Objective:To explore the impacts of smoking on the need for respiratory support and mortality in patients hospitalized with pneumonia.Methods:A total of 24 367 patients hospitalized with pneumonia from 2009 to 2017 in the China Kadoorie Biobank, were included. Smoking status was self-reported, and data regarding respiratory support during hospitalization and mortality during follow-up were obtained from medical claims and death registries, respectively. OR, HR, and 95% CI were calculated and adjusted for potential confounders using logistic regression models and Cox proportional hazards regression models, respectively. Results:Among males, current smokers or those who quit smoking due to illness had higher risks of requiring respiratory support ( OR=1.15, 95% CI: 1.03-1.29), 1-year mortality ( HR=1.66, 95% CI: 1.32-2.08), and 5-year mortality ( HR=1.32, 95% CI: 1.13-1.54) following pneumonia hospitalization compared to nonsmokers. Male smokers who started smoking at a younger age or with longer smoking duration had the highest mortality risks (trend test both P<0.05). Female current smokers or those who quit smoking due to illness had higher risks of 1-year mortality ( HR=1.62, 95% CI: 1.17-2.23) and 5-year mortality ( HR=1.33, 95% CI: 1.06-1.67). We found no statistically significant difference in 90-day mortality between current smokers/those who quit smoking due to illness and nonsmokers. Conclusions:Smoking was associated with higher risks of requiring respiratory support and mortality in patients hospitalized with pneumonia, especially among males and heavy smokers. These findings highlight the need for targeted strategies to promote smoking cessation in patients hospitalized with pneumonia.

Objective:To explore the impacts of smoking on the need for respiratory support and mortality in patients hospitalized with pneumonia.Methods:A total of 24 367 patients hospitalized with pneumonia from 2009 to 2017 in the China Kadoorie Biobank, were included. Smoking status was self-reported, and data regarding respiratory support during hospitalization and mortality during follow-up were obtained from medical claims and death registries, respectively. OR, HR, and 95% CI were calculated and adjusted for potential confounders using logistic regression models and Cox proportional hazards regression models, respectively. Results:Among males, current smokers or those who quit smoking due to illness had higher risks of requiring respiratory support ( OR=1.15, 95% CI: 1.03-1.29), 1-year mortality ( HR=1.66, 95% CI: 1.32-2.08), and 5-year mortality ( HR=1.32, 95% CI: 1.13-1.54) following pneumonia hospitalization compared to nonsmokers. Male smokers who started smoking at a younger age or with longer smoking duration had the highest mortality risks (trend test both P<0.05). Female current smokers or those who quit smoking due to illness had higher risks of 1-year mortality ( HR=1.62, 95% CI: 1.17-2.23) and 5-year mortality ( HR=1.33, 95% CI: 1.06-1.67). We found no statistically significant difference in 90-day mortality between current smokers/those who quit smoking due to illness and nonsmokers. Conclusions:Smoking was associated with higher risks of requiring respiratory support and mortality in patients hospitalized with pneumonia, especially among males and heavy smokers. These findings highlight the need for targeted strategies to promote smoking cessation in patients hospitalized with pneumonia.

Objective:To develop an R script that can efficiently and accurately filter genome-wide association studies (GWASs) from the GWAS Catalog Website.Methods:The selection principles of GWASs were established based on previous studies. The process of manual filtering in the GWAS Catalog was abstracted as standard algorithms. The R script (gwasfilter.R) was written by two programmers and tested many times.Results:It takes six steps for gwasfilter.R to filter GWASs. There are five main self-defined functions among this R script. GWASs can be filtered based on "whether the GWAS has been replicated" "sample size" "ethnicity of the study population" and other conditions. It takes no more than 1 second for this script to filter GWASs of a single trait.Conclusions:This R script (gwasfilter.R) is user-friendly and provides an efficient and standard process to filter GWASs flexibly. The source code is available at github ( https://github.com/lab319/gwas_filter).

Chondroitin sulfate (CS) is a sulfurated glycosaminoglycan, a major component of the extracellular matrix, widely distributed in skin, cartilage and vascular tissue. CS plays an important role in the physiological state regulation of articular cartilage, which affects tensile strength and elasticity of tissues by influencing aggrecan. Previous studies have shown that CS sulfate modification may be related to the growth and development disorders of cartilage tissue and the occurrence of osteoarticular diseases. At the same time, CS is also a common joint supplement, often used in the treatment of osteoarthritis and Kashin-Beck disease. In this paper, the research progress of CS sulfate modification characteristics in Kashin-Beck disease and osteoarthritis and the application of the preparation in the treatment of Kashin-Beck disease and osteoarthritis are reviewed, aiming to provide help for the investigation of the etiology of Kashin-Beck disease and the treatment of osteoarthritis and Kashin-Beck disease.