The Patient Health Questionnaire-9 for detection of major depressive disorder in primary care: consequences of current thresholds in a crosssectional study

<p>Abstract</p> <p>Background</p> <p>There is a need for brief instruments to ascertain the diagnosis of major depressive disorder. In this study, we present the reliability, construct validity and accuracy of the PHQ-9 and PHQ-2 to detect major depressive disorder in primary care.</p> <p>Methods</p> <p>Cross-sectional analyses within a large prospective cohort study (PREDICT-NL). Data was collected in seven large general practices in the centre of the Netherlands. 1338 subjects were recruited in the general practice waiting room, irrespective of their presenting complaint. The diagnostic accuracy (the area under the ROC curve and sensitivities and specificities for various thresholds) was calculated against a diagnosis of major depressive disorder determined with the Composite International Diagnostic Interview (CIDI).</p> <p>Results</p> <p>The PHQ-9 showed a high degree of internal consistency (ICC = 0.88) and test-retest reliability (correlation = 0.94). With respect to construct validity, it showed a clear association with functional status measurements, sick days and number of consultations. The discriminative ability was good for the PHQ-9 (area under the ROC curve = 0.87, 95% CI: 0.84-0.90) and the PHQ-2 (ROC area = 0.83, 95% CI 0.80-0.87). Sensitivities at the recommended thresholds were 0.49 for the PHQ-9 at a score of 10 and 0.28 for a categorical algorithm. Adjustment of the threshold and the algorithm improved sensitivities to 0.82 and 0.84 respectively but the specificity decreased from 0.95 to 0.82 (threshold) and from 0.98 to 0.81 (algorithm). Similar results were found for the PHQ-2: the recommended threshold of 3 had a sensitivity of 0.42 and lowering the threshold resulted in an improved sensitivity of 0.81.</p> <p>Conclusion</p> <p>The PHQ-9 and the PHQ-2 are useful instruments to detect major depressive disorder in primary care, provided a high score is followed by an additional diagnostic work-up. However, often recommended thresholds for the PHQ-9 and the PHQ-2 resulted in many undetected major depressive disorders.</p

Distances and ages of globular clusters using Hipparcos parallaxes of local subdwarfs

We discuss the impact of Population II and Globular Cluster (GCs) stars on the derivation of the age of the Universe, and on the study of the formation and early evolution of galaxies, our own in particular. The long-standing problem of the actual distance scale to Population II stars and GCs is addressed, and a variety of different methods commonly used to derive distances to Population II stars are briefly reviewed. Emphasis is given to the discussion of distances and ages for GCs derived using Hipparcos parallaxes of local subdwarfs. Results obtained by different authors are slightly different, depending on different assumptions about metallicity scale, reddenings, and corrections for undetected binaries. These and other uncertainties present in the method are discussed. Finally, we outline progress expected in the near future.Comment: Invited review article to appear in: `Post-Hipparcos Cosmic Candles', A. Heck & F. Caputo (Eds), Kluwer Academic Publ., Dordrecht, in press. 22 pages including 3 tables and 2 postscript figures, uses Kluwer's crckapb.sty LaTeX style file, enclose

Robust averaging protects decisions from noise in neural computations

An ideal observer will give equivalent weight to sources of information that are equally reliable. However, when averaging visual information, human observers tend to downweight or discount features that are relatively outlying or deviant (‘robust averaging’). Why humans adopt an integration policy that discards important decision information remains unknown. Here, observers were asked to judge the average tilt in a circular array of high-contrast gratings, relative to an orientation boundary defined by a central reference grating. Observers showed robust averaging of orientation, but the extent to which they did so was a positive predictor of their overall performance. Using computational simulations, we show that although robust averaging is suboptimal for a perfect integrator, it paradoxically enhances performance in the presence of “late” noise, i.e. which corrupts decisions during integration. In other words, robust decision strategies increase the brain’s resilience to noise arising in neural computations during decision-making

The Formation and Evolution of the First Massive Black Holes

The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

Five years post whiplash injury: Symptoms and psychological factors in recovered versus non-recovered

<p>Abstract</p> <p>Background</p> <p>Few studies have focused on the differences between persons who are recovered after whiplash injury and those who suffer from persistent disability. The primary aim of this study was therefore to examine differences in symptoms, psychological factors and life satisfaction between subjects classified as recovered and those with persistent disability five years after whiplash injury based on the Neck Disability Index (NDI).</p> <p>Methods</p> <p>A set of questionnaires was answered by 158 persons (75 men, 83 women) to assess disability (NDI), pain intensity (VAS), whiplash-related symptoms (Rivermead Post-Concussion Symptoms Questionnaire, RPQ), post-traumatic stress (Impact of Event Scale, IES), depression (Beck's depression inventory, BDI) and life satisfaction (LiSat-11).</p> <p>The participants were divided into three groups based on the results of the NDI: recovered (34.8%), mild disability (37.3%) and moderate/severe disability (27.3%).</p> <p>Results</p> <p>The moderate/severe group reported significantly higher VAS, BDI and IES scores and lower level of physical health and psychological health compared to the mild and the recovered groups. Less significant differences were reported between the mild and the recovered groups.</p> <p>Conclusions</p> <p>The group with the highest disability score reported most health problems with pain, symptoms, depression, post-traumatic stress and decreased life satisfaction. These findings indicate that classifying these subjects into subgroups based on disability levels makes it possible to optimize the management and treatment after whiplash injury.</p

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants

BACKGROUND: Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. METHODS: A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. RESULTS: CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0–1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. CONCLUSION: State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide

Monitoring Community Pharmacist's Quality of Care: A feasibility study of using pharmacy claims data to assess performance

Contains fulltext : 98109.pdf (publisher's version ) (Open Access)BACKGROUND: Public pressure has increasingly emphasized the need to ensure the continuing quality of care provided by health professionals over their careers. Health profession's regulatory authorities, mandated to be publicly accountable for safe and effective care, are revising their quality assurance programs to focus on regular evaluations of practitioner performance. New methods for routine screening of performance are required and the use of administrative data for measuring performance on quality of care indicators has been suggested as one attractive option. Preliminary studies have shown that community pharmacy claims databases contain the information required to operationalize quality of care indicators. The purpose of this project was to determine the feasibility of routine use of information from these databases by regulatory authorities to screen the quality of care provided at community pharmacies. METHODS: Information from the Canadian province of Quebec's medication insurance program provided data on prescriptions dispensed in 2002 by more than 5000 pharmacists in 1799 community pharmacies. Pharmacy-specific performance rates were calculated on four quality of care indicators: two safety indicators (dispensing of contra-indicated benzodiazepines to seniors and dispensing of nonselective beta-blockers to patients with respiratory disease) and two effectiveness indicators (dispensing asthma or hypertension medications to non-compliant patients). Descriptive statistics were used to summarize performance. RESULTS: Reliable estimates of performance could be obtained for more than 90% of pharmacies. The average rate of dispensing was 4.3% (range 0 - 42.5%) for contra-indicated benzodiazepines, 15.2% (range 0 - 100%) for nonselective beta-blockers to respiratory patients, 10.7% (range 0 - 70%) for hypertension medications to noncompliant patients, and 43.3% (0 - 91.6%) for short-acting beta-agonists in over-use situations. There were modest correlations in performance across the four indicators. Nine pharmacies (0.5%) performed in the lowest quartile in all four of the indicators, and 5.3% (n = 95) performed in the lowest quartile on three of four indicators. CONCLUSIONS: Routinely collected pharmacy claims data can be used to monitor indicators of the quality of care provided in community pharmacies, and may be useful in future to identify underperforming pharmacists, measure the impact of policy changes and determine predictors of best practices

Herding QATs: Quality Assessment Tools for Evidence in Medicine

Medical scientists employ ‘quality assessment tools’ (QATs) to measure the quality of evidence from clinical studies, especially randomized controlled trials (RCTs). These tools are designed to take into account various methodological details of clinical studies, including randomization, blinding, and other features of studies deemed relevant to minimizing bias and error. There are now dozens available. The various QATs on offer differ widely from each other, and second-order empirical studies show that QATs have low inter-rater reliability and low inter-tool reliability. This is an instance of a more general problem I call the underdetermination of evidential significance. Disagreements about the strength of a particular piece of evidence can be due to different—but in principle equally good—weightings of the fine-grained methodological features which constitute QATs

Does neurocognitive training have the potential to improve dietary self-care in type 2 diabetes? Study protocol of a double blind randomised controlled trial

Dietary self-care is a key element of self-management in type 2 diabetes. It is also the most difficult aspect of diabetes self-management. Adhering to long-term dietary goals and resisting immediate food desires requires top-down inhibitory control over subcortical impulsive and emotional responses to food. Practising simple neurocognitive tasks can improve inhibitory control and health behaviours that depend on inhibitory control, such as resisting alcohol consumption. It is yet to be investigated, however, whether neurocognitive training can improve dietary self-care in people with type 2 diabetes. The aim of this randomised controlled trial is to investigate whether web-based neurocognitive training can improve the ability of people with type 2 diabetes to resist tempting foods and better adhere to a healthy dietary regime