Publications by authors named "Saly Abouelenein"

Background: Insulin resistance can impair the electrical conductivity of the heart. Spatial QRS-T axis reflects ventricular depolarization and repolarization. The relationship between insulin resistance and spatial QRS-T angle has not been examined in the general population.

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Background: Poultry plant workers are exposed to chemical carcinogens and oncogenic viruses in their work environment. Our objective was to identify jobs and workplaces related to poultries that could increase the pancreatic cancer risk.

Methods: We conducted a case-control study within a defined cohort of poultry workers.

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Objective: This job analysis was conducted to compare, assess and refine the competencies of the clinical research data management profession.

Materials And Methods: Two questionnaires were administered in 2015 and 2018 to collect information from data managers on professional competencies, types of data managed, types of studies supported, and necessary foundational knowledge.

Results: In 2018 survey, 67 professional competencies were identified.

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Purpose: Metabolic syndrome has a high prevalence in the United States. P-wave duration is a valuable indicator for atrial electrical conduction. Abnormalities in atrial electrical conduction can predispose to atrial fibrillation.

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The QRS-T angle is a key ECG predictor for ventricular arrhythmia. Lead has a strong relation with cardiovascular diseases; however, no study has been conducted to investigate the association between lead exposure and QRS-T angle. Thus, we explored this association in a population-based representative sample: NHANES III.

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Objective: Cadmium's effect on QRS|T angle has not been studied. An abnormal QRS|T angle deviation may increase the risk for ventricular dysrhythmias.

Methods: We calculated the orientation of spatial QRS|T angle using QRS and T amplitudes of leads V2, V5, V6, and AVF from the National Health and Nutritional Examination Survey III.

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A power calculation for a study with a quantitative outcome requires information on the outcome distribution under the alternative hypothesis. Researchers face challenges when they concisely specify alternative distributions in genetic studies because power depends on genotype frequencies and the average effect of each genotype. In GWAS, investigators evaluate hundreds of thousands of associations; therefore it is unrealistic to specify gene frequencies and gene effects for each test and some simplification is needed.

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