Objectives Through analyzing the published scientific papers by the professionals of the Center for Disease Control and Prevention of Guangdong Province(GDCDC) from 2001 to 2006,to put forward some suggestions for the research management,the discipline development and the personnel training.Methods Literature quantitative analysis and health statistics methods were used to analyze these papers.Results The professionals of GDCDC published a total of 924 papers with an annual average of 154 in 114 kinds of periodicals from 2001 to 2006 of the 924 papers.264 papers(28.6%) were published in the key Chinese periodicals,320 papers(34.6%)in the South China Journal of Preventive Medicine,68 papers (7.4%)in the Chinese Journal of Health Laboratory Technology and 51 papers(5.5%)in the China Public Health.Of the 924 papers,433 papers(46.9%)belonged in the field of health laboratory technology,354 papers(38.3%)in the field of disease prevention and control,and 70 papers(7.6%)in the field of public health.During the six years,79.2% of the total professionals Published at least one paper,58professionals published at least six papers.Of the 924 corresponding authors.56.8% aged 30～40 years old.48.9% had a bachelor degree,and 45.9% had a senior professional title.Conclusions In recent years,the quantity and quality of papers published by the professionals of GDCDC were improved.The professional's ability to conduct scientific research was enhanced and the research level of GDCDC wag raised year by year.The predominant specialties of the academic research were in the field of health laboratory technology and disease prevention and control.But the professional work and discipline development of Public health should be sirengthened further.

Based on the principle of Joinpoint regression (JPR) model and the additivity of Poisson distribution, this paper constructed a JPR model for series cumulative data. The notifiable incidence number of dengue fever cases per week and weekly cumulative data in Guangdong province from 2008 to 2017 were analyzed, using (mean squared errors) MSE and (mean absolute percentage error) MAPE to evaluate different models. Except for 2015, the MSE and MAPE produced from the logarithmic linear JPR model based on weekly cumulative incidence number were smaller than those based on the weekly data. The fitting accuracy of JPR model for series cumulative data for trend analysis had been improved significantly. This model could be applied to the analysis of the trend change and the prediction of staged cumulative incidence.

OBJECTIVE: To explore the application and the effect of early recognition of deteriorating patient program in department of cardiac surgery. METHODS: We used the early recognition of deteriorating patient program in the cardiac surgery groups, including cardiac surgeons, nurses in ward, ICU and operation rooms of the cardiac surgery department, and compared the satisfaction of nurses and doctors, handover time, handover score of critical patients, and rate of unplanned ICU admission before and after the intervention. RESULTS: After using the early recognition of deteriorating patient program, the satisfaction of doctors and nurses was increased, the handover time was lowered 0.56 min/time (t=2.22, P<0.05), the handover score of critical patients enhanced by 19.59 points (t=30.57, P<0.001), the rate of unplanned ICU readmission after the operation reduced by 4.8% (χ2=4.14, P<0.05). CONCLUSION Early recognition of deteriorating patient program can improve the safety of cardiac patients, enhance the self-confidence of nurses and work efficiency.
Cardiology Service, Hospital ; organization & administration ; Critical Illness ; Humans ; Intensive Care Units ; Outcome and Process Assessment, Health Care ; Patient Handoff ; Surgery Department, Hospital ; organization & administration

Based on the principle of Joinpoint regression (JPR) model and the additivity of Poisson distribution, this paper constructed a JPR model for series cumulative data. The notifiable incidence number of dengue fever cases per week and weekly cumulative data in Guangdong province from 2008 to 2017 were analyzed, using (mean squared errors) MSE and (mean absolute percentage error) MAPE to evaluate different models. Except for 2015, the MSE and MAPE produced from the logarithmic linear JPR model based on weekly cumulative incidence number were smaller than those based on the weekly data. The fitting accuracy of JPR model for series cumulative data for trend analysis had been improved significantly. This model could be applied to the analysis of the trend change and the prediction of staged cumulative incidence.

Based on the principle of Joinpoint regression (JPR) model and the additivity of Poisson distribution, this paper constructed a JPR model for series cumulative data. The notifiable incidence number of dengue fever cases per week and weekly cumulative data in Guangdong province from 2008 to 2017 were analyzed, using (mean squared errors) MSE and (mean absolute percentage error) MAPE to evaluate different models. Except for 2015, the MSE and MAPE produced from the logarithmic linear JPR model based on weekly cumulative incidence number were smaller than those based on the weekly data. The fitting accuracy of JPR model for series cumulative data for trend analysis had been improved significantly. This model could be applied to the analysis of the trend change and the prediction of staged cumulative incidence.

Objective To study the probability distribution of Mosquito ovitrap Index(MOI)risk of dengue Aedes vector,so as to provide a new method for more scientific and accurate MOI risk assessment.Methods Cubic spline function,cumulative probability distribution and python language programming were used to fit and analyze the MOI surveillance data of Guangzhou from 2016 to 2019 years.Results The probability distribution table and distribution figure of MOI risk assessment in Guangzhou from January to December were developed.From January to December,the MOI critical values were 7.54～60.12 and 5.05～34.10 with a cumulative probability less than 0.01 or 0.05 respectively.The critical value was the lowest in January,followed by December and February.The highest was in June,followed by May and July.From January to December,the probabilities of MOI risk grade of transmission,outbreak and epidemic were 5.07%～66.60%,0.25%～36.19%and 0.00%～16.80%respectively.The lowest risk probability of transmission,outbreak and epidemic occurred in January,followed by February respectively.The highest risk probability values appeared in July,July and June,followed by June,June and May respectively.Conclusion The probability distribution of MOI risk in each month in Guangzhou had significant seasonal growth and decline laws and characteristics,which were worthy of attention in the monitoring,evaluation and control of dengue Aedes vector.It provided a new analysis method for MOI risk assessment fitting based on cubic spline functions and cumulative probability distribution.

Cancer is the most cause death of among adolescents and young adults (AYAs).Psychological distress caused by cancer affects AYAs' effective coping abilities of disease,physical symptoms and treatment.This paper mainly introduces the related concepts,screening tools and intervention progress of psychological distress of AYAs cancer patients to deepen the understanding of these among clinical professionals and provide reference for implement effective interventions to patients.