ALBERT

Description: Background The prevalence of risk factors for poor outcomes from aneurysmal subarachnoid hemorrhage (SAH) varies widely and has not been fully elucidated to date in Vietnam. Understanding the risk and prognosis of aneurysmal SAH is important to reduce poor outcomes in Vietnam. The aim of this study, therefore, was to investigate the rate of poor outcome at 90 days of ictus and associated factors from aneurysmal SAH in the country. Methods We performed a multicenter prospective cohort study of patients (≥18 years) presenting with aneurysmal SAH to three central hospitals in Hanoi, Vietnam, from August 2019 to August 2020. We collected data on the characteristics, management, and outcomes of patients with aneurysmal SAH and compared these data between good (defined as modified Rankin Scale (mRS) of 0 to 3) and poor (mRS, 4–6) outcomes at 90 days of ictus. We assessed factors associated with poor outcomes using logistic regression analysis. Results Of 168 patients with aneurysmal SAH, 77/168 (45.8%) were men, and the median age was 57 years (IQR: 48–67). Up to 57/168 (33.9%) of these patients had poor outcomes at 90 days of ictus. Most patients underwent sudden-onset and severe headache (87.5%; 147/168) and were transferred from local to participating central hospitals (80.4%, 135/168), over half (57.1%, 92/161) of whom arrived in central hospitals after 24 hours of ictus, and the initial median World Federation of Neurological Surgeons (WFNS) grading score was 2 (IQR: 1–4). Nearly half of the patients (47.0%; 79/168) were treated with endovascular coiling, 37.5% (63/168) were treated with surgical clipping, the remaining patients (15.5%; 26/168) did not receive aneurysm repair, and late rebleeding and delayed cerebral ischemia (DCI) occurred in 6.1% (10/164) and 10.4% (17/163) of patients, respectively. An initial WFNS grade of IV (odds ratio, OR: 15.285; 95% confidence interval, CI: 3.096–75.466) and a grade of V (OR: 162.965; 95% CI: 9.975–2662.318) were independently associated with poor outcomes. Additionally, both endovascular coiling (OR: 0.033; 95% CI: 0.005–0.235) and surgical clipping (OR: 0.046; 95% CI: 0.006–0.370) were inversely and independently associated with poor outcome. Late rebleeding (OR: 97.624; 95% CI: 5.653–1686.010) and DCI (OR: 15.209; 95% CI: 2.321–99.673) were also independently associated with poor outcome. Conclusions Improvements are needed in the management of aneurysmal SAH in Vietnam, such as increasing the number of aneurysm repairs, performing earlier aneurysm treatment by surgical clipping or endovascular coiling, and improving both aneurysm repairs and neurocritical care.

Description: Black pepper is an industrial crop with high economic and export value. However, black pepper production in Vietnam has been seriously affected by the root-knot nematodes, Meloidogyne spp. The purpose of this study was to select active endophytic bacteria (EB) for the cost-effective and environmentally friendly management of Meloidogyne sp. Thirty-four EB strains were isolated. Of these, five isolates displayed the highest activity, demonstrating 100% mortality of J2 nematodes. These active EB were identified based on sequencing and phylogenetic analysis of the 16S rRNA gene; notably, all the potential endophytic bacterial strains belong to the genus of Bacillus. In greenhouse tests, Bacillus megaterium DS9 significantly reduced nematodes in the soil and pepper plant roots with great inhibition values of 81.86% and 73.11%, respectively, with the lowest rate of nematodes built up at 0.23. This active antinematodes strain also showed good effect on promoting pepper plant growth. Some enzymatic activities, including chitinase and protease activity related to the biocontrol of Meiloidogyne sp., were also detected. The results investigated in the current study suggested that these selected EB strains may be good candidates for biocontrol agents of Meloidogyne sp., and plant promoting effects. The results also enhanced the novel active antinematode endophytic bacterial communities.

Description: Road traffic injuries (RTIs) cause a substantial disease burden in Vietnam. Evaluating health-related quality of life (HRQOL) among patients having a diversity of RTIs informs an integral part of treatment effectiveness. This study aims to examine HRQOL of patients suffering different RTIs in Vietnam’s urban areas. A cross-sectional study was conducted on 408 patients from October to December 2018 in six hospitals in Thai Binh. The EuroQol-5 dimensions-5 levels (EQ-5D-5L) and visual analog scale (VAS) were used to assess the HRQOL of patients. Multivariable Tobit regression was applied to measure the difference of HRQOL among different kinds of injuries. The mean EQ-5D-5L and VAS score was 0.40–0.66, respectively. Mean EQ-5D-5L index was lowest in patients with oral and facial injuries (0.22) and fracture injuries (0.23), while patients having hand injuries had the highest EQ-5D-5L index (0.54). EQ-5D-5L index had a negative association with oral, facial, and fracture injuries. Meanwhile, patients with brain, fracture, and multiple injuries tended to have lower VAS score. Poor HRQOL among patients injured in road traffic were observed. Pain management, early rehabilitation, and mental health counseling services should be considered during treatment time, especially among those having the brain, oral and facial trauma, fracture, and multiple injuries.

Description: In recent years, the amount of intelligent CCTV cameras installed in public places for surveillance has increased enormously and as a result, a large amount of video data is produced every moment. Due to this situation, there is an increasing request for the distributed processing of large-scale video data. In an intelligent video analytics platform, a submitted unstructured video undergoes through several multidisciplinary algorithms with the aim of extracting insights and making them searchable and understandable for both human and machine. Video analytics have applications ranging from surveillance to video content management. In this context, various industrial and scholarly solutions exist. However, most of the existing solutions rely on a traditional client/server framework to perform face and object recognition while lacking the support for more complex application scenarios. Furthermore, these frameworks are rarely handled in a scalable manner using distributed computing. Besides, existing works do not provide any support for low-level distributed video processing APIs (Application Programming Interfaces). They also failed to address a complete service-oriented ecosystem to meet the growing demands of consumers, researchers and developers. In order to overcome these issues, in this paper, we propose a distributed video analytics framework for intelligent video surveillance known as SIAT. The proposed framework is able to process both the real-time video streams and batch video analytics. Each real-time stream also corresponds to batch processing data. Hence, this work correlates with the symmetry concept. Furthermore, we introduce a distributed video processing library on top of Spark. SIAT exploits state-of-the-art distributed computing technologies with the aim to ensure scalability, effectiveness and fault-tolerance. Lastly, we implant and evaluate our proposed framework with the goal to authenticate our claims.