Objective To explore the effects of two methods of air-impact on clearing the subglottic secretion in patients with intubation.Methods A simple random sampling method was used to select 106 patients underwent mechanical ventilation through oral tracheal intubation in intensive medicine department from September 2016 to October 2017.The recruited patients were divided into two groups by the random number table,53 patients in Group A were treated with breath-holding key of a ventilator,combined with air-bag inflation and deflation,and 53 patients in Group B were treated with simple breathing apparatus combined with manual technique to clear subglottic secretion.The incidence of ventilator-associated pneumonia(VAP),amount of cleared subglottic secretions,difference of vital signs before and after operation,number of coughing,in vitro training time and operation time were compared between groups.Results The intention-to-treat ana]ysis(ITT) showed that the incidence of VAP in Group A and B were 7.55％ and 5.66％,the per-protocol analysis(PP) showed that the incidence of VAP in Group A and B were 3.92％ and 3.85％,and there was no significant difference between groups(P＞0.05);the amount of cleared subglottic secretions in two groups were (8.31±0.82) ml,(7.97±1.12)ml,and there was no significant difference (P＞ 0.05);but vital signs before and after operation,number of coughing,in vitro training time and operation time in Group A were lower than those in Group B,and the differences were statistically significant(P＜0.05).Conclusion Two methods of air-impact can both effectively reduce the incidence of VAP,but using breath-holding key of a ventilator combined with airbag inflation and deflation has less influence on vital signs,which patients can better tolerate and medical staff can master and cooperate more easily.

Objective To explore the ^“contribution^” of different exposures to cardiovascular diseases at the population level and to construct a risk prediction model for the effective allocation of prevention resources. Methods The CHNS (China Health and Nutrition Survey) database was used. In 2009, 2011 and 2015, 9 899 permanent residents aged 35 to 75 years in 10 provinces and cities in the central and eastern regions (Beijing, Liaoning, Heilongjiang, Shanghai, Shandong, Henan, Hubei, Hunan, Guangxi and Jiangsu) were selected as the research subjects. A single-factor analysis was conducted to examine the risk factors including sex, age, BMI, marital status, urban/rural area, sleep time, smoking, alcohol consumption, diabetes, education, and health insurance. The multifactor-adjusted population-attributable risk of certain risk factors was also estimated based on logistic regression analysis. The cardiovascular disease (CVD) risk prediction model was developed using a modeling group of 6 927 randomly selected individuals (70%) and a validation group of 2 974 individuals (30%). The model's differentiation and calibration were assessed using the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow goodness-of-fit test. Results The results showed that the adjusted population attributable risk and 95% confidence interval for BMI, sleep time, smoking, drinking and diabetes were 32.20% (27.67%-36.89%), 7.90% (1.68%-16.58%), 18.56% (11.35%-26.24%), 6.47% (0.11%-13.25%) and 5.73% (4.42%-7.03%). The results of multivariate adjusted population attributable risk percentage showed that BMI was the dominant cause of cardiovascular diseases, followed by smoking, sleep time, drinking and diabetes. The low-risk prevalence rate was 18.44%, the higher-risk prevalence rate was 14.19%, and the high-risk prevalence rate was 42.52%. The area under ROC curve AUC was 0.711, P<0.001, and Hosmer-Lemeshow goodness of fit test showed P=0.257. Conclusion In the future, it is important to focus on high-risk groups , control body mass index to the normal range, and reduce smoking , which is of great significance for the prevention of cardiovascular diseases. The risk prediction model has the value of good differentiation and practicability , and can provide certain prediction ability for the prevention of cardiovascular diseases.