The clinical value of new diagnostic tools for tuberculosis

Barriers to global tuberculosis (TB) control include multidrug resistance, HIV infection, and weak health systems. Case detection is critical to TB control and is affected by all three of these. Currently, most low- and middle-income countries (LMICs) rely on direct sputum smear microscopy for diagnosis. Modern culture methods and molecular tests, previously considered too complex or too expensive for implementation in LMICs, are now being introduced there in parallel with a global effort to strengthen laboratories. It remains to be seen whether services based on these tools can be made widely accessible to patients. New point-of-care tests for TB are urgently needed but cannot be expected in the near future. In the meantime, diagnostic tools based on optimized smear microscopy, although less sensitive than reference laboratory tests, may be more accessible and have more impact on case finding. It is a matter of urgency that these improved microscopy services be integrated with services based on rapid methods that can identify multidrug-resistant cases

Twin Peaks - The Legal and Regulatory Anatomy of Australia's System of Financial Regulation

Australia adopts a functionally-based model – the ‘twin peaks’ model – under which the functions for financial regulation are consolidated into two regulators: the Australian Securities and Investments Commission (ASIC), which is responsible for the regulation of companies, market conduct and consumer protection; and the Australian Prudential Regulation Authority (APRA), which is responsible for prudential regulation. This paper examines the anatomy of the Australian twin peaks model from a legal and regulatory perspective. It also reflects on the work of the Financial System Inquiry (FSI) of 2014, which reviewed Australia’s financial system and examined issues that are relevant to the operation of the twin peaks model

The rapid structured literature review as a research strategy

A diversity of sources of literature encompassed by the management disciplines appears to result in a growing need for a systematic methodology to map the territory of management theory. As such, when scoping out a study, structured literature review (SLR) can be considered as a means by which any critical, central literature might be considered. However, there is little guidance, or evidence, of this being undertaken for the purposes of small scale projects such as undergraduate or masters’ dissertations. This paper reports four case studies of master’s degree students following management programmes of undertaking a structured literature review (SLR) and the issues and problems they had to encounter during their journey. The findings from the case studies suggest that in terms of time to complete and the volume of output required in terms of word count, Tranfield, et al’s approach to SLRs, whilst suited to doctoral level research is not appropriate generally when dealing with undergraduate and masters research projects. Therefore, this paper provides accounts of the experiences of four students who undertook SLR for their undergraduate or master’s degree dissertation. The paper identifies that these students had to deal with a new set of conceptual problems relating to this “unorthodox” approach to a postgraduate research dissertation in coming to terms with new paradigms of enquiry that are not normally taught as part of a traditional research methods course. This was despite gaining a greater depth of insight into the subject area through a more rigorous and structured manner. The paper presents alternative remedies by way of a rapid structured literature review (RSLR) model. This would appear to be more appropriate to the conducting of small scale literature based research projects when used with undergraduate and master’s degree students than SLR identified for other research activities

User-centered design in brain–computer interfaces — a case study

The array of available brain–computer interface (BCI) paradigms has continued to grow, and so has the corresponding set of machine learning methods which are at the core of BCI systems. The latter have evolved to provide more robust data analysis solutions, and as a consequence the proportion of healthy BCI users who can use a BCI successfully is growing. With this development the chances have increased that the needs and abilities of specific patients, the end-users, can be covered by an existing BCI approach. However, most end-users who have experienced the use of a BCI system at all have encountered a single paradigm only. This paradigm is typically the one that is being tested in the study that the end-user happens to be enrolled in, along with other end-users. Though this corresponds to the preferred study arrangement for basic research, it does not ensure that the end-user experiences a working BCI. In this study, a different approach was taken; that of a user-centered design. It is the prevailing process in traditional assistive technology. Given an individual user with a particular clinical profile, several available BCI approaches are tested and – if necessary – adapted to him/her until a suitable BCI system is found

Relative effectiveness of robot-assisted and standard laparoscopic prostatectomy as alternatives to open radical prostatectomy for treatment of localised prostate cancer : a systematic review and mixed treatment comparison meta-analysis

© 2013 The Authors. BJU International © 2013 BJU International.Peer reviewedPublisher PD

Discriminating nursery grounds of juvenile plaice (Pleuronectes platessa) in the south-eastern Irish Sea using otolith microchemistry

Nursery grounds are valuable habitats providing sources of food and refuge during early life stages for many commercially caught marine fish. Distinguishing between different nursery grounds and identifying habitat origin using trace elemental concentrations in aragonite structures of teleost fish has proved valuable in fish ecology and fisheries. This study aimed to (1) compare chemical signatures (elemental fingerprints) within sagittal otoliths of juvenile European plaice Pleuronectes platessa sampled from known nursery habitats in the south-eastern Irish Sea and (2) assess their potential and robustness as natural tags for identifying nursery grounds for the putative south-eastern Irish Sea plaice stock. Otoliths from juvenile plaice (‘1-group’, 6 to 15 cm total length) were obtained from 8 nursery grounds in coastal areas off north-west England and north Wales (including Anglesey) between June and August 2008. Solution-based inductively coupled plasma-mass spectrometry determined the concentrations of 10 elements (Li, Na, Mg, K, Mn, Zn, Rb, Sr, Sn, Ba), with significant differences in otolith element composition observed between all nursery grounds. Cross-validation linear discriminant function analysis (CV-LDFA) classified fish to their nursery ground of capture (46.2 to 93.3%), with a total group CV-LDFA accuracy of 71.0%. CV-LDFA between regions (north-west England and north Wales) classified fish with 82% accuracy. The discrimination of juvenile plaice from all 8 nursery grounds within the south-eastern Irish Sea using otolith microchemistry offers significant opportunities in the development of future effective fisheries management strategies through understanding the supply of juveniles from specific nursery grounds and adult plaice in the south-eastern Irish Sea

Assessment of the learning curve in health technologies: a systematic review

Objective: We reviewed and appraised the methods by which the issue of the learning curve has been addressed during health technology assessment in the past. Method: We performed a systematic review of papers in clinical databases (BIOSIS, CINAHL, Cochrane Library, EMBASE, HealthSTAR, MEDLINE, Science Citation Index, and Social Science Citation Index) using the search term "learning curve:" Results: The clinical search retrieved 4,571 abstracts for assessment, of which 559 (12%) published articles were eligible for review. Of these, 272 were judged to have formally assessed a learning curve. The procedures assessed were minimal access (51%), other surgical (41%), and diagnostic (8%). The majority of the studies were case series (95%). Some 47% of studies addressed only individual operator performance and 52% addressed institutional performance. The data were collected prospectively in 40%, retrospectively in 26%, and the method was unclear for 31%. The statistical methods used were simple graphs (44%), splitting the data chronologically and performing a t test or chi-squared test (60%), curve fitting (12%), and other model fitting (5%). Conclusions: Learning curves are rarely considered formally in health technology assessment. Where they are, the reporting of the studies and the statistical methods used are weak. As a minimum, reporting of learning should include the number and experience of the operators and a detailed description of data collection. Improved statistical methods would enhance the assessment of health technologies that require learning

Assessing the learning curve effect in health technologies: Lessons from the non-clinical literature

Introduction: Many health technologies exhibit some form of learning effect, and this represents a barrier to rigorous assessment. It has been shown that the statistical methods used are relatively crude. Methods to describe learning curves in fields outside medicine, for example, psychology and engineering, may be better. Methods: To systematically search non–health technology assessment literature (for example, PsycLit and Econlit databases) to identify novel statistical techniques applied to learning curves. Results: The search retrieved 9,431 abstracts for assessment, of which 18 used a statistical technique for analyzing learning effects that had not previously been identified in the clinical literature. The newly identified methods were combined with those previously used in health technology assessment, and categorized into four groups of increasing complexity: a) exploratory data analysis; b) simple data analysis; c) complex data analysis; and d) generic methods. All the complex structured data techniques for analyzing learning effects were identified in the nonclinical literature, and these emphasized the importance of estimating intra- and interindividual learning effects. Conclusion: A good dividend of more sophisticated methods was obtained by searching in nonclinical fields. These methods now require formal testing on health technology data sets