Comparative radiological features of disseminated disease due to Mycobacterium tuberculosis vs non-tuberculosis mycobacteria among AIDS patients in Brazil

Background: Disseminated mycobacterial disease is an important cause of morbidity and mortality in patients with HIV-infection. Nonspecific clinical presentation makes the diagnosis difficult and sometimes neglected. Methods: We conducted a retrospective cohort study to compare the presentation of disseminated Mycobacterial tuberculosis (MTB) and non-tuberculous Mycobacterial (NTM) disease in HIV-positive patients from 1996 to 2006 in Brazil. Results: Tuberculosis (TB) was diagnosed in 65 patients (67.7%) and NTM in 31 (32.3%) patients. Patients with NTM had lower CD4 T cells counts (median 13.0 cells/mm3 versus 42.0 cells/mm3, P = 0.002). Patients with tuberculosis had significantly more positive acid-fast smears (48.0% vs 13.6%, P = 0.01). On chest X-ray, miliary infiltrate was only seen in patients with MTB (28.1% vs. 0.0%, P = 0.01). Pleural effusion was more common in patients with MTB (45.6% vs. 13.0%, P = 0.01). Abdominal adenopathy (73.1% vs. 33.3%, P = 0.003) and splenic hypoechoic nodules (38.5% vs. 0.0%, P = 0.002) were more common in patients with TB. Conclusion: Miliary pulmonary pattern on X-ray, pleural effusion, abdominal adenopathy, and splenic hypoechoic nodules were imaging findings associated with the diagnosis of tuberculosis in HIV-infected patients. Recognition of these imaging features will help to distinguish TB from NTM in AIDS patients with fever of unknown origin due to disseminated mycobacterial disease

Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies

<p>Abstract</p> <p>Background</p> <p>Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP), the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling.</p> <p>Methods</p> <p>We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error.</p> <p>Results</p> <p>The model identified three major factors that influence sampling strategies: (1) the clustering of episodes in individuals; (2) the duration of episodes; (3) the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year) often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates.</p> <p>Conclusion</p> <p>Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid and cost-effective.</p

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination ‘as a public health problem’ when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models’ predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Does Time Since Immigration Modify Neighborhood Deprivation Gradients in Preterm Birth? A Multilevel Analysis

Immigrants’ health is jointly influenced by their pre- and post-migration exposures, but how these two influences operate with increasing duration of residence has not been well-researched. We aimed to examine how the influence of maternal country of birth and neighborhood deprivation effects, if any, change over time since migration and how neighborhood effects among immigrants compare with those observed in the Canadian-born population. Birth data from Ontario hospital records (2002–2007) were linked with an official Canadian immigration database (1985–2000). The outcome measure was preterm birth. Neighborhoods were ranked according to a neighborhood deprivation index developed for Canadian urban areas and collapsed into tertiles of approximately equal size. Time since immigration was measured from the date of arrival to Canada to the date of delivery, ranging from 1 to 22 years. We used cross-classified random effect models to simultaneously account for the membership of births (N = 83,233) to urban neighborhoods (N = 1,801) and maternal countries of birth (N = 168). There were no differences in preterm birth between neighborhood deprivation tertiles among immigrants with less than 15 years of residence. Among immigrants with 15 years of stay or more, the adjusted absolute risk difference (ARD%, 95% confidence interval) between high-deprived (tertile 3) and low-deprived (tertile 1) neighborhoods was 1.86 (0.68, 2.98), while the ARD% observed among the Canadian-born (N = 314,237) was 1.34 (1.11, 1.57). Time since migration modifies the neighborhood deprivation gradient in preterm birth among immigrants living in Ontario cities. Immigrants reached the level of inequalities in preterm birth observed at the neighborhood level among the Canadian-born after 14 years of stay, but neighborhoods did not influence preterm birth among more recent immigrants, for whom the maternal country of birth was more predictive of preterm birth

Linear low-dose extrapolation for noncancer health effects is the exception, not the rule

The nature of the exposure-response relationship has a profound influence on risk analyses. Several arguments have been proffered as to why all exposure-response relationships for both cancer and noncarcinogenic end-points should be assumed to be linear at low doses. We focused on three arguments that have been put forth for noncarcinogens. First, the general “additivity-to-background” argument proposes that if an agent enhances an already existing disease-causing process, then even small exposures increase disease incidence in a linear manner. This only holds if it is related to a specific mode of action that has nonuniversal properties—properties that would not be expected for most noncancer effects. Second, the “heterogeneity in the population” argument states that variations in sensitivity among members ofthe target population tend to “flatten out and linearize” the exposure-response curve, but this actually only tends to broaden, not linearize, the dose-response relationship. Third, it has been argued that a review of epidemiological evidence shows linear or no-threshold effects at low exposures in humans, despite nonlinear exposure-response in the experimental dose range in animal testing for similar endpoints. It is more likely that this is attributable to exposure measurement error rather than a true non-threshold association. Assuming that every chemical is toxic at high exposures and linear at low exposures does not comport to modern-day scientific knowledge of biology. There is no compelling evidence-based justification for a general low-exposure linearity; rather, case-specific mechanistic arguments are needed

Acute myeloid leukemia of donor origin after allogeneic stem cell transplantation from a sibling who harbors germline XPD and XRCC3 homozygous polymorphisms

A 54-year-old woman was diagnosed with infiltrative ductal breast carcinoma. Two years after treatment, the patient developed an acute myeloid leukemia (AML) which harbored del(11q23) in 8% of the blast cells. The patient was submitted for allogeneic stem cell transplantation (aSCT) from her HLA-compatible sister. Ten months after transplantation, she relapsed with an AML with basophilic maturation characterized by CD45low CD33high, CD117+, CD13-/+, HLA Drhigh, CD123high, and CD203c+ blast cells lacking expression of CD7, CD10, CD34, CD15, CD14, CD56, CD36, CD64, and cytoplasmic tryptase. Karyotype analysis showed the emergence of a new clone with t(2;14) and FISH analysis indicated the presence of MLL gene rearrangement consistent with del(11q23). Interestingly, AML blast cell DNA tested with microsatellite markers showed the same pattern as the donor's, suggesting that this AML emerged from donor cells. Additionally, polymorphisms of the XPA, XPD, XRCC1, XRCC3 and RAD51 DNA repair genes revealed three unfavorable alleles with low DNA repair capacity