OBJECTIVE To explore the occurring characteristic and curing measures of hospital infection for inpatients with cardiovascular disease.METHODS The data of hospital infection for inpatients with cardiovascular disease from Jan to Dec,2004 were analyzed retrospectively.RESULTS The total incidence of hospital infection was 3.38% for inpatients with cardiovascular disease.The infection located as follows: 157 patients were in lower respiratory tract(48.2%);66 patients in upper respiratory tract(20.2%);40 patients in urinary tract(12.3%);33 patients in gastrointestinal tract(10.1%);and 18 patients were in cutis tissue ((5.5%).) CONCLUSIONS Pneumonia is one of the inducing factors to heart failure for patients with cardiovascular disease.Applying antibiotics reasonably,aseptic operation and treating the primary affection could decrease the incidence of hospital infection.

Retinol binding protein 4 (RBP4)was a class of secreting protein,mainly synthesized by the liver,widely distribu-ted in the human body blood,urine and other body fluids.It plays an important role in assisting the physiological function of vitamin A[1].Recent research shows that RBP4 was a new kind of adipocytokine,participated in insulin resistance and occur-rence of type 2 diabetes,and had a closed relationship with diabetic nephropathy,nutritional disease.This article describes the function of RBP4,review the relationship between RBP4 and nutritional or other type of diseases,and new clinical detec-tion method with RBP4.

In real world clinical studies,standardized data acquisition method is a key step in the formation of reliable clinical evidence.This article described how to carry out clinical data collection and how to preprocess data in order to ensure the quality of data.The results showed that from the data sources,data collection contents,collection key points,data description and evaluation,this paper put forward the method of collecting the real world data of traditional Chinese medicine (TCM).It was concluded that the standardized methods of clinical data acquisition had laid a solid foundation for real world research.

Objective:To analyze the epidemiological characteristics and pathogen spectrum of influenza outbreaks in Shaanxi Province from 2014 to 2023 and provide basis reference for strengthening regional influenza prevention and control.Methods:The data were collected from the Public Health Emergency Management Information System of the China Disease Prevention and Control Information System and the China Influenza Surveillance Information System. On-site epidemiological investigation information and etiological test results of influenza network laboratories reported in Shaanxi Province during 2014-2023 were collected, and descriptive analysis was conducted on the time, region, and location distribution of influenza outbreaks. SPSS 25.0 software was used for statistical analysis.Results:A total of 386 influenza outbreaks were reported in Shaanxi from 2014 to 2023, with a total attack rate of 1.81% (14 880/821 001). The epidemic peaks mainly occurred in winter and spring (November to March of the following year), and there was an alternating pattern of epidemic peaks in different years (the early peak was in December, and the late peak was in March of the following year). The epidemic areas were mainly concentrated in the Qinba Mountains of southern Shaanxi (209, 54.15%) and Guanzhong Plain (173, 44.82%). The epidemic places were mainly distributed in primary schools (239, 61.92%), and the differences of epidemic areas and places were statistically significant (all P<0.001). Influenza A(H3N2) viruses were the predominant pathogen in the outbreak (849, 57.76%), and influenza A(H3N2), B (Victoria) lineage and A(H1N1)pdm09 virus alternately dominated the epidemic peak in different years. Conclusions:The peak of influenza outbreaks in Shaanxi Province was winter and spring during 2014-2023. Primary schools in the Qinba Mountains of southern Shaanxi and Guanzhong Plain should be targeted for prevention and control. In the prevention and control programs, close attention should be paid to the changing trend of dominant strains. Effective intervention measures should be targeted to the high-incidence areas and seasons.