Performance of HBsAg point-of-care tests for detection of diagnostic escape-variants in clinical samples

BACKGROUND Hepatitis B viruses (HBV) harboring mutations in the a-determinant of the Hepatitis B surface antigen (HBsAg) are associated with reduced reactivity of HBsAg assays. OBJECTIVES To evaluate the sensitivity and specificity of three HBsAg point-of-care tests for the detection of HBsAg of viruses harboring HBsAg mutations. STUDY DESIGN A selection of 50 clinical plasma samples containing HBV with HBsAg mutations was used to evaluate the performance of three HBsAg point-of-care tests (Vikia(®), bioMérieux, Marcy-L'Étoile, France. Alere Determine HBsAg™, Iverness Biomedical Innovations, Köln, Germany. Quick Profile™, LumiQuick Diagnostics, California, USA) and compared to the ARCHITECT HBsAg Qualitative(®) assay (Abbott Laboratories, Sligo, Ireland). RESULTS The sensitivity of the point-of-care tests ranged from 98% to 100%. The only false-negative result occurred using the Quick Profile™ assay with a virus harboring a D144A mutation. CONCLUSIONS The evaluated point-of-care tests revealed an excellent sensitivity in detecting HBV samples harboring HBsAg mutations.

Reliability of Quantitative Sensory Tests in a Low Back Pain Population.

BACKGROUND AND OBJECTIVES Reliability is an essential condition for using quantitative sensory tests (QSTs) in research and clinical practice, but information on reliability in patients with chronic pain is sparse. The aim of this study was to evaluate the reliability of different QST in patients with chronic low back pain. METHODS Eighty-nine patients with chronic low back pain participated in 2 identical experimental sessions, separated by at least 7 days. The following parameters were recorded: pressure pain detection and tolerance thresholds at the toe, electrical pain thresholds to single and repeated stimulation, heat pain detection and tolerance thresholds at the arm and leg, cold pain detection threshold at the arm and leg, and conditioned pain modulation using the cold pressor test.Reliability was analyzed using the coefficient of variation, the coefficient of repeatability, and the intraclass correlation coefficient. It was judged as acceptable or not based primarily on the analysis of the coefficient of repeatability. RESULTS The reliability of most tests was acceptable. Exceptions were cold pain detection thresholds at the leg and arm. CONCLUSIONS Most QST measurements have acceptable reliability in patients with chronic low back pain.

Quantum Nondemolition Measurement Enables Macroscopic Leggett-Garg Tests

We show how a test of macroscopic realism based on Leggett-Garg inequalities (LGIs) can be performed in a macroscopic system. Using a continuous-variable approach, we consider quantum nondemolition (QND) measurements applied to atomic ensembles undergoing magnetically driven coherent oscillation. We identify measurement schemes requiring only Gaussian states as inputs and giving a significant LGI violation with realistic experimental parameters and imperfections. The predicted violation is shown to be due to true quantum effects rather than to a classical invasivity of the measurement. Using QND measurements to tighten the “clumsiness loophole” forces the stubborn macrorealist to recreate quantum backaction in his or her account of measurement.

Confidence Bands for Isotonic Median Curves using Sign-Tests

Suppose that one observes independent random variables (X1, Y1), (X2, Y2), …, (Xn, Yn) in R2 with unknown distributions, except that Median(Yi | Xi = M(x) for some unknown isotonic function M. We describe an explicit algorithm for the computation of confidence bands for the median function M whose running time is of order O(n2). The bands rely on multiscale sign tests and are shown to have desirable asymptotic properties.

Application of Local Rank Tests for Nonparametric Regression

Let Y_i = f(x_i) + E_i\ (1\le i\le n) with given covariates x_1\lt x_2\lt \cdots\lt x_n , an unknown regression function f and independent random errors E_i with median zero. It is shown how to apply several linear rank test statistics simultaneously in order to test monotonicity of f in various regions and to identify its local extrema.

Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension

BACKGROUND The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established. AIMS To assess diagnostic accuracy of six serum scores, artificial neural networks and liver stiffness measured by transient elastography, for diagnosing cirrhosis, clinically significant portal hypertension and oesophageal varices. METHODS 202 consecutive compensated patients requiring liver biopsy and hepatic venous pressure gradient measurement were included. Several serum tests (alone and combined into scores) and liver stiffness were measured. Artificial neural networks containing or not liver stiffness as input variable were also created. RESULTS The best non-invasive method for diagnosing cirrhosis, portal hypertension and oesophageal varices was liver stiffness (C-statistics=0.93, 0.94, and 0.90, respectively). Among serum tests/scores the best for diagnosing cirrhosis and portal hypertension and oesophageal varices were, respectively, Fibrosis-4, and Lok score. Artificial neural networks including liver stiffness had high diagnostic performance for cirrhosis, portal hypertension and oesophageal varices (accuracy>80%), but were not statistically superior to liver stiffness alone. CONCLUSIONS Liver stiffness was the best non-invasive method to assess the presence of cirrhosis, portal hypertension and oesophageal varices. The use of artificial neural networks integrating different non-invasive tests did not increase the diagnostic accuracy of liver stiffness alone.