Default from tuberculosis treatment in Tashkent, Uzbekistan; Who are these defaulters and why do they default?

<p>Abstract</p> <p>Background</p> <p>In Tashkent (Uzbekistan), TB treatment is provided in accordance with the DOTS strategy. Of 1087 pulmonary TB patients started on treatment in 2005, 228 (21%) defaulted. This study investigates who the defaulters in Tashkent are, when they default and why they default.</p> <p>Methods</p> <p>We reviewed the records of 126 defaulters (cases) and 132 controls and collected information on time of default, demographic factors, social factors, potential risk factors for default, characteristics of treatment and recorded reasons for default.</p> <p>Results</p> <p>Unemployment, being a pensioner, alcoholism and homelessness were associated with default. Patients defaulted mostly during the intensive phase, while they were hospitalized (61%), or just before they were to start the continuation phase (26%). Reasons for default listed in the records were various, 'Refusal of further treatment' (27%) and 'Violation of hospital rules' (18%) were most frequently recorded. One third of the recorded defaulters did not really default but continued treatment under 'non-DOTS' conditions.</p> <p>Conclusion</p> <p>Whereas patient factors such as unemployment, being a pensioner, alcoholism and homelessness play a role, there are also system factors that need to be addressed to reduce default. Such system factors include the obligatory admission in TB hospitals and the inadequately organized transition from hospitalized to ambulatory treatment.</p

Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study

The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the deblooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis

Determining the neurotransmitter concentration profile at active synapses

Establishing the temporal and concentration profiles of neurotransmitters during synaptic release is an essential step towards understanding the basic properties of inter-neuronal communication in the central nervous system. A variety of ingenious attempts has been made to gain insights into this process, but the general inaccessibility of central synapses, intrinsic limitations of the techniques used, and natural variety of different synaptic environments have hindered a comprehensive description of this fundamental phenomenon. Here, we describe a number of experimental and theoretical findings that has been instrumental for advancing our knowledge of various features of neurotransmitter release, as well as newly developed tools that could overcome some limits of traditional pharmacological approaches and bring new impetus to the description of the complex mechanisms of synaptic transmission

Surgical Task Shifting in Sub-Saharan Africa

Kathryn Chu and colleagues discuss some of the experiences of surgical task shifting to date, and outline lessons from task shifting in the delivery of HIV/AIDS care

Brain age predicts mortality

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N = 2001), then tested in the Lothian Birth Cohort 1936 (N = 669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death