Clinical reporting following the quantification of cerebrospinal fluid biomarkers in Alzheimer's disease: An international overview

Introduction: The current practice of quantifying cerebrospinal fluid (CSF) biomarkers as an aid in the diagnosis of Alzheimer's disease (AD) varies from center to center. For a same biochemical profile, interpretation and reporting of results may differ, which can lead to misunderstandings and raises questions about the commutability of tests. Methods: We obtained a description of (pre-)analytical protocols and sample reports from 40 centers worldwide. A consensus approach allowed us to propose harmonized comments corresponding to the different CSF biomarker profiles observed in patients. Results: The (pre-)analytical procedures were similar between centers. There was considerable heterogeneity in cutoff definitions and report comments. We therefore identified and selected by consensus the most accurate and informative comments regarding the interpretation of CSF biomarkers in the context of AD diagnosis. Discussion: This is the first time that harmonized reports are proposed across worldwide specialized laboratories involved in the biochemical diagnosis of AD

SMARTEST - knowledge and learning repository

SMARTEST is a knowledge repository that assists and facilitates learning. It represents knowledge and learning activities as graphs, which present information in a clear, visual format that is easy to follow and understand. Nodes (coloured circles) contain content such as instructions or concepts relevant to the subject it is being used for; the lines connecting together two nodes (edges), show the relationship between them. Students can follow instructions using these graphs and visually see the links between the concepts or entities represented by the nodes. The nodes can then be colour-coded by students depending on their understanding of what that node represents. If a student has had difficulty understanding a particular concept, they can simply choose the colour that best represents their situation and level of understanding. This allows teachers to get clear feedback from students on specific parts of a subject and enable them to then help that student better understand the topic at hand. Furthermore, if several students are having a problem with a certain topic, this is communicated to the teacher and as a group the teacher can tackle the problem. There are two types of graphs: learning paths and ontologies. A learning path sets out steps for students to go through to acquire knowledge for their subject and build on the already acquired knowledge to complete the next steps. It allows students to see what steps they will need to take to achieve the final goal and creates a visual sense of accomplishment as students get closer and closer to the end of the learning path. An ontology is a set of concepts and categories in a subject area or domain that shows their properties and the relations between them. SMARTEST has been developed within a project undertaken at the University of Westminster and is sponsored by Quintin Hogg Trust