Objective To investigate the effects of median effective dose (ED50 )of ropivacaine combined with sufentanil for spinal anesthesia in elderly patients.Methods Forty-eight elderly patients (ASAⅠ-Ⅲ)scheduled for elective lower limb or perineum operation under spinal anesthesia were enrolled in this study.All patients were randomly divided into two groups:control group (group C)and sufentanil group (group S).L3-4 intervertebral puncture was selected for all patients.Anesthetic solution in group C was 0.5% ropivacaine,in group S was 0.5% ropivacaine and sufentanil,which was fixed at 5.0 μg,based on the experimental results and sequential principle.The ropivacaine dose of first patient in the control group was 9.0 mg,and in sufentanil group was 8.0 mg,followed by reducing the dose of ropivacaine,each time 1.0 mg.If the patient appeared invalid standards response,the previous one was selected as the first case. ED50 was determined by Dixon??s sequential method.Results The ED50 of sufentanil combined with ropiva-caine for spinal anesthesia in elderly patients with lower extremity or perineal surgery was 6.40 mg (95%CI:5.98-6.80 mg),ED50 of only ropivacaine was 8.42 mg (95% CI:7.79-9.03 mg).Compared with pre-dose,MAP at 3,6,15 min after treated in group C were decreased,and lower than those in group S (P <0.01).Conclusion Combined with 5.0 μg sufentanil in spinal anesthesia for lower limb or perineal surgery elderly,median effective dose of ropivacaine is reduced.

Objective:To explore the correlation between glycemic control of type 2 diabetes mellitus (T2DM) patients and brachial-ankle pulse velocity (baPWV). Methods:A community-based cross-sec-tional study was conducted in Beijing, China. Every subject underwent physical examinations, glycated hemoglobin ( HbA1 c ) , blood lipid and baPWV measurements and completed a standardized question-naire. T2DM patients were divided into well controlled and poorly controlled groups according to HbA1c levels. The correlation between glycemic control of T2DM patients and baPWV was analyzed. Results:In this study, 1 341 subjects were recruited, including 733 T2DM patients and 608 non-diabetes sub-jects. Compared with non-diabetes subjects, abnormal baPWV ( baPWV≥1 700 cm/s) rate for T2DM patients was higher (40. 8% vs. 26. 8%, P<0. 001). With HbA1c<6. 5% or <7. 0% as the aim of glycemic control in T2DM patients, the abnormal baPWV rates for non-diabetes subjects, well controlled and poorly controlled T2DM patients were significantly different (non-diabetes vs. HbA1c<6. 5% T2DM vs. HbA1c≥6. 5% T2DM: 26. 8% vs. 32. 8% vs. 42. 6%, P <0. 001; non-diabetes vs. HbA1c <7. 0% T2DM vs. HbA1c≥7. 0% T2DM:26. 8% vs. 36. 1% vs. 43. 4%, P<0. 001). After being ad-justed for gender, age, smoking status, diabetes mellitus family history, T2DM duration, cardiovascular diseases ( CVD ) , waist hip ratio ( WHR ) , systolic blood pressure ( SBP ) , diastolic blood pressure ( DBP) , total triglycerides ( TG) , high density lipoprotein cholesterol ( HDL-C) , and low density lipo-protein cholesterol ( LDL-C ) , the Logistic regression models suggested that glycemic control status of T2DM patients was associated with abnormal baPWV. Compared with non-diabetes subjects, the ORs for abnormal baPWV in HbA1 c <6 . 5% T2 DM patients and HbA1 c≥6 . 5% T2 DM patients were 0 . 927 (95%CI 0. 560-1. 537) and 1. 826 (95%CI 1. 287-2. 591). Compared with non-diabetes subjects, the ORs for abnormal baPWV in HbA1c<7. 0% T2DM patients and HbA1c≥7. 0% T2DM patients were 1. 210 (95%CI 0. 808-1. 811) and 1. 898 (95%CI 1. 313-2. 745). Conclusion:The glycemic con-trol status of T2DM patients from communities is significantly associated with baPWV. Poor glycemic con-trol is a risk factor for abnormal baPWV. Keeping HbA1c under control might lower the risk of cardiovas-cular diseases in T2DM patients.

Objective To identify post?marketing active surveillance systems for vaccine safety around the world and understand their features and mechanisms, in order to provide guidance for vaccine administration activities in China. Methods Following the steps of scoping review, literature about active surveillance system for vaccine safety and published by 30 June 2018 were identified by searching electronic databases, including PubMed, Scopus, and Cochrane Library. Grey literature were also sought by exploring relevant websites. Identified literature were screened according to eligibility criteria, and informative data from included literature were then charted. Framework Synthesis and Thematic Analysis were performed to integrate the charted data. Results 97 pieces of literature were included for review, and 11 active surveillance systems for vaccine safety were identified, mostly located in developed countries. These systems were constructed by 3 types of organizations: administration departments, academic or research institutions, and health care providers. Their data sources included immunization registries, electronic medical records, claims data, case reports of adverse events following immunization electronic questionnaires, and epidemiologic study data. According to their operation procedures, these systems were grouped into 4 modes of active surveillance: Data Linkage, Investigator Network, Automatic Follow?up System, Studies Consortium. Conclusion Practice of active surveillance for vaccine safety greatly varies across countries, with different conditions and advantages. It is suggested that developing countries should choose suitable mode of active surveillance considering their local situations.

Objective To identify post?marketing active surveillance systems for vaccine safety around the world and understand their features and mechanisms, in order to provide guidance for vaccine administration activities in China. Methods Following the steps of scoping review, literature about active surveillance system for vaccine safety and published by 30 June 2018 were identified by searching electronic databases, including PubMed, Scopus, and Cochrane Library. Grey literature were also sought by exploring relevant websites. Identified literature were screened according to eligibility criteria, and informative data from included literature were then charted. Framework Synthesis and Thematic Analysis were performed to integrate the charted data. Results 97 pieces of literature were included for review, and 11 active surveillance systems for vaccine safety were identified, mostly located in developed countries. These systems were constructed by 3 types of organizations: administration departments, academic or research institutions, and health care providers. Their data sources included immunization registries, electronic medical records, claims data, case reports of adverse events following immunization electronic questionnaires, and epidemiologic study data. According to their operation procedures, these systems were grouped into 4 modes of active surveillance: Data Linkage, Investigator Network, Automatic Follow?up System, Studies Consortium. Conclusion Practice of active surveillance for vaccine safety greatly varies across countries, with different conditions and advantages. It is suggested that developing countries should choose suitable mode of active surveillance considering their local situations.

Objective: To explore the relationship between glycemic control and visceral adiposity index (VAI) among type 2 diabetes mellitus (T2DM) patients.Methods: A community-based epidemiological field study for patients with T2DM aged ≥ 40 years was conducted in China.Every participant underwent physical examinations, biochemical tests of fasting glucose, glycosylated hemoglobin (HbA1c), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and so on, and a questionnaire, including anthropometric characteristics, lifestyle, disease history, family history, and medication use.Those participants with HbA1c ≥7.0% were classified as the poorly controlled in our analysis of relationship between glycemic control and VAI.Anthropometric characteristics, lifestyle, and biochemical indexes of the participants were compared among the groups of different VAI levels.Logistic models were applied in multiple analysis adjusting for possible confounders.Results: A total of 1 607 patients with T2DM were recruited in our analysis with a mean age of (59.4±8.1) years and an average T2DM duration of (7.0±6.4) years.Among them, 78.3% were on hypoglycemic therapy.The cutoff points of quartiles of VAI were calculated for the males and females, respectively.According to the ascending order of the quartiles of VAI, the participants were divided into four groups, i.e.Q1, Q2, Q3, and Q4.The poor glycemic control rate for these groups were 60.6%, 65.7%, 70.1%, and 71.0%, respectively (Trend χ2=12.20, P<0.001).After adjustment for age, gender, systolic blood pressure (SBP), diastolic blood pressure (DBP), LDL-C, smoking, cardio-cerebral vascular disease (CVD) history, hypoglycemic therapy, T2DM duration, and family history of diabetes, the Logistic regression models showed that the glycemic control rate was significantly associated with VAI levels among the patients with T2DM.Compared with the participants in group Q1, the ORs of poor glycemic control for those in groups Q2, Q3, and Q4 were 1.239 (95%CI 0.918 to 1.672), 1.513 (95%CI 1.117 to 2.050), and 1.535 (95%CI 1.128to 2.088), respectively (trend P=0.003).With each quartile increase in VAI, the OR of poor glycemic control was 1.162 (95%CI 1.054 to 1.282).Conclusion: The glycemic control among the patients with T2DM is significantly associated with VAI.High level of VAI is an indicator of poor glycemic control.

Objective:To establish a multi-state Markov model of type 2 diabetes mellitus (T2DM) patients and explore the transition rule between the cumulative number of different chronic complications, estimate the transition probability and intensity between status, and explore the possible factors affecting the transition between status.Methods:A retrospective cohort study of 33 575 patients with T2DM was conducted. According to the baseline and the cumulative number of chronic complications during the follow-up period, the patients were classified based on five status: T2DM, one complication, two complications, three complications, four and above complication, indicated by S0, S1, S2, S3 and S4, respectively. A time-continuous and state-discrete multi-state irreversible Markov model was used for statistical analysis.Results:The study included 33 575 T2DM patients, and their average age was 60 years old, the median of follow-up length was 8 years. In these patients, 32 653 had no baseline complications. At the end of follow-up, the transition probabilities of S0→S1, S1→S2, S2→S3 and S3→S4 were 16.4%, 32.4%, 45.6% and 25.9%, respectively. The results of multivariate analysis showed that being female ( HR=0.919), less than 60 years old ( HR=0.929), higher fasting plasma glucose ( HR=1.601), lower high-density lipoprotein ( HR=1.087), higher total cholesterol ( HR=1.090),weekly exercise ( HR=0.897), vegetarian diet ( HR=0.852) and heavy diet ( HR=1.887) were the risk factors for S0 to S1. And being female ( HR=0.768), less than 60 years old ( HR=0.859) and lower high-density lipoprotein ( HR=1.160) were the risk factors for S1 to S2. Conclusions:The probability of multiple complications in T2DM patients increased over time, the transition intensity of S2→S3 was largest, followed by S1→S2. Therefore, we need to conduct both early and long-term indicators monitoring and disease prevention, strengthen the health education to improve patients' daily living habits at early stage of the illness, encourage patients to have moderate exercise and balanced diet, strengthen the monitoring of fasting blood- glucose, cholesterol and high-density lipoprotein levels to prevent the deterioration of the illness.

Objective: To identify post-marketing active surveillance systems for vaccine safety around the world and understand their features and mechanisms, in order to provide guidance for vaccine administration activities in China. Methods: Following the steps of scoping review, literature about active surveillance system for vaccine safety and published by 30 June 2018 were identified by searching electronic databases, including PubMed, Scopus, and Cochrane Library. Grey literature were also sought by exploring relevant websites. Identified literature were screened according to eligibility criteria, and informative data from included literature were then charted. Framework Synthesis and Thematic Analysis were performed to integrate the charted data. Results: 97 pieces of literature were included for review, and 11 active surveillance systems for vaccine safety were identified, mostly located in developed countries. These systems were constructed by 3 types of organizations: administration departments, academic or research institutions, and health care providers. Their data sources included immunization registries, electronic medical records, claims data, case reports of adverse events following immunization electronic questionnaires, and epidemiologic study data. According to their operation procedures, these systems were grouped into 4 modes of active surveillance: Data Linkage, Investigator Network, Automatic Follow-up System, Studies Consortium. Conclusion Practice of active surveillance for vaccine safety greatly varies across countries, with different conditions and advantages. It is suggested that developing countries should choose suitable mode of active surveillance considering their local situations.