Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Lipoprotein(a) Atherosclerotic Cardiovascular Disease Risk Score Development and Prediction in Primary Prevention From Real-World Data.
Circ Genom Precis Med
January 2025
Mary and Steve Wen Cardiovascular Division, Department of Medicine, University of California, Los Angeles. (W.F., N.D.W.).
Background: Lp(a; Lipoprotein[a]) is a predictor of atherosclerotic cardiovascular disease (ASCVD); however, there are few algorithms incorporating Lp(a), especially from real-world settings. We developed an electronic health record (EHR)-based risk prediction algorithm including Lp(a).
Methods: Utilizing a large EHR database, we categorized Lp(a) cut points at 25, 50, and 75 mg/dL and constructed 10-year ASCVD risk prediction models incorporating Lp(a), with external validation in a pooled cohort of 4 US prospective studies.
Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems.
Circ Genom Precis Med
January 2025
Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT (A.A., L.S.D., E.K.O., R.K.).
Background: While universal screening for Lp(a; lipoprotein[a]) is increasingly recommended, <0.5% of patients undergo Lp(a) testing. Here, we assessed the feasibility of deploying Algorithmic Risk Inspection for Screening Elevated Lp(a; ARISE), a validated machine learning tool, to health system electronic health records to increase the yield of Lp(a) testing.
View Article and Find Full Text PDFRandom Survival Forest Machine Learning for the Prediction of Cardiovascular Events Among Patients With a Measured Lipoprotein(a) Level: A Model Development Study.
Circ Genom Precis Med
January 2025
Department of Medicine, Division of Cardiology (M.P., N.J.P., N.P.S.), Duke University, Durham, NC.
Background: Established risk models may not be applicable to patients at higher cardiovascular risk with a measured Lp(a) (lipoprotein[a]) level, a causal risk factor for atherosclerotic cardiovascular disease.
Methods: This was a model development study. The data source was the Nashville Biosciences Lp(a) data set, which includes clinical data from the Vanderbilt University Health System.
Characterisation of pregnancy-induced alterations in apolipoproteins and their associations with maternal metabolic risk factors and offspring birth outcomes: a preconception and longitudinal cohort study.
EBioMedicine
January 2025
Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore, Singapore; Department of Biochemistry and Precision Medicine Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. Electronic address:
Background: Apolipoproteins as an integral part of lipoproteins are crucial for the transport and metabolism of lipids. However, there is a lack of longitudinal studies to quantify the concentrations of maternal apolipoproteins from preconception to postpartum and their associations with maternal metabolic health and offspring birth outcomes.
Methods: Quantification of apolipoproteins was performed on maternal plasma samples (N = 243 trios) collected at preconception, 26-28 weeks' pregnancy, and three months postpartum in the Singapore PREconception Study of long-Term maternal and child Outcomes (S-PRESTO) cohort study.
Variation in lipoprotein(a) response to potent lipid lowering: The role of apolipoprotein (a) isoform size.
J Clin Lipidol
December 2024
Center for the Prevention of Cardiovascular Disease, Leon H. Charney Division of Cardiology, Department of Medicine, NYU Grossman School of Medicine. 530 First Avenue, HCC5, New York, NY 10016, USA. Electronic address:
Background: Lipoprotein(a) [Lp(a)] is a driver of residual cardiovascular risk. Proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) decrease Lp(a) with significant heterogeneity in response. We investigated contributors to the heterogeneous response.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!