Search

Background. Flow diversion (FD) has become a widely adopted treatment method for intracranial aneurysms in the clinic, but a comprehensive meta-analysis of large-sample studies including anterior and posterior circulation is still lacking. Methods. The PubMed, Embase, Web of Science, and Cochrane databases were searched between January 1, 2008, and December 1, 2019. A random-effect model was used to calculate the efficacy and safety data as well as 95% confidence intervals (CIs). Results. The pooled sample size of all included studies was 6695 patients; the mean age was 55.5 years old, with a total of 7406 aneurysms. For efficacy, the complete occlusion rate in angiographic follow-up (AFU) at 6 months was 78% (95% CI, 0.77, 0.80), and the AFU rate at 6-12 months was 90% (95% CI, 0.88, 0.92). For safety, the hemorrhagic event rate was 2%, the ischemic event rate was 5%, and the mortality rate was 3%. Conclusion. FD is an effective and safe treatment for intracranial aneurysm with high complete occlusion rate and acceptable complication rate.

This study proposes a new method to describe, compare, and classify the traffic congestion states in 23 Chinese cities using the online map data and further reveals the influential factors that may affect them. First, the real-time traffic congestion information is obtained from the online map of AutoNavi in a 15-minute interval. Next, a new measuring index is introduced to describe the overall characterization of congestion patterns in each city based on online map data, which is named as the congestion ratio. The next analysis is the cluster analysis based on the temporal distribution of the congestion ratio, which helps to identify groups of the selected cities with similar traffic congestion states. These cities are categorized as four groups according to the severity of traffic congestion: severely congested, less severely congested, amble, and smooth cities. Lastly, multiple linear regression models are developed to identify the primary factors that affect the congestion ratio. The result shows that the influences of per capita road area, car ownership, and vehicle miles traveled (VMT) on the congestion ratio are significant. Sensitivity analyses are also implemented in order to reveal more effective policy measures in mitigating traffic congestion in urban areas.