The Impact of Frailty on Adverse Outcomes in Geriatric Hip Fracture Patients: A Systematic Review and Meta-Analysis.

Objective: With an aging population and advances in medicine, more research focuses on health and longevity in geriatric adults. Recently, frailty has gradually emerged to assess physical conditions. Frailty can be generally described as a multi-dimensional situation of increased vulnerabilities to both endogenous and exogenous stressors. The objective of the review was to evaluate the predictive value of frailty on adverse outcomes in geriatric hip fracture patients. Materials and Methods: We searched PubMed, Embase, Web of Science, and the Cochrane library for relevant literature about the connection between frailty and poor outcomes in hip fracture elders. Results: Eleven studies involving a total of 45,979 participants were selected in our study. Our results indicated that frailty could significantly predict postoperative and in-patient complications (OR, 1.46; 95% CI, 1.13-1.90; I2 = 77.4%). Frail elders had higher risk of inpatient mortality (OR, 1.68; 95% CI, 1.26-2.25; I2 = 0.0%), 6-month mortality (OR, 1.46; 95% CI, 1.25-1.72; I2 = 0.0%) and ≥1-year mortality (OR, 2.24; 95% CI, 1.66-3.04; I2 = 91.3%). Furthermore, the risk of prolonged hospital stays was 1.15 times more likely in frail patients (95% CI, 1.03-1.28; I2 = 14.8%). Conclusion: Frailty can predict adverse outcomes effectively in geriatric hip fracture patients. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/#recordDetails.

Analysis and Synthesis of Traffic Scenes from Road Image Sequences.

Traffic scene construction and simulation has been a hot topic in the community of intelligent transportation systems. In this paper, we propose a novel framework for the analysis and synthesis of traffic elements from road image sequences. The proposed framework is composed of three stages: traffic elements detection, road scene inpainting, and road scene reconstruction. First, a new bidirectional single shot multi-box detector (BiSSD) method is designed with a global context attention mechanism for traffic elements detection. After the detection of traffic elements, an unsupervised CycleGAN is applied to inpaint the occlusion regions with optical flow. The high-quality inpainting images are then obtained by the proposed image inpainting algorithm. Finally, a traffic scene simulation method is developed by integrating the foreground and background elements of traffic scenes. The extensive experiments and comparisons demonstrate the effectiveness of the proposed framework.