Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after pregnancy. Because of its diverse clinical presentation, preeclampsia is an adverse pregnancy outcome that is uniquely challenging to predict and manage. In this paper, we developed racial bias-free machine learning models that predict the onset of preeclampsia with severe features or eclampsia at discrete time points in a nulliparous pregnant study cohort.
View Article and Find Full Text PDFHereditary angioedema with C1 inhibitor deficiency (HAE-C1-INH) is a rare disorder characterized by recurrent, potentially life-threatening swelling in various parts of the body, including the limbs, face, and airways Current treatments focus primarily on symptomatic relief and the management of acute attacks, without targeting the underlying genetic cause or the dysregulated bradykinin production. Donidalorsen, a novel antisense oligonucleotide, addresses a key driver of HAE-C1-INH by targeting prekallikrein (PKK) to reduce bradykinin levels. This meta-analysis evaluates the efficacy and safety of Donidalorsen versus placebo, focusing on two dosing regimens: 4-week and 8-week intervals.
View Article and Find Full Text PDFObjective: To determine whether point-of-order clinical decision support (CDS) based on the Wells Criteria improves CT pulmonary angiogram (CTPA) yield and utilization in hospitalized patients in an enterprise-wide health system and identify yield-related factors.
Methods: This retrospective IRB-approved cross-sectional study in an urban, multi-institution health system included hospitalized patients undergoing CTPA 12 months before and after CDS implementation (entire cohort). Chi-square test was used to compare PE yield in patients in whom providers overrode vs.