Geometric View of Measurement Errors

The slope of the best fit line from minimizing the sum of the squared oblique errors is the root of a polynomial of degree four. This geometric view of measurement errors is used to give insight into the performance of various slope estimators for the measurement error model including an adjusted fourth moment estimator introduced by Gillard and Iles (2005) to remove the jump discontinuity in the estimator of Copas (1972). The polynomial of degree four is associated with a minimun deviation estimator. A simulation study compares these estimators showing improvement in bias and mean squared error

Beyond Diagnostic Accuracy: The Clinical Utility of Diagnostic Tests

Like any other medical technology or intervention, diagnostic tests should be thoroughly evaluated before their introduction into daily practice. Increasingly, decision makers, physicians, and other users of diagnostic tests request more than simple measures of a test's analytical or technical performance and diagnostic accuracy; they would also like to see testing lead to health benefits. In this last article of our series, we introduce the notion of clinical utility, which expresses-preferably in a quantitative form-to what extent diagnostic testing improves health outcomes relative to the current best alternative, which could be some other form of testing or no testing at all. In most cases, diagnostic tests improve patient outcomes by providing information that can be used to identify patients who will benefit from helpful downstream management actions, such as effective treatment in individuals with positive test results and no treatment for those with negative results. We describe how comparative randomized clinical trials can be used to estimate clinical utility. We contrast the definition of clinical utility with that of the personal utility of tests and markers. We show how diagnostic accuracy can be linked to clinical utility through an appropriate definition of the target condition in diagnostic-accuracy studies. (C) 2012 American Association for Clinical Chemistr

Perspectives on reasons for suicidal behaviour and recommendations for suicide prevention in Kenya: qualitative study

Background: Little is known about the reasons for suicidal behaviour in Africa, and communities’ perception of suicide prevention. A contextualised understanding of these reasons is important in guiding the implementation of potential suicide prevention interventions in specific settings. Aims: To understand ideas, experiences and opinions on reasons contributing to suicidal behaviour in the Coast region of Kenya, and provide recommendations for suicide prevention. Method: We conducted a qualitative study with various groups of key informants residing in the Coast region of Kenya, using in-depth interviews. Audio-recorded interviews were transcribed and translated from the local language before thematic inductive content analysis. Results: From the 25 in-depth interviews, we identified four key themes as reasons given for suicidal behaviour: interpersonal and relationship problems, financial and economic difficulties, mental health conditions and religious and cultural influences. These reasons were observed to be interrelated with each other and well-aligned to the suggested recommendations for suicide prevention. We found six key recommendations from our thematic content analysis: (a) increasing access to counselling and social support, (b) improving mental health awareness and skills training, (c) restriction of suicide means, (d) decriminalisation of suicide, (e) economic and education empowerment and (f) encouraging religion and spirituality. Conclusions: The reasons for suicidal behaviour are comparable with high-income countries, but suggested prevention strategies are more contextualised to our setting. A multifaceted approach in preventing suicide in (coastal) Kenya is warranted based on the varied reasons suggested. Community-based interventions will likely improve and increase access to suicide prevention in this study area

Estimation of the Optimal Statistical Quality Control Sampling Time Intervals Using a Residual Risk Measure

Background: An open problem in clinical chemistry is the estimation of the optimal sampling time intervals for the application of statistical quality control (QC) procedures that are based on the measurement of control materials. This is a probabilistic risk assessment problem that requires reliability analysis of the analytical system, and the estimation of the risk caused by the measurement error. Methodology/Principal Findings: Assuming that the states of the analytical system are the reliability state, the maintenance state, the critical-failure modes and their combinations, we can define risk functions based on the mean time of the states, their measurement error and the medically acceptable measurement error. Consequently, a residual risk measure rr can be defined for each sampling time interval. The rr depends on the state probability vectors of the analytical system, the state transition probability matrices before and after each application of the QC procedure and the state mean time matrices. As optimal sampling time intervals can be defined those minimizing a QC related cost measure while the rr is acceptable. I developed an algorithm that estimates the rr for any QC sampling time interval of a QC procedure applied to analytical systems with an arbitrary number of critical-failure modes, assuming any failure time and measurement error probability density function for each mode. Furthermore, given the acceptable rr, it can estimate the optimal QC sampling time intervals

Velocity tuning of friction with two trapped atoms

Our ability to control friction remains modest, as our understanding of the underlying microscopic processes is incomplete. Atomic force experiments have provided a wealth of results on the dependence of nanofriction on structure velocity and temperature but limitations in the dynamic range, time resolution, and control at the single-atom level have hampered a description from first principles. Here, using an ion-crystal system with single-atom, single-substrate-site spatial and single-slip temporal resolution we measure the friction force over nearly five orders of magnitude in velocity, and contiguously observe four distinct regimes, while controlling temperature and dissipation. We elucidate the interplay between thermal and structural lubricity for two coupled atoms, and provide a simple explanation in terms of the Peierls–Nabarro potential. This extensive control at the atomic scale enables fundamental studies of the interaction of many-atom surfaces, possibly into the quantum regime

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the dopamine D-2 receptor occupancy of olanzapine in rats

A mechanism-based PK-PD model was developed to predict the time course of dopamine D-2 receptor occupancy (D2RO) in rat striatum following administration of olanzapine, an atypical antipsychotic drug. A population approach was utilized to quantify both the pharmacokinetics and pharmacodynamics of olanzapine in rats using the exposure (plasma and brain concentration) and D2RO profile obtained experimentally at various doses (0.01-40 mg/kg) administered by different routes. A two-compartment pharmacokinetic model was used to describe the plasma pharmacokinetic profile. A hybrid physiology- and mechanism-based model was developed to characterize the D-2 receptor binding in the striatum and was fitted sequentially to the data. The parameters were estimated using nonlinear mixed-effects modeling . Plasma, brain concentration profiles and time course of D2RO were well described by the model; validity of the proposed model is supported by good agreement between estimated association and dissociation rate constants and in vitro values from literature. This model includes both receptor binding kinetics and pharmacokinetics as the basis for the prediction of the D2RO in rats. Moreover, this modeling framework can be applied to scale the in vitro and preclinical information to clinical receptor occupancy

Analytical bias in the measurement of serum 25-hydroxyvitamin D concentrations impairs assessment of vitamin D status in clinical and research settings

Measured serum 25-hydroxyvitamin D concentrations vary depending on the type of assay used and the specific laboratory undertaking the analysis, impairing the accurate assessment of vitamin D status. We investigated differences in serum 25-hydroxyvitamin D concentrations measured at three laboratories (laboratories A and B using an assay based on liquid chromatography-tandem mass spectrometry and laboratory C using a DiaSorin Liaison assay), against a laboratory using an assay based on liquid chromatography-tandem mass spectrometry that is certified to the standard reference method developed by the National Institute of Standards and Technology and Ghent University (referred to as the ‘ certified laboratory ’ ). Separate aliquots from the same original serum sample for a subset of 50 participants from the Ausimmune Study were analysed at the four laboratories. Bland-Altman plots were used to visually check agreement between each laboratory against the certified laboratory. Compared with the certified laboratory, serum 25-hydroxyvitamin D concentrations were on average 12.4 nmol/L higher at laboratory A (95% limits of agreement: -17 .8,42.6); 12.8 nmol/L higher at laboratory B (95% limits of agreement: 0.8,24.8); and 10.6 nmol/L lower at laboratory C (95% limits of agreement: -48.4,27.1). The prevalence of vitamin D deficiency (defined here as 25-hydroxyvitamin D < 50 nmol/L) was 24%, 16%, 12% and 41% at the certified laboratory, and laboratories A, B, and C, respectively. Our results demonstrate considerable differences in the measurement of 25-hydroxyvitamin D concentrations compared with a certified laboratory, even between laboratories using assays based on liquid chromatography-tandem mass spectrometry, which is often considered the gold-standard assay. To ensure accurate and reliable measurement of serum 25-hydroxyvitamin D concentrations, all laboratories should use an accuracy-based quality assurance system and, ideally, comply with international standardisation effort

Effects of low birth weight, maternal smoking in pregnancy and social class on the phenotypic manifestation of Attention Deficit Hyperactivity Disorder and associated antisocial behaviour: investigation in a clinical sample

<p>Abstract</p> <p>Background</p> <p>Attention Deficit Hyperactivity Disorder (ADHD) is a genetically influenced condition although indicators of environmental risk including maternal smoking during pregnancy, low birth weight and low social class have also been found to be associated with the disorder.</p> <p>ADHD is a phenotypically heterogeneous disorder in terms of the predominant symptom types (inattention, hyperactive-impulsivity), their severity and comorbidity, notably Conduct Disorder. It is possible that these different clinical manifestations of the disorder may arise because of the differing effects of the environmental indicators of environmental risk. We set out to test this hypothesis.</p> <p>Methods</p> <p>In a sample of 356 children diagnosed with ADHD, we sought to investigate possible effects of three indicators of environmental risk – maternal smoking during pregnancy, birth weight and social class – on comorbid Conduct Disorder, conduct disorder symptoms and inattentive and hyperactive-impulsive symptom severity.</p> <p>Results</p> <p>Multiple regression analysis revealed that, after controlling for significant covariates, greater hyperactive-impulsive symptom severity was significantly associated with maternal smoking during pregnancy (r²= 0.02, Beta = 0.11, t = 1.96, p = 0.05) and social class (r²= 0.02, Beta = 0.12, t = 2.19, p = 0.03) whilst none of the environmental risk indicators significantly predicted number of inattentive symptoms. Conduct Disorder symptoms were positively predicted by maternal smoking in pregnancy (r²= 0.04, Beta = 0.18, t = 3.34, p = 0.001) whilst both maternal smoking during pregnancy and social class significantly predicted a diagnosis of Conduct Disorder (OR = 3.14, 95% CI: 1.54, 6.41, Wald = 9.95, p = 0.002) and (OR = 1.95 95% CI: 1.18, 3.23 Wald = 6.78, p = 0.009) respectively.</p> <p>Conclusion</p> <p>These findings suggest that indicators of environmental risk, in this instance maternal smoking in pregnancy and environmental adversity indexed by lower social class, independently influence the clinical presentation of the ADHD phenotype. Other types of study design are needed to investigate whether these associations between indicators of environmental risk factors and ADHD clinical heterogeneity are attributable to causal risk effects and to further establish the magnitude of these effects. These findings have implications, not only for our understanding of the aetiology of ADHD, but may also be of clinical value, enabling the identification of individuals who are at higher risk of problematic behaviours in ADHD, notably conduct disorder, to enable earlier, targeted risk reduction strategies.</p