Background Fast food and other away from home food sources are linked with poorer diet quality and adverse health outcomes. The diet quality of young adults, major consumers of fast food, is understudied in terms of long-term shifts based on food sources for key subpopulation disparities. Methods The study included young adults ages 18–39 ( n = 8012) from the Continuing Survey of Food Intakes by Individuals 1989–1991 ( n = 4217) and the National Health and Nutrition Examination Survey 2011–2012 and 2013–2014 ( n = 3795). We stratified individuals based on their combination of food sources, race/ethnicity, and socioeconomic status. Using 24-h dietary recall data, we measured diet quality with the Healthy Eating Index-2015 (HEI-2015). Differences in diet quality were determined using 95% confidence intervals. Results Overall, diet quality increased across all food sources between the 1989–1991 and 2011–2014 surveys. The restaurant category overtook the at home category as the healthiest food source, while the fast food category remained the unhealthiest on days it was consumed. Vegetable intake decreased, while added sugar intake increased across all sources. Non-Hispanic whites and non-Hispanic blacks experienced similar increases in HEI-2015 scores across all food sources except restaurants, while Mexican American diet quality remained unchanged. Although all income levels experienced an increase in diet quality, the disparity between low- and high-income groups increased considerably. Conclusions US young adults consume healthier foods from all food sources, however, fast food consumers have significantly lower quality in the remainder of their diets. Additionally, Mexican Americans and low-income individuals emerge as high-risk groups for poor diet quality. Electronic supplementary material The online version of this article (10.1186/s12937-019-0460-4) contains supplementary material, which is available to authorized users.

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Background Uterine Artery Embolization (UAE) is a minimally invasive procedure used to treat symptomatic uterine fibroids. The HydroPearl Microsphere (Terumo Interventional Systems) is an embolic agent approved for UAE and other embolization procedures. The purpose of this article is to describe our initial experience with HydroPearl for UAE in patients with symptomatic uterine fibroids. Twenty-one patients who underwent UAE using HydroPearl Microspheres at a single institution from May 1, 2018 to December 31, 2019 were included in the study. The electronic medical record (EMR) was reviewed for documentation of short- and long-term complications, as well as improvements in menorrhagia and bulk-type symptoms. We also describe unique attributes of the HydroPearl Microsphere that should be considered when utilizing this embolization particle for UAE. Results Of the 21 patients, 18 had a 3-month or later post-procedure follow-up documented in the EMR and were included in the analysis. The average time between the UAE procedure and the most recent clinical note was 145 days. Sixteen patients reported symptoms of menorrhagia and 13 reported bulk symptoms prior to the UAE procedure. On follow-up, 13/16 patients (81%) and 12/13 patients (92%) experienced improvement in menorrhagia and bulk symptoms, respectively. The only recorded complication was amenorrhea in 4 patients (22%) who had an average age of 51 years. Conclusions Several characteristics of HydroPearl Microsphere may prove helpful when considering these embolic particles for use in UAE. Our initial experience with this embolic agent suggest that the reatment response for menorrhagia and bulk symptoms are largely similar to success rates reported in the literature for other embolic agents. Larger studies are needed to evaluate the safety and efficacy of this embolic particle for this indication.

Background Deep learning-based radiological image analysis could facilitate use of chest x-rays as a triaging tool for COVID-19 diagnosis in resource-limited settings. This study sought to determine whether a modified commercially available deep learning algorithm (M-qXR) could risk stratify patients with suspected COVID-19 infections. Methods A dual track clinical validation study was designed to assess the clinical accuracy of M-qXR. The algorithm evaluated all Chest-X-rays (CXRs) performed during the study period for abnormal findings and assigned a COVID-19 risk score. Four independent radiologists served as radiological ground truth. The M-qXR algorithm output was compared against radiological ground truth and summary statistics for prediction accuracy were calculated. In addition, patients who underwent both PCR testing and CXR for suspected COVID-19 infection were included in a co-occurrence matrix to assess the sensitivity and specificity of the M-qXR algorithm. Results 625 CXRs were included in the clinical validation study. 98% of total interpretations made by M-qXR agreed with ground truth (p = 0.25). M-qXR correctly identified the presence or absence of pulmonary opacities in 94% of CXR interpretations. M-qXR's sensitivity, specificity, PPV, and NPV for detecting pulmonary opacities were 94%, 95%, 99%, and 88% respectively. M-qXR correctly identified the presence or absence of pulmonary consolidation in 88% of CXR interpretations (p = 0.48). M-qXR's sensitivity, specificity, PPV, and NPV for detecting pulmonary consolidation were 91%, 84%, 89%, and 86% respectively. Furthermore, 113 PCR-confirmed COVID-19 cases were used to create a co-occurrence matrix between M-qXR's COVID-19 risk score and COVID-19 PCR test results. The PPV and NPV of a medium to high COVID-19 risk score assigned by M-qXR yielding a positive COVID-19 PCR test result was estimated to be 89.7% and 80.4% respectively. Conclusion M-qXR was found to have comparable accuracy to radiological ground truth in detecting radiographic abnormalities on CXR suggestive of COVID-19.

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