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Background: Klebsiella pneumoniae (KP) is the most common pathogen isolated in intensive care units (ICUs) and the most frequently encountered carbapenemase-producing Enterobacteriaceae. Increasing antimicrobial drug resistance, especially in carbapenem-resistant KP (CRKP), can limit the choice of antibiotics used for the treatment of infectious diseases and further poses a negative impact on patient outcome. However, the reason behind this increasing resistance is not well known. Patients and methods: A retrospective analysis of laboratory records and clinical cases of KP infection in the ICUs of a hospital from January 2013 to December 2017 was conducted. The disk diffusion method and double-paper synergy test were used to test drug sensitivity for extended-spectrum β-lactamase (ESBL) detection. WHONET5.6 and SPSS 21.0 software were used for statistical analysis. Results: A total of 64.8% (570/847) of patients with KP infection were older than 60 years. The lower respiratory tract was the main infection site, accounting for 70.84% (600/847); the highest rate of ICU admission was for neurosurgery, accounting for 28.69% (243/847). Some 444 multidrug-resistant KP strains were detected, including 69 CRKP and 299 ESBL-producing strains. In the past 5 years, the resistance rate of detected strains to common antibiotics increased to various degrees, particularly carbapenem-resistant strains which increased from 4.76% (9/189) in 2013 to 16.00% (28/175) in 2017. All carbapenem-resistant isolates were resistant to β-lactam antibiotics, and no isolates were resistant to tigecycline. Conclusion: CRKP and ESBLKP prevalence and resistance rates gradually increased in our ICUs in the past 5 years. The reasons for this are manifold. Regular surveillance of resistance, rational use of antibiotics, and other effective infection control measures need to be strengthened to slow down the production of multidrug-resistant bacteria and prevent their spread in ICU settings. [ABSTRACT FROM AUTHOR]

Studying the driving factors of pollutant emissions is of great significance for China in the formulation of pollution control strategies. Existing studies mainly focus on the causes of national aggregate emission changes. However, considering the large differences among provinces in China and their close economic linkages, it is necessary to develop a provincial-level analysis to shape provincial policies for emission reduction. Using the multi-regional input-output (MRIO) tables of 30 provinces in China and adopting structural decomposition analysis, we analyze how changes in the end-of-pipe treatment, cleaner production, economic production structure, domestic final use, domestic exports and international exports drive national and provincial SO 2 emissions. Decomposition results show that during 2002–2010 the absolute value of each effect based on the MRIO model is higher than that based on the national aggregate input-output model, which indicates that the existing studies adopting the national average data conceal the variation in the driving factors and underestimate their contributions to SO 2 emission changes. The decomposition results based on MRIO model further show that the end-of-pipe treatment and cleaner production are the major emission reduction factors for all provinces, and the effect of the former has noticeably increased during 2007–2010. For the eastern provinces, interestingly, the economic production structure becomes a major emission reduction factor during the period of 2007–2010. Changes in domestic final demand, domestic exports and international exports exhibit significantly different contributions among provinces. The increased final demand in eastern provinces largely drive SO 2 emissions for all provinces. Based on the above findings, policy implications that address the SO 2 emission reduction issues are proposed. • Drivers of provincial SO 2 emissions in China is examined by using MRIO-SDA. • Large differences and close economic linkages among provinces in China are captured. • Absolute value of decomposition results based on MRIO model were higher than that based on national aggregate IO model. • Changes of economic production structures reduced SO 2 emissions in the eastern provinces. • The increased final demand in eastern provinces drove SO 2 emissions for all provinces. [ABSTRACT FROM AUTHOR]