Inter-rater reliability of the Dysexecutive Questionnaire (DEX): comparative data from non-clinician respondents – all raters are not equal

Primary objective: The Dysexecutive Questionnaire (DEX) is used to obtain information about executive and emotional problems after neuropathology. The DEX is self-completed by the patient (DEX-S) and an independent rater such as a family member (DEX-I). This study examined the level of inter-rater agreement between either two or three non-clinician raters on the DEX-I in order to establish the reliability of DEX-I ratings. Methods and procedures: Family members and/or carers of 60 people with mixed neuropathology completed the DEX-I. For each patient, DEX-I ratings were obtained from either two or three raters who knew the person well prior to brain injury. Main outcomes and results: We obtained two independent-ratings for 60 patients and three independent-ratings for 36 patients. Intra-class correlations revealed that there was only a modest level of agreement for items, subscale and total DEX scores between raters for their particular family member. Several individual DEX items had low reliability and ratings for the emotion sub-scale had the lowest level of agreement. Conclusions: Independent DEX ratings completed by two or more non-clinician raters show only moderate correlation. Suggestions are made for improving the reliability of DEX-I ratings.</p

Multicentre evaluation of the Roche Elecsys® Active B12 (holotranscobalamin) electro-chemiluminescence immunoassay

Background: Vitamin B12 deficiency is a common disorder. In circulation, vitamin B12 is bound to transcobalamin (holotranscobalamin), which is considered the active form of cobalamin. The objective of this study was to evaluate the analytical performance of the Roche Elecsys Active B12 immunoassay. Methods: Limit of quantification and linearity were assessed according to CLSI EP17-A2 and EP-6A guidelines. Precision and bias of Roche Active B12 test against Architect ci8200 (Abbott) were performed according to CLSI EP-5 A3 guideline at three Euro

Fault diagnosis for uncertain networked systems

Fault diagnosis has been at the forefront of technological developments for several decades. Recent advances in many engineering fields have led to the networked interconnection of various systems. The increased complexity of modern systems leads to a larger number of sources of uncertainty which must be taken into consideration and addressed properly in the design of monitoring and fault diagnosis architectures. This chapter reviews a model-based distributed fault diagnosis approach for uncertain nonlinear large-scale networked systems to specifically address: (a) the presence of measurement noise by devising a filtering scheme for dampening the effect of noise; (b) the modeling of uncertainty by developing an adaptive learning scheme; (c) the uncertainty issues emerging when considering networked systems such as the presence of delays and packet dropouts in the communication networks. The proposed architecture considers in an integrated way the various components of complex distributed systems such as the physical environment, the sensor level, the fault diagnosers, and the communication networks. Finally, some actions taken after the detection of a fault, such as the identification of the fault location and its magnitude or the learning of the fault function, are illustrated

Seismic P Wave Velocity Model From 3‐D Surface and Borehole Seismic Data at the Alpine Fault DFDP‐2 Drill Site (Whataroa, New Zealand)

No description supplie