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Development and application of a clinical core data set for deep brain stimulation in Parkinson's disease, dystonia or tremor: from data collection to data exchange and data sharing.
Neurol Res Pract
January 2025
Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-Universität Würzburg (JMU), Haus D7, Josef-Schneider-Straße 2, 97080, Würzburg, Germany.
Background: Comprehensive clinical data regarding factors influencing the individual disease course of patients with movement disorders treated with deep brain stimulation might help to better understand disease progression and to develop individualized treatment approaches.
Methods: The clinical core data set was developed by a multidisciplinary working group within the German transregional collaborative research network ReTune. The development followed standardized methodology comprising review of available evidence, a consensus process and performance of the first phase of the study.
Catlet scoring system as a new predictor for in-stent restenosis in patients with chronic coronary artery disease undergoing percutaneous coronary intervention with drug-eluting stent.
J Cardiothorac Surg
January 2025
Department of Cardiology, The first Affiliated Hospital of Wannan, Medical College, Wuhu, China.
Background: He's team have recently developed a new Coronary Artery Tree description and Lesion EvaluaTion (CatLet) angiographic scoring system, which is capable of accounting for the variability in coronary anatomy, and risk-stratifying patients with coronary artery disease. Preliminary studies have demonstrated its superiority over the the Synergy between percutaneous coronary intervention with Taxus and Cardiac Surgery (SYNTAX) score with respect to outcome predictions for acute myocardial infarction (AMI) patients. However, there are fewer studies on the prognostic in chronic coronary artery disease(CAD).
View Article and Find Full Text PDFGlucagon like peptide-1 (GLP-1) agonists and cardiometabolic protection: historical development and future challenges.
Cardiovasc Diabetol
January 2025
Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have revolutionized the treatment of cardiometabolic diseases, extending their therapeutic applications far beyond glycemic control in type 2 diabetes (T2D) and obesity. This editorial synthesizes key milestones, from the discovery of GLP-1 to recent clinical trials highlighting the pleiotropic effects of GLP-1RAs in addressing the interconnected spectrum of cardiometabolic conditions, with a focus on cardiovascular, renal, and hepatic benefits. In addition, as GLP-1RAs continue to reshape the management of cardiometabolic disease and global public health, we discuss future challenges to better elucidate their mechanisms of cardiometabolic protection and maximize their therapeutic potential.
View Article and Find Full Text PDFIncreased plasma DOPA decarboxylase levels in Lewy body disorders are driven by dopaminergic treatment.
Nat Commun
January 2025
Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Amsterdam, The Netherlands.
DOPA Decarboxylase (DDC) has been proposed as a cerebrospinal fluid (CSF) biomarker with increased concentrations in Lewy body disorders (LBDs) and highest levels in patients receiving dopaminergic treatment. Here we evaluate plasma DDC, measured by proximity extension assay, and the effect of dopaminergic treatment in three independent LBD (with a focus on dementia with Lewy bodies (DLB) and Parkinson's disease (PD)) cohorts: an autopsy-confirmed cohort (n = 71), a large multicenter, cross-dementia cohort (n = 1498) and a longitudinal cohort with detailed treatment information (n = 66, median follow-up time[IQR] = 4[4, 4] years). Plasma DDC was not altered between different LBDs and other disease groups or controls in absence of treatment.
View Article and Find Full Text PDFIntricacies of human-AI interaction in dynamic decision-making for precision oncology.
Nat Commun
January 2025
Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics if clinicians over or under rely on AI. To investigate such collaborative decision-making process, we conducted a Human-AI interaction study on response-adaptive radiotherapy for non-small cell lung cancer and hepatocellular carcinoma.
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