Bmc Med
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Over the last 100 years, several persistent misconceptions or 'false beliefs' have built up around allergen immunotherapy and its use in allergic rhinitis. This is perhaps because enthusiastic physicians administered complex allergen extracts to a diverse population of patients suffering from heterogeneous atopic conditions. Here, we review evidence that counters seven of these 'false beliefs.' ⋯ Modern, evidence-based medicine has generated more than enough robust evidence to remove misconceptions about allergen immunotherapy and allergic rhinitis.
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Review
Management of HIV-associated tuberculosis in resource-limited settings: a state-of-the-art review.
The HIV-associated tuberculosis (TB) epidemic remains a huge challenge to public health in resource-limited settings. Reducing the nearly 0.5 million deaths that result each year has been identified as a key priority. Major progress has been made over the past 10 years in defining appropriate strategies and policy guidelines for early diagnosis and effective case management. ⋯ ART reduces mortality across a spectrum of CD4 counts and randomized controlled trials have defined the optimum time to start ART. Good outcomes can be achieved when combining TB treatment with first-line ART, but use with second-line ART remains challenging due to pharmacokinetic drug interactions and cotoxicity. We review the frequency and spectrum of adverse drug reactions and immune reconstitution inflammatory syndrome (IRIS) resulting from combined treatment, and highlight the challenges of managing HIV-associated drug-resistant TB.
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The HIV integrase inhibitor, Dolutegravir (DTG), was recently approved by the Food and Drug Administration in the United States and is the only HIV drug that has not selected for resistance mutations in the clinic when used as part of first-line therapy. This has led to speculation that DTG might have a higher genetic barrier for the development of drug resistance than the other compounds that are used in therapy. ⋯ DTG is a valuable addition to the anti-HIV armamentarium of drugs and its long-term utility may potentially exceed its obvious use in treatment of HIV disease.
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Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. ⋯ Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, 'dark matter' and 'dark energy' are posited to balance various theoretical equations, so medical student selection must also have its 'dark variance', whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills.
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Most UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training. ⋯ This collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general.