Transvaginal ultrasound cervical length for prediction of spontaneous labour at term: A systematic review and meta-analysis

BACKGROUND: The possibility to predict the delivery date is a question frequently raised by pregnant women. However, a clinician has currently little to predict when a woman at term will deliver. OBJECTIVE: To evaluate the predictive accuracy of transvaginal ultrasound (TVU) cervical length (CL) for spontaneous onset of labour in singleton gestation enrolled at term by a meta-analysis. SEARCH STRATEGY: We performed a literature search in electronic databases. SELECTION CRITERIA: We included only studies assessing the accuracy of TVU CL in prediction of spontaneous onset of labour in singleton gestations with vertex presentation who were enrolled at term. DATA COLLECTION AND ANALYSIS: The primary outcome was the accuracy of CL for prediction of spontaneous labour within 7 days. Pooled sensitivities and specificities were calculated. MAIN RESULTS: Five studies including 735 singleton gestations were included. For the prediction of spontaneous labour within 7 days for CL <30 mm the pooled sensitivity was 64% and pooled specificity was 60%. The higher the CL, the better the sensitivity; the lower the CL, the better the specificity. A woman with a singleton gestation at term and a TVU CL of 30 mm has a <50% chance of delivering within 7 days, while one with a TVU CL of 10 mm has an over 85% chance of delivery within 7 days. CONCLUSIONS: TVU CL at term has moderate value in predicting the onset of spontaneous labour. A woman with a TVU CL of 10 mm or less has a high chance of delivering within a week. TWEETABLE ABSTRACT: Cervical length at term has moderate value in predicting the onset of spontaneous labour

SUPPLY CHAIN COLLABORATION

MBA - WBSThe purpose of this project report was to develop a conceptual model that could be used to examine collaboration within its particular supply chain for the Web Printing industry. Although the model is based on literature not necessarily related to the Web Printing industry, it is suited for any industry that needs to improve collaboration within its supply chain. The findings from the research show that the industry in question can benefit by investigating the proposed model. For effective collaboration, information sharing is of cardinal importance. Respondents have indicated through the questionnaires that firstly, trust and commitment do not exist for all members in the supply chain. Access to information and on-line information in particular is limited. This affects much needed supply chain visibility that is vital for collaboration. Another important factor is the lack of an integrated information infrastructure to support information sharing. The industry’s access to technologies for improved supply chain collaboration is also a major factor impeding successful communication and thus collaboration within and across the supply chai

Management and performance of virtual and execution environments in FAIN

Next generation network nodes are required to function within heterogeneous network environments, where new services and protocols are rapidly deployed on demand. In such emerging environments, traditional node architectures that offer a predetermined and preloaded set of services, are increasingly incapable of coping with these new requirements. Accordingly, there is a need for new node architectures that offer higher degrees of flexibility measured by their capability to extend the functionality of the node and change its behaviour on demand. This paper makes use of programmable and active network technologies as developed during the FAIN project', to present a novel secure active node architecture, called the FAIN node architecture, capable of supporting virtual environments (VEs) for the allocation of the required amount of resources in which new services are dynamically deployed together with their entire execution environments (EEs). To this end, multiple VEs and services run simultaneously and interact securely with the node resources and mechanisms through open interfaces and the FAIN node management framework. We also present the implementation of the FAIN node architecture and two case studies that demonstrate its extensibility aspects and novel features