Publications by authors named "Meleeka Akbarpour"

Objective: To assess and characterize online ratings and comments on laryngologists and determine factors that correlate with higher ratings.

Methods: All the American Laryngological Association (ALA) members were queried across several online platforms. Ratings were normalized for comparison on a five-point Likert scale.

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Objective: Tinnitus is defined as the perception of sound in the absence of an external source. We propose the hypothesis that migraine can cause exacerbation of tinnitus in some patients.

Methods: English literature from PubMed has been reviewed.

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Real-world data on lipid levels and treatment among adults with diabetes mellitus (DM) are relatively limited. We studied lipid levels and treatment status in patients with DM across cardiovascular disease (CVD) risk groups and sociodemographic factors. In the Research Program, we categorized DM as (1) moderate risk (≤1 CVD risk factor), (2) high risk (≥2 CVD risk factors), and (3) DM with atherosclerotic CVD (ASCVD).

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Purpose: Data are limited on sodium glucose co-transport 2 inhibitors (SGLT2-is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) among real-world cohorts of underrepresented patients. We examined these therapies and glycemic control in US adults with diabetes mellitus (DM) by atherosclerotic cardiovascular disease (ASCVD) risk and sociodemographic factors.

Methods: In the NIH Precision Medicine Initiative All of Us Research Program, we categorized DM as (1) moderate risk, (2) high risk, and (3) with ASCVD.

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The development of public health education campaigns about tobacco products requires an understanding of specific audience segments including their views, intentions, use of media, perceived barriers, and benefits of change. For example, identifying and targeting individuals who express ambivalence about e-cigarette use on Twitter may be helpful in devising and focusing public health campaigns to reduce e-cigarette use. This study developed a novel analytic strategy using social network analysis to identify audience segments on Twitter based on positive, negative, and neutral e-cigarette sentiment.

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