Assessment of FUS-200 Performance: Comparison with Quantitative Urine Culture Shows that Identifying the Right Cutoff for Optimizing Analyzer Performance Is Challenging.

BACKGROUND: Urine sediment analysis is a frequently ordered test, since it permits screening for many clinical conditions. Here, the technical and bacteriuria diagnostic performance of FUS-200, a new sediment analyzer, was assessed. METHODS: Carry-over, imprecision, and linearity were measured according to CLSI protocols. FUS-200 was compared to sediMAX™, our current laboratory analyzer, in terms of particle recognition/counting in 382 fresh urine samples, and bacteriuria diagnosis was based on white blood cell (WBC) and bacteria counts in a subgroup of the same samples. In the diagnostic study, quantitative bacterial cultures served to classify the samples as bacteria-positive or bacteria-negative. RESULTS: FUS-200 did not show carryover for the particles tested. Total imprecision for red blood cells (RBCs) and WBCs in positive controls was 3.6%-10.5% and complied with European guidelines. RBC and WBC recovery was linear. When FUS-200 particle counts were edited by a reviewer, concordance with sediMAX improved for epithelial cells, yeast, and crystals, and recognition of casts and crystals improved. FUS-200 concordance with sediMAX varied between 97% for yeast and 58% for bacteria and was satisfactory. FUS-200 detected bacteriuria better than sediMAX (P = 0.004). FUS-200 WBC and bacteria cutoff values based on the Youden index detected bacteriuria better than manufacturer cutoffs. The best sensitivity with which FUS-200 detected bacteriuria was 79%. CONCLUSIONS: Although casts and crystal recognition should be improved, the overall technical performance of FUS-200 was acceptable to good. FUS-200 exhibited good screening accuracy for bacteria and WBC. Editing only mildly influenced FUS-200 outcomes.

NodeTrix: a hybrid visualization of social networks.

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily resolve the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections to and from node-link and matrix forms, and to flexibly manipulate the NodeTrix representation to explore the dataset and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results.

MatrixExplorer: a dual-representation system to explore social networks.

MatrixExplorer is a network visualization system that uses two representations: node-link diagrams and matrices. Its design comes from a list of requirements formalized after several interviews and a participatory design session conducted with social science researchers. Although matrices are commonly used in social networks analysis, very few systems support the matrix-based representations to visualize and analyze networks. MatrixExplorer provides several novel features to support the exploration of social networks with a matrix-based representation, in addition to the standard interactive filtering and clustering functions. It provides tools to reorder (layout) matrices, to annotate and compare findings across different layouts and find consensus among several clusterings. MatrixExplorer also supports Node-link diagram views which are familiar to most users and remain a convenient way to publish or communicate exploration results. Matrix and node-link representations are kept synchronized at all stages of the exploration process.