Publications by authors named "J B Gilman"
Background: Two diagnostic clinical scoring systems, the ATTR-CM Score and the T-AMYLO Score, have been proposed but not validated in diverse populations, despite Black race being an important risk factor for transthyretin amyloid cardiomyopathy (ATTR-CM). The aim of this study was to evaluate their performance in diagnosing ATTR-CM in a diverse patient cohort.
Methods: This retrospective single-center study analyzed patients who underwent a 99mTc-pyrophosphate single photon emission computed tomography scan (Tc-PYP) for workup of suspected ATTR-CM.
Article Synopsis
- Wildfires are a growing contributor to air pollution, particularly due to reactive organic compounds (ROC), which have varying health impacts based on their toxicity and abundance.
- A study combining field campaign data and air quality modeling found that current emissions estimates capture only 40-45% of the total ROC released from wildfires.
- The research indicates that particulate ROC could significantly affect health risks from smoke exposure, highlighting the need for more accurate toxicity data on these compounds.
Article Synopsis
- The study investigates the effects of one year of medical cannabis use on brain function, specifically focusing on areas tied to working memory, reward, and inhibitory control.
- Conducted in the Boston area, the cohort study involved individuals aged 18-65 who sought medical cannabis cards for conditions like anxiety, depression, pain, or insomnia.
- Results showed brain imaging performed before and after a year of cannabis use did not reveal significant changes in brain activation related to the cognitive tasks evaluated.
Introduction: Little is known about the prevalence and predictors of adolescents' intention to quit or reduce use of e-cigarettes and/or cannabis.
Methods: Frequencies of intention to change (quit, reduce) e-cigarettes and/or cannabis use were examined among 23,915 surveyed middle and high school students with sole and co-use. Predictors of intention to change were identified via LASSO/multilevel logistic regression.