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The status of complementary and alternative medicine (CAM) in biomedical education
Published in Caragh Brosnan, Bryan S. Turner, Handbook of the Sociology of Medical Education, 2009
So what are the key ontological and epistemological issues and how might we make sense of the differences in ideological approach between CAM and biomedicine? Ontology, in this context, refers to the study of the nature of reality and epistemology refers to the study of knowledge or how we get to know certain things. CAM practice and biomedicine, in some cases, pursue quite different approaches to the reality of disease (ontology) and prioritize different ways of creating knowledge about disease and the body (epistemology). As shown in Table 8.1, the biomedical model (the broad therapeutic approach espoused within biomedicine), entails a functionalist approach to illness, with an emphasis on the body as an organism that can be treated symptomatically. The biomedical model constructs illness as a breakdown or dysfunction of a particular organ. Medicine, especially hospital-based, is broadly mechanistic, with doctors viewing the body as a machine made of many parts, with the respective individual parts treated separately. This mechanistic approach, crucially, stresses the centrality of the doctor in the healing process. The doctor’s intervention is active, and, in general, downplays the role of any psychological or metaphysical factors that may cause the disease or play a role in its natural evolution or treatment. The biomedical model is thus characterized as materialist in its focus on the corporeal body, yet at the same time abstract in its removal of the body from the soul and from the person. It is important at this point to stress that this is a model of healthcare, not a description of the actual approach taken by biomedical practitioners. However, in saying this, the centrality of this model in biomedical training and organizational culture does strongly influence how doctors approach treatment and is key within the curricula of medical- education programmes internationally.
Temporal Trends in Childhood Uveitis: Using Administrative Health Data to Investigate the Impact of Health Policy and Clinical Practice
Published in Ocular Immunology and Inflammation, 2022
Akshay R. Narayan, Jugnoo S. Rahi, Ameenat Lola Solebo
We aimed to capture data for cases of non-infectious uveitis, but were limited by the use of the ICD-10 disease taxonomy within this national administrative health database. ICD-10 does not allow for comprehensive classification of the uveitides. For example, whilst different forms of toxoplasma uveitis (“B58.01: toxoplasmosis chorioretinitis”) and ocular tuberculosis have unique ICD-10 codes (eg: “A18.54: tuberculous iridocyclitis,” or “A18.53: tuberculous chorioretinitis”), other infectious uveitides have no unique ICD-10 code (uveitis due to toxocariasis or due to Lyme disease is included within “B83.0: visceral larva migrans,” and “A69.29: Other conditions associated with Lyme disease,” respectively). As ICD-10 categories such as “H30.1: disseminated chorioretinal inflammation,” or “H30.8: other chorioretinal inflammations” or “H44.1: other endophthalmitis” may not be limited to non-infectious uveitides, the cohort presented here may include infectious causes. However, this is expected to be relevant to only a minority of cases, and a particularly small minority within the episodes related to anterior uveitis. The incomplete mapping of ICD-10 codes to international consensus-based disease taxonomy (such as that in the standardized uveitis nomenclature) remains a challenge to the use of historic administrative datasets to explore trends and outcomes for the different disease phenotypes. International groups will need to continue work towards agreed supranational disease ontology.
Current and emerging treatment options to prevent renal failure due to autosomal dominant polycystic kidney disease
Published in Expert Opinion on Orphan Drugs, 2020
Gopala K. Rangan, Aarya Raghubanshi, Alissa Chaitarvornkit, Ashley N. Chandra, Robert Gardos, Alexandra Munt, Mark N. Read, Sayanthooran Saravanabavan, Jennifer Q.J. Zhang, Annette T.Y. Wong
V2RAs have generated renewed interest in ADPKD, leading to an abundance of new interventions being evaluated in clinical trials, as discussed earlier. Thus, over the next decade, the number of proven treatments will expand, providing opportunities to individualize therapy based on personal preferences and disease ontology. Moreover, over the next 5 years, ongoing post-market cohort studies such as the German ADPKD Tolvaptan Treatment Registry (2015–27, NCT02497521); the Canadian Medical Assessment of JINARC Outcomes Registry (C-MAJOR study, 2016–22, NCT02925221) [178,179] will allow the long-term uncertainties of V2Ras in ADPKD to be addressed. In addition, studies in sub-groups, such as pediatric ADPKD patients [180] and in Korea (the ESSENTIAL trial, NCT03949894) [181], will provide much needed data.
Working the literature harder: what can text mining and bibliometric analysis reveal?
Published in Expert Review of Proteomics, 2019
Yu Han, Sara A. Wennersten, Maggie P. Y. Lam
This discovery model can be accelerated by text-mining and may become increasingly valuable for drug repurposing by joining together separate disease–protein (A–B) and protein–drug (B–C) relationships [10]. It can also uncover unexpected commonalities in disease mechanisms. As mentioned, literature analysis can associate a disease term (e.g. ‘hypertension’) with a list of proteins [6] or phenotype terms [11]. It is therefore possible to quantify how closely related two diseases are, based on how many associated proteins or phenotypes they share. Upon analyzing a collection of disease terms (e.g. Disease Ontology), a network of relationships between disorders, or ‘diseasome’, can be constructed to identify unexpected similarities across diseases. For example, network analysis of phenotype associations led to the hypothesis that some forms of spinal muscular atrophy may be more closely related to lysosomal storage disorders than previously anticipated [11].