Publications by authors named "B E Abdelbary"

Article Synopsis
  • The All of Us Research Program wants to create a huge and diverse database for medical research that scientists can easily use through a special platform called the Researcher Workbench (RW).
  • Researchers with different levels of experience helped design a new tool called SAS by sharing their ideas and testing it out.
  • The feedback from these researchers was super helpful in making the SAS tool better, which means more people can use the All of Us data easily and effectively in their studies.
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The Mexican state of Tamaulipas serves as a migration waypoint into the US. Here, we determined the contribution of immigrants to TB burden in Tamaulipas. TB surveillance data from Tamaulipas (2006-2013) was used to conduct a cross-sectional characterization of TB immigrants (born outside Tamaulipas) and identify their association with TB treatment outcomes.

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We investigated the distribution of comorbidities among adult tuberculosis (TB) patients in Chiapas, the poorest Mexican state, with a high presence of indigenous population, and a corridor for migrants from Latin America. Secondary analysis on 5508 new adult TB patients diagnosed between 2010 and 2014 revealed that the most prevalent comorbidities were diabetes mellitus (DM; 19.1%) and undernutrition (14.

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Type 2 diabetes (T2D) is a prevalent risk factor for tuberculosis (TB), but most studies on TB-T2D have focused on TB patients, been limited to one community, and shown a variable impact of T2D on TB risk or treatment outcomes. We conducted a cross-sectional assessment of sociodemographic and metabolic factors in adult TB contacts with T2D (versus no T2D), from the Texas-Mexico border to study Hispanics, and in Cape Town to study South African Coloured ethnicities. The prevalence of T2D was 30.

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The purpose of this study was to develop a method for identifying newly diagnosed tuberculosis (TB) patients at risk for TB adverse events in Tamaulipas, Mexico. Surveillance data between 2006 and 2013 (8431 subjects) was used to develop risk scores based on predictive modelling. The final models revealed that TB patients failing their treatment regimen were more likely to have at most a primary school education, multi-drug resistance (MDR)-TB, and few to moderate bacilli on acid-fast bacilli smear.

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