ArticleMedical research archives2024
A Personalized Medicine Approach is Best for Patients with Homozygous Familial Hypercholesterolemia.
Article in Medical research archives, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
Abstract
Homozygous familial hypercholesterolemia (HoFH) is an autosomal semi-dominant condition characterized by biallelic pathogenic variants impacting low-density lipoprotein receptor (LDLR) function. Affected individuals have severely elevated LDL cholesterol, early onset atherosclerotic heart disease and/or aortic stenosis, and characteristic clinical findings. While the cause is known and diagnosis is relatively simple, real-world HoFH care presents many complexities, including genetic heterogeneity and the diverse personal and social circumstances that influence care. Genetics-informed treatment involves a trial-and-error approach that warrants specific considerations during pregnancy. Thus, HoFH care requires a deep understanding of personal factors, social determinants of health, and a flexible, adaptable approach to treatment, all of which justify the need for personalized care. Framed by complexity theory, this review offers strategies for personalizing HoFH care, including a reconceptualization of the definition of health and implementing a multidisciplinary team approach. We also recommend integrating complexity theory and systems thinking into clinical care. By doing so, we illustrate the advantages of classifying knowledge complexity to inform clinical decision-making. We also demonstrate how openness to relationship-building and time investment is critical to materializing personalized care to HoFH.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.