Leading paradigms of clinical ethics consultation closely follow a biomedical model of care. In this paper, we present a theoretical reflection on the underlying biomedical model of disease, how it shaped clinical practices and patterns of ethical deliberation within these practices, and the repercussions it has on clinical ethics consultations for patients with chronic illness. We contend that this model, despite its important contribution to capturing the ethical issues of day-to-day clinical ethics deliberation, might not be sufficient for patients presenting with chronic illnesses and navigating as "lay experts" of their medical condition(s) through the health care system. Not fully considering the sources of personal knowledge and expertise may lead to epistemic injustice within an ethical deliberation logic narrowly relying on a biomedical model of disease. In caring "for" and collaboratively "with" this patient population, we answer the threat of epistemic injustice with epistemic modesty and humility. We will propose ideas about how clinical ethics could contribute to an expansion of the biomedical model of care, so that important aspects of chronic illness experience would flow into clinical-ethical decision-making.
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http://dx.doi.org/10.1007/s10730-022-09494-8 | DOI Listing |
Open Res Eur
January 2025
Heidelberger Institut für Global Health, Universitätsklinikum Heidelberg, Heidelberg, Baden-Württemberg, 69120, Germany.
Introduction: The benefits of sharing participant-level data, including clinical or epidemiological data, genomic data, high-dimensional imaging data, or human-derived samples, from biomedical studies have been widely touted and may be taken for granted. As investments in data sharing and reuse efforts continue to grow, understanding the cost and positive and negative effects of data sharing for research participants, the general public, individual researchers, research and development, clinical practice, and public health is of growing importance. In this scoping review, we will identify and summarize existing evidence on the positive and negative impacts and costs of data sharing and how they are measured.
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January 2025
Faculty of Medicine, King Abdulaziz University, Jeddah, SAU.
Objective: Our study aims to assess the clinical effectiveness of using MRI in diagnosing various shoulder pain-related conditions among patients at King Abdulaziz University Hospital.
Methods: 383 patients who were admitted to King Abdulaziz University Hospital and had shoulder magnetic resonance imaging between January 2020 and July 2024 were studied retrospectively. The dataset was subjected to a thorough statistical analysis using descriptive and inferential approaches.
Introduction Nephrotic syndrome, an unusual clinical presentation of IgA nephropathy (IgAN), occurs only in a few cases. The data regarding its clinical characteristics and treatment outcomes are lacking. Material and methods In this retrospective analysis, we reviewed kidney biopsies conducted between January 2007 and December 2018.
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December 2024
Prosthodontics, Government Dental College, Kozhikode, IND.
Background: Digital dentistry has transformed all aspects of dentistry, especially prosthodontics, and is increasingly used for diagnosis, treatment planning, execution, student training, and research. This study aimed to assess the perception, attitude, and practice of digital technology in prosthodontics among dental professionals in Kerala, India.
Materials And Methods: A cross-sectional, questionnaire-based study was conducted among dental professionals in Kerala.
Cureus
December 2024
Department of Dental Anesthesiology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, JPN.
Objective: Imbalanced autonomic nervous system (ANS) activity raises concerns about the development of systemic complications during dental treatment. The purpose of this study was to determine whether a psychological test (Toho Medical Index (TMI)) prior to the impacted mandibular third molar extraction can identify patients with potentially imbalanced autonomic function.
Materials And Methods: In this prospective study, 34 healthy adult patients with no history of systemic disease were assigned to either the autonomic imbalance group (type II, III, IV) or the control group (type I) based on the results of the TMI.
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