Selective immunisation strategy to protect newborns at risk for transmission of hepatitis B: retrospective audit of vaccine uptake

BACKGROUND: 90% of newborns infected perinatally will develop chronic hepatitis B infection with the risk of liver cirrhosis or hepatocellular carcinoma. In Switzerland, screening of all pregnant women for hepatitis B virus (HBV) has been recommended since 1983. Neonates at risk for perinatally acquired HBV are passively and actively immunised immediately after birth as well as at 1 and 6 months of age. The objective of this study was to evaluate the proportion of newborns immunised in accordance with the proposed vaccination schedule. METHODS: Patient records of 3997 mothers who gave birth to a liveborn infant during a two-year period at Zürich University Hospital were screened by computer. 128 women were identified as HBsAg positive or anti-HBc alone positive. Of 133 infants born to these mothers, complete data were available for 94 (71%). RESULTS: Immunisation was started in 88 infants (94%), but only in 78 (83%) within the first 24 hours of life. 85 (90%) received the 2nd immunisation but only 72 (77%) within the given time limit. 80 (85%) of the infants received the 3rd immunisation but only 69 (73%) within the correct time limit. In summary, only 51 (54%) of the infants at risk for HBV infection were immunised correctly (immunoglobulin within 24 hours and active prophylaxis at 0, 1 and 6 months). CONCLUSIONS: The success of the immunisation strategy following maternal screening and selective immunisation of newborns at risk for HBV infection is limited for various reasons (lack of screening results at birth, problems with correct documentation and communication). To overcome these drawbacks, selective vaccination strategy should be improved and general vaccination strategy, including infants, should be reconsidered.

Total-body digital X-ray in trauma. An experience report on the first operational full body scanner in Europe and its possible role in ATLS

When patients enter our emergency room with suspected multiple injuries, Statscan provides a full body anterior and lateral image for initial diagnosis, and then zooms in on specific smaller areas for a more detailed evaluation. In order to examine the possible role of Statscan in the management of multiply injured patients we implemented a modified ATLS((R)) algorithm, where X-ray of C-spine, chest and pelvis have been replaced by single-total a.p./lat. body radiograph. Between 15 October 2006 and 1 February 2007 143 trauma patients (mean ISS 15+/-14 (3-75)) were included. We compared the time in resuscitation room to 650 patients (mean ISS 14+/-14 (3-75)) which were treated between 1 January 2002 and 1 January 2004 according to conventional ATLS protocol. The total-body scanning time was 3.5 min (3-6 min) compared to 25.7 (8-48 min) for conventional X-rays, The total ER time was unchanged 28.7 min (13-58 min) compared to 29.1 min (15-65 min) using conventional plain radiography. In 116/143 patients additional CT scans were necessary. In 98/116 full body trauma CT scans were performed. In 18/116 patients selective CT scans were ordered based on Statscan findings. In 43/143 additional conventional X-rays had to be performed, mainly due to inadequate a.p. views of fractured bones. All radiographs were transmitted over the hospital network (Picture Archiving and Communication System, PACS) for immediate simultaneous viewing at different places. The rapid availability of images for interpretation because of their digital nature and the reduced need for repeat exposures because of faulty radiography are also felt to be strengths.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.