Predicting the incidence risk of ischemic stroke in a hospital population of southern China: a classification tree analysis.

OBJECTIVE: To determine the major risk factors and their interactions of ischemic stroke (IS) and to develop a classification tree model to predict the incidence risk of IS for a Chinese population. METHODS: Exhaustive Chi-squared Automatic Interaction Detection (Exhaustive CHAID) algorithm of classification tree method was applied to build a prediction model for the incidence risk of IS under the design of 1:1 matched case-control study. The statistics of misclassification risk was used to evaluate the fitness of the model. RESULTS: In the prediction model, six variables of physical exercise, history of hypertension, tea drinking, HDL-c level, smoking status and educational level were in turn selected as the predictors of IS incidence risk. In the subgroup of lacking of physical exercise, individuals who had history of hypertension would have a significantly higher IS risk (92%) than that of the ones who had no history of hypertension (64%). The misclassification risk estimate of the prediction model was 0.21 with the standard error of 0.02, indicating that 79% of the cases could be classified correctly based on current prediction model. CONCLUSIONS: Lacking of physical exercise and history of hypertension are identified to be the prominent predicting variables of IS risk for a hospital population of southern China. Although CHAID analysis could provide detailed information and insight about interactions among risk factors of IS, we still need to validate our model and improve the vascular risk prediction for Chinese subjects in further studies.

Ventilator-associated pneumonia in intensive care units in Hubei Province, China: a multicentre prospective cohort survey.

A multicentre prospective cohort study was performed in 17 intensive care units (ICUs) in tertiary care hospitals in Hubei Province, China. Ventilator-associated pneumonia (VAP) was defined according to modified criteria from the published literature. Among 4155 ventilated patients, the crude incidence and incidence rate of VAP were 20.9% and 28.9 cases per 1000 ventilator-days. Multivariate analysis using logistic regression revealed risk factors including male sex [risk ratio (RR): 1.5; P<0.001], coma (RR: 2.1; P<0.001), chronic obstructive pulmonary disease (RR: 1.4; P<0.001), infections at other sites (RR: 1.6; P=0.001), serious disease predating the onset of VAP (RR: 1.6; P<0.001) and interventions including antacid treatment (RR: 1.4; P<0.001), antimicrobial treatment (RR: 5.1; P<0.001), bronchoscopy (RR: 1.5; P=0.041) and tracheostomy (RR: 1.4; P=0.014). The most frequently isolated causative pathogens were Pseudomonas aeruginosa and Acinetobacter baumannii. Of all Staphylococcus aureus isolates, 45.7% were meticillin resistant. Rates, risk factors and causal pathogens of VAP in ICUs in Hubei differ from those reported from developed countries. These data show the need for more effective infection control interventions in Hubei, China.

Point prevalence surveys of healthcare-associated infection in 13 hospitals in Hubei Province, China, 2007-2008.

Successive point prevalence surveys were conducted in November 2007 and 2008 to monitor the prevalence of healthcare-associated infection (HCAI) in 13 grade III, 1st class hospitals in Hubei Province of China, using the case definition criteria established by the Ministry of Health in the People's Republic of China. In total, of 20 350 patients surveyed, 833 (4.09%) HCAIs were observed in 790 (3.88%) patients. There was no significant difference between the overall prevalence of HCAI in 2007 (4.14%) and 2008 (3.72%). Respiratory tract infection was the most common HCAI (63.15%), followed by surgical site infection (9.60%) and urinary tract infection (8.64%). Only 35.29% (294/833) of HCAI patients had positive microbiology results. Gram-negative bacteria were isolated most frequently and the most frequent organism was Pseudomonas aeruginosa, followed by Escherichia coli, Acinetobacter baumannii and Staphylococcus aureus. Antibiotic use was documented for 10,344 (50.83%) patients, and cephalosporins, penicillins, and quinolones were the most commonly used agents for treatment or prophylaxis.

[Application of complex networks model in preventing and controlling communicable disease].

To discuss the application of complex networks models in preventing and controlling communicable disease, analyze and control the spread of infectious diseases by using the models and the software of complex networks based on its basic properties. Compared with conventional epidemiological approach, the complex networks theory, as a new theory, not only can describe the dynamic process of infections diseases spreading but also forecast the situation of infectious disease. The influence of the network's topology on the infections diseases transmission can be deeply understood through the research on disease spreading by its theory, so to control the spread of diseases. Complex networks theory approach can be used in epidemiological research for having much advantage compared with those conventional epidemiological approaches.