within one year. Methods In the present study, 1,742 Chinese patients with HF were randomly divided into two groups: a derivation sample group and a test sample group. A Markov Chain Monte Carlo simulation method was used to identify variables that can predict the one-year post-discharge mortality. Variables with a frequency of >1% in the bivariate analysis and that were considered clinically meaningful were eligible for further modeling analyses. The posterior probability that a variable was statistically and significantly associated with the outcome was calculated as the total number of times that the variable's 95% CI did not overlap with 1 (i.e., the reference point) divided by the total number of iterations. A variable with a probability of 0.9 or higher was considered a robust risk factor for predicting the outcome, and this was included in the final variable list. The level of statistical significance adopted was 5%. Results Five variables that could robustly predict the one-year post-discharge mortality were identified: age, female gender, New York Heart Association functional classification score >3, left atrial diameter, and body mass index. Both derivation and test models had a receiver operating curve area of 0.79. These selected variables were used to assess the one-year HF mortality risk score, and these were divided into three groups (low, moderate, and high). The high-risk group corresponds to nearly 86% of the deaths, while the moderate group corresponds to 12% of the deaths. Conclusion A simple 5-variable risk score can be used to assess the one-year post-discharge mortality of hospitalized Chinese patients with HF.

A Simple Clinical Risk Score to Predict Post-Discharge Mortality in Chinese Patients Hospitalized with Heart Failure. / Escore de Risco Clínico Simples para Prever a Mortalidade Pós-Alta Hospitalar em Pacientes Chineses Hospitalizados por Insuficiência Cardíaca.

BACKGROUND: Cardiovascular diseases are the leading causes of death in China. However, present efforts to identify the risk factors for death in patients hospitalized with heart failure (HF) are primarily focused on in-hospital mortality and 30-day mortality in the United States. Thus, a model similar to the model used for predicting the risk in patients considered for cardiovascular surgical procedures is needed to evaluate the risk of the patients admitted with a diagnosis of HF. OBJECTIVE: To identify variables that can predict post-discharge one-year HF mortality and develop a risk score to assess the risk of dying within one year. METHODS: In the present study, 1,742 Chinese patients with HF were randomly divided into two groups: a derivation sample group and a test sample group. A Markov Chain Monte Carlo simulation method was used to identify variables that can predict the one-year post-discharge mortality. Variables with a frequency of >1% in the bivariate analysis and that were considered clinically meaningful were eligible for further modeling analyses. The posterior probability that a variable was statistically and significantly associated with the outcome was calculated as the total number of times that the variable's 95% CI did not overlap with 1 (i.e., the reference point) divided by the total number of iterations. A variable with a probability of 0.9 or higher was considered a robust risk factor for predicting the outcome, and this was included in the final variable list. The level of statistical significance adopted was 5%. RESULTS: Five variables that could robustly predict the one-year post-discharge mortality were identified: age, female gender, New York Heart Association functional classification score >3, left atrial diameter, and body mass index. Both derivation and test models had a receiver operating curve area of 0.79. These selected variables were used to assess the one-year HF mortality risk score, and these were divided into three groups (low, moderate, and high). The high-risk group corresponds to nearly 86% of the deaths, while the moderate group corresponds to 12% of the deaths. CONCLUSION: A simple 5-variable risk score can be used to assess the one-year post-discharge mortality of hospitalized Chinese patients with HF.

FUNDAMENTO: Doenças cardiovasculares são a principal causa de morte na China. Entretanto, os esforços atuais para se identificar os fatores de risco de morte em pacientes hospitalizados com insuficiência cardíaca (IC) estão direcionados principalmente para a mortalidade durante a internação e a mortalidade após 30 dias nos Estados Unidos. Dessa forma, é necessário um modelo semelhante ao modelo utilizado para prever o risco considerado para procedimentos cirúrgicos cardiovasculares em pacientes para avaliar o risco de pacientes internados com diagnóstico de IC. OBJETIVO: Identificar variáveis que podem prever a mortalidade por IC um ano após a alta hospitalar, e desenvolver um escore de risco para avaliar o risco de morte no período de um ano. MÉTODOS: No presente estudo, 1.742 pacientes chineses com IC foram divididos aleatoriamente em dois grupos: um grupo de amostra de derivação e um grupo de amostra de teste. O método de simulação Monte Carlo via Cadeias de Markov foi usado para identificar variáveis que podem prever a mortalidade um ano após a alta hospitalar. Variáveis com uma frequência >1% na análise bivariada, e que foram consideradas clinicamente significativas, foram qualificadas para análises de modelagens posteriores. A probabilidade posterior de que uma variável estava estatística e significativamente associada ao resultado foi calculada como o número total de vezes em que o IC de 95% da variável não coincidiu com 1 (ou seja, o ponto de referência), dividido pelo número total de iterações. Uma variável com uma probabilidade de 0,9 ou mais alta foi considerado um fator de risco robusto para prever o resultado, e foi incluída na lista final de variáveis. O nível de significância estatística adotado foi 5%. RESULTADOS: Cinco variáveis que pudessem prever de maneira robusta a mortalidade um ano após a alta hospitalar foram identificadas: idade, sexo feminino, escore da New York Heart Association (Associação de Cardiologia de Nova Iorque) >3, diâmetro do átrio esquerdo, e índice de massa corporal. Os modelos de derivação e de teste tiveram uma área de curva característica de operação do receptor de 0,79. Essas variáveis selecionadas foram utilizadas para avaliar o escore de risco de mortalidade por IC após um ano, e este foi dividido em três grupos (baixo, moderado e alto). O grupo de alto risco corresponde a aproximadamente 86% das mortes, e o grupo de risco moderado corresponde a 12% das mortes. CONCLUSÃO: Um escore de risco de 5 variáveis simples pode ser utilizado para avaliar a mortalidade um ano após a alta hospitalar de pacientes internados com IC.

Evaluation of a Community Health Service Center-Based Intervention Program for Managing Chronic Heart Failure.

BACKGROUND: Although the role of primary care for the management of patients with chronic heart failure (CHF) has been highly recommended, structural involvement of primary care in heart failure (HF) management programs is extremely limited. AIMS: To examine the feasibility and applicability of two most recommended forms of care delivery mode, home visit and telephone support, for CHF management in the setting of community health service center (CHSC). STUDY DESIGN: Prospective study. METHODS: This study was conducted in two CHSCs in Beijing, China. Care delivery was led by trained general practitioners or community nurses via home visits in one CHSC and telephone support in the other. Data regarding the change in mortality and hospitalization rate during 12 months and self-care level at 6 months were prospectively collected and compared across the intervention groups. RESULTS: A total of 329 patients were included, with 142 in the home visit group and 187 in the telephone support group. Patients in both groups had frequent visits to CHSC (8.1±5.9 in the home visit and 7.7±4.1 in the telephone support group, p=0.45) during the follow-up period. Compared to the telephone support group, patients in the home visit group showed a reduction in all-cause mortality (14.1% versus 20.3%, p=0.14), one or more hospitalizations due to any cause (33.8% versus 44.2%, p=0.12) and one or more hospitalizations due to cardiac cause (17.6% versus 24.6%, p=0.13) in the home visit group. The absolute differences were 6.2% (95% CI: 1.9%, 14.3%), 8.4% (95% CI: 2.1%, 18.9%) and 7.3% (95% CI: 1.5%, 16.1%), respectively, although the results were not statistically significant. After 6 months of intervention, patients in both groups achieved marked improvement in self-care with reference to their own baseline values. CONCLUSION: Although no statistical difference was observed between the two care delivery approaches regarding the clinical outcomes of interest, given the high participation rates, the acceptable rate of adverse events, frequent CHSC visits and patients' preferences in the current study, it was concluded that CHSC might be the optimal setting for delivering care to CHF patients in China.