OBJECTIVE To study drug resistance and distribution of infectious bacteria in lower respiratory tract among inpatients and outpatients and use the experience for reference of clinical application.METHODS Bacterial culture of the qualified sputum sample of patients who were admitted from Jan to Dec 2005 was done.The bacteria identification and drug sensitivity tests were done by ATB system.RESULTS Totally 687 strains of bacteria were isolated,the dominant were Gram-negative bacilli(81.5%).Among them,the Pseudomonas aeruginosa was 21.3%,the Acinetobacter baumannii was 19.8%,the Klebsiella pneumoniae was 14.3%,the Stenotrophomonas maltophilia was 16.6%,the Escherichia coli was 7.5%,and the others were 17.5%.The second pathogens were fungi(15.9%).The Gram-positive bacteria were the lowest ones.The results of drug sensitivity tests indicated,the imipenem was the most sensitive for Gram-negative bacilli except the P.aeruginosa and the M.stenotrophomonas(99.1% to 100.0%).For the P.aeruginosa,the amikacin was the highest one,and for the S.maltophilia,the highest was sulfamethoxazole-trimethoprim.CONCLUSIONS The dominant pathogenic bacteria in lower respiratory tract in our area are Gram-negative bacteria.For the same antimicrobial agent,different bacteria have a different sensitivity.We should select the antibiotic according to the results of drug sensitivity test.

Objective To explore how to perform effective health management for the metabolic syndrome(MS) in the health examination center. Methods A total of 153 subjects diagnosed with MS and the same number of healthy controls were analyzed. All patients received health management for 12 months and an impact evaluation was conducted. Results Waist circumference, IBM, SBP, DBP, blood lipids of MS group were remarkably higher than those in normal control group, and there was statistical significance (P

Randomization is one of the four basic principles of research design. The meaning of randomization includes two aspects: one is to randomly select samples from the population, which is known as random sampling; the other is to randomly group all the samples, which is called randomized grouping. Randomized grouping can be subdivided into three categories: completely, stratified and dynamically randomized grouping. This article mainly introduces the steps of complete randomization, the definition of dynamic randomization and the realization of random sampling and grouping by SAS software.

The control principle is one of the four basic principles of research design. Without a control group, the conclusion of research will be unconvincing; furthermore, if the control group is not set properly, the conclusion will be unreliable. Generally, there is more than one control group in a multi-factor design. Problems like incomplete control and excessive control should be avoided. This article introduces the meaning and function of the control principle, common forms of control, common errors that researchers tend to make as well as analysis and differentiation of these errors.

The repetition principle is important in scientific research, because the observational indexes are random variables, which require a certain amount of samples to reveal their changing regularity. The repetition principle stabilizes the mean and the standard variation, so that statistics of the sample can well represent the parameters of the population. Thus, the statistical inference will be reliable. This article discussed the repetition principle from the perspective of common sense and specialty with examples.

Scientific research design includes specialty design and statistics design which can be subdivided into experimental design, clinical trial design and survey design. Usually, statistics textbooks introduce the core aspects of experimental design as the three key elements, the four principles and the design types, which run through the whole scientific research design and determine the overall success of the research. This article discusses the principle of randomization, which is one of the four principles, and focuses on the following two issues--the definition and function of randomization and the real life examples which go against the randomization principle, thereby demonstrating that strict adherence to the randomization principle leads to meaningful and valuable scientific research.

Objective To evaluate the relationship between body mass index (BMI) and blood pressure,blood glucose,lipid profiles and blood uric acid in healthy populations in Hefei of Anhui province.Methods A total of 3 640 healthy adults were enrolled to analyze the relationship between BMI and blood pressure and serum levels of lipid profiles,uric acid and glucose.Results The mean BMI of the subjects was (25.5±2.8) kg/m2 (men vs women:(26.3±2.5) vs (23.9±2.8) kg/m2).BMI showed a significant difference in different age groups (P＜0.05).Different BMI subgroup had statistically significant difference in blood pressure,glucose,lipid profiles and uric acid.In different gender and age groups,BMI,blood pressure,glucose,blood lipid and uric acid were found to be significantly different.Conclusion The prevalence of obesity and overweight is high in our health check-up populations.It should be important to prevent and control hypertension,high blood glucose,high blood uric acid and other chronic diseases.

The principles of balance, randomization, control and repetition, which are closely related, constitute the four principles of scientific research. The balance principle is the kernel of the four principles which runs through the other three. However, in scientific research, the balance principle is always overlooked. If the balance principle is not well performed, the research conclusion is easy to be denied, which may lead to the failure of the whole research. Therefore, it is essential to have a good command of the balance principle in scientific research. This article stresses the definition and function of the balance principle, the strategies and detailed measures to improve balance in scientific research, and the analysis of the common mistakes involving the use of the balance principle in scientific research.