Publications by authors named "J F Brandts"
Purpose Of Review: This review explores the relationship between lipid-lowering therapies, particularly statins, and the risk of new-onset diabetes (NOD). It examines the underlying mechanisms and evaluates whether other lipid-lowering agents present similar risks.
Recent Findings: Recent meta-analyses further underscore a dose-dependent increase in NOD risk with statin therapy, particularly with high-intensity statins.
Article Synopsis
- - The study focuses on improving the detection of familial hypercholesterolemia (FH), a common genetic disorder that is often underdiagnosed, which could help prevent heart-related issues linked to it.
- - Researchers used machine learning algorithms on data from the UK Biobank to identify individuals with FH-causing genetic variants, comparing the performance of these algorithms against existing clinical diagnostic criteria.
- - The findings showed that their machine learning model outperformed traditional diagnostic methods in identifying FH, with better sensitivity and accuracy, and reduced the number of individuals needed to be screened to find a case of FH.
Objective: This review aims to systematically map and categorize the current state of wearable applications among oncology patients and to identify determinants impeding clinical implementation.
Methods: A Medline, Embase and clinicaltrials.gov search identified journal articles, conference abstracts, letters, reports, dissertations and registered studies on the use of wearables in patients with malignancies published up to 10 November 2021.
Aim: To assess the implementation of the 2019 European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) guideline recommendations for lipid-lowering therapies among more than 30 000 patients with type 1 diabetes (T1D) and type 2 diabetes (T2D) in a German and Austrian registry from 2020 to 2022.
Materials And Methods: Registry data from 2020 and 2021 of 32 170 adult patients (8314 patients with T1D and 23 856 with T2D) were stratified according to the 2019 ESC/EAS risk categories, and guideline-based low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) goal attainment was analysed.
Results: In patients with T1D (median age 38.
Background: The impact of the stepwise implementation of the 2019 European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) treatment algorithm on low-density lipoprotein cholesterol (LDL-C) goal attainment was simulated in patients from the DA VINCI study.
Methods: Monte Carlo simulation was used to evaluate treatment optimisation scenarios, based on a patient's risk category: statin intensification (step 1), addition of ezetimibe (step 2), and addition of a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor (step 3). Residual cardiovascular risk and predicted relative and absolute risk reduction (RRR and ARR) in cardiovascular events were assessed.