Aims: To validate the reported increased atherosclerotic cardiovascular disease (ASCVD) risk associated with very high lipoprotein(a) [Lp(a)] and to investigate the impact of routine Lp(a) assessment on risk reclassification.
Methods And Results: We performed a cross-sectional case-control study in the Amsterdam UMC, a tertiary hospital in The Netherlands. All patients in whom a lipid blood test was ordered between October 2018 and October 2019 were included. Individuals with Lp(a) >99th percentile were age and sex matched to individuals with Lp(a) ≤20th percentile. We computed odds ratios (ORs) for myocardial infarction (MI) and ASCVD using multivariable logistic regression adjusted for age, sex, and systolic blood pressure. Furthermore, we assessed the additive value of Lp(a) to established ASCVD risk algorithms. Lipoprotein(a) levels were determined in 12 437 individuals, out of whom 119 cases [Lp(a) >99th percentile; >387.8 nmol/L] and 119 matched controls [Lp(a) ≤20th percentile; ≤7 nmol/L] were included. Mean age was 58 ± 15 years, 56.7% were female, and 30.7% had a history of ASCVD. Individuals with Lp(a) levels >99th percentile had an OR of 2.64 for ASCVD [95% confidence interval (CI) 1.45-4.89] and 3.39 for MI (95% CI 1.56-7.94). Addition of Lp(a) to ASCVD risk algorithms led to 31% and 63% being reclassified into a higher risk category for Systematic Coronary Risk Evaluation (SCORE) and Second Manifestations of ARTerial disease (SMART), respectively.
Conclusion: The prevalence of ASCVD is nearly three-fold higher in adults with Lp(a) >99th percentile compared with matched subjects with Lp(a) ≤20th percentile. In individuals with very high Lp(a), addition of Lp(a) resulted in one-third of patients being reclassified in primary prevention, and over half being reclassified in secondary prevention.
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http://dx.doi.org/10.1093/eurjpc/zwab167 | DOI Listing |
Mayo Clin Proc
January 2025
Division of Pediatric Cardiology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN; Department of Molecular Pharmacology and Experimental Therapeutics, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, MN; Division of Heart Rhythm Services, Department of Cardiovascular Medicine, Windland Smith Rice Genetic Heart Rhythm Clinic, Mayo Clinic, Rochester, MN. Electronic address:
Objective: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with long QT syndrome (LQTS) from those with acquired QT prolongation.
Methods: The study cohort included all patients with genetically confirmed LQTS evaluated in the Windland Smith Rice Genetic Heart Rhythm Clinic and controls from Mayo Clinic's ECG data vault comprising more than 2.5 million patients.
PLoS One
January 2025
Centre for Community Health Studies (ReaCH), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Purpose: This study investigates the agreement of children's retinal thickness classification by color category between Topcon 3D OCT-1's built-in adult reference data and our new pediatric database and assesses the correlation of retinal thickness with age and spherical equivalent (SE).
Methods: 160 eyes of 160 healthy children (74 boys, 86 girls) aged 6-18 years (mean: 11.60 ± 3.
Clin Chem Lab Med
January 2025
Coordinator of the Italian Study Group of Cardiac Biomarkers, Scuola Superiore Sant'Anna and Fondazione CNR - Regione Toscana G. Monasterio, Pisa, Italy.
Biom J
February 2025
Department of Mathematics, University of Bergen, Bergen, Norway.
Correct measurement results from in vitro diagnostic (IVD) medical devices (MD) are crucial for optimal patient care. The performance of IVD-MDs is often assessed through method comparison studies. Such studies can be compromised by the influence of various factors.
View Article and Find Full Text PDFClin Chim Acta
December 2024
Department of Clinical Chemistry, Department of Biochemistry, University of Health Sciences, Bakirköy Dr. Sadi Konuk Training and Research Hospital, İstanbul, Türkiye.
Introduction: To perform simulation studies on patient-based real-time quality control (PBRTQC) for aspartate aminotransferase (AST), iron (Fe), potassium (K), and thyrotropin (thyroid stimulating hormone, TSH) analytes, focusing on optimizing systematic error detection while minimizing data loss.
Methods: Clinical laboratory data for the four analytes were analyzed using various truncation methods. Among these methods, truncation limits corresponding to fixed percentiles (e.
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