Can mental health diagnoses in administrative data be used for research? A systematic review of the accuracy of routinely collected diagnoses

BACKGROUND: There is increasing availability of data derived from diagnoses made routinely in mental health care, and interest in using these for research. Such data will be subject to both diagnostic (clinical) error and administrative error, and so it is necessary to evaluate its accuracy against a reference-standard. Our aim was to review studies where this had been done to guide the use of other available data. METHODS: We searched PubMed and EMBASE for studies comparing routinely collected mental health diagnosis data to a reference standard. We produced diagnostic category-specific positive predictive values (PPV) and Cohen’s kappa for each study. RESULTS: We found 39 eligible studies. Studies were heterogeneous in design, with a wide range of outcomes. Administrative error was small compared to diagnostic error. PPV was related to base rate of the respective condition, with overall median of 76 %. Kappa results on average showed a moderate agreement between source data and reference standard for most diagnostic categories (median kappa = 0.45–0.55); anxiety disorders and schizoaffective disorder showed poorer agreement. There was no significant benefit in accuracy for diagnoses made in inpatients. CONCLUSIONS: The current evidence partly answered our questions. There was wide variation in the quality of source data, with a risk of publication bias. For some diagnoses, especially psychotic categories, administrative data were generally predictive of true diagnosis. For others, such as anxiety disorders, the data were less satisfactory. We discuss the implications of our findings, and the need for researchers to validate routine diagnostic data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12888-016-0963-x) contains supplementary material, which is available to authorized users

A genomic selection strategy to identify accessible and dimerization blocking targets in the 5′-UTR of HIV-1 RNA

Defining target sites for antisense oligonucleotides in highly structured RNA is a non-trivial exercise that has received much attention. Here we describe a novel and simple method to generate a library composed of all 20mer oligoribonucleotides that are sense- and antisense to any given sequence or genome and apply the method to the highly structured HIV-1 leader RNA. Oligoribonucleotides that interact strongly with folded HIV-1 RNA and potentially inhibit its dimerization were identified through iterative rounds of affinity selection by native gel electrophoresis. We identified five distinct regions in the HIV-1 RNA that were particularly prone to antisense annealing and a structural comparison between these sites suggested that the 3′-end of the antisense RNA preferentially interacts with single-stranded loops in the target RNA, whereas the 5′-end binds within double-stranded regions. The selected RNA species and corresponding DNA oligonucleotides were assayed for HIV-1 RNA binding, ability to block reverse transcription and/or potential to interfere with dimerization. All the selected oligonucleotides bound rapidly and strongly to the HIV-1 leader RNA in vitro and one oligonucleotide was capable of disrupting RNA dimers efficiently. The library selection methodology we describe here is rapid, inexpensive and generally applicable to any other RNA or RNP complex. The length of the oligonucleotide in the library is similar to antisense molecules generally applied in vivo and therefore likely to define targets relevant for HIV-1 therapy

A numerical method for pricing European options with proportional transaction costs

In the paper,we propose a numerical technique based on a finite difference scheme in space and an implicit time-stepping scheme for solving the Hamilton–Jacobi–Bellman (HJB) equation arising from the penalty formulation of the valuation ofEuropean options with proportional transaction costs. We show that the approximate solution from the numerical scheme converges to the viscosity solution of the HJB equation as the mesh sizes in space and time approach zero. We also propose an iterative scheme for solving the nonlinear algebraic system arising from the discretization and establish a convergence theory for the iterative scheme. Numerical experiments are presented to demonstrate the robustness and accuracy of the method