Review Article | DOI: https://doi.org/10.31579/2639-4162/250
Specialist, Family and Community Medicine, Health Center Santa Maria de Benquerencia, Regional Health Service of Castilla la Mancha (SESCAM), Toledo, Spain.
*Corresponding Author: Jose Luis Turabian, Specialist, Family and Community Medicine, Health Center Santa Maria de Benquerencia, Regional Health Service of Castilla la Mancha (SESCAM), Toledo, Spain.
Citation: Jose L. Turabian (2025), A Provisional Conceptual Taxonomy of Prototypical Uncertainty Management Strategies in General Medicine, J. General Medicine and Clinical Practice, 8(2); DOI:10.31579/2639-4162/250
Copyright: 2025, Jose Luis Turabian. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Received: 19 December 2024 | Accepted: 03 February 2025 | Published: 14 February 2025
Keywords: nitrate-rich diet; nitric oxide; cognitive decline; sugar; oral microbiome; gut-brain axis
Cognitive decline is influenced by various factors, including diet, oral and gut microbiome health, vascular function, and systemic inflammation. This paper examines the contrasting effects of nitrate-rich diets and high sugar consumption on brain health. While nitrate-rich foods enhance nitric oxide (NO) production, supporting vascular and cognitive functions, excessive sugar intake disrupts glucose metabolism, damages the microbiome, and accelerates neurodegeneration. We review clinical studies, present relevant data through tables and graphs, and discuss strategies to optimize diet and microbiome health to prevent cognitive decline.
General practitioners (GPs) are often faced with complex problems, defined as those with two or more chronic conditions that together may have an adverse effect on health status, function or quality of life, and which require complex approaches to health care (1), but also patients with associated socioeconomic and medical problems, with mental and behavioural health problems, and frequently with multimorbidity that is associated with polypharmacy and the consequent adverse drug effects and drug interactions. Many decisions are made in fractions of a second, so that the process is so fast that we are not aware of it. But it is important to analyse what happens and how we can improve it because decisions are fundamental to our professional development and to achieving better patient outcomes. However, the methods GPs use to address these complexities are not yet understood, adequately conceptualised, or taught to junior doctors. ¿So how do expert GPs manage complex problems and adapt them to their community context? (2-5).
In addition to using evidence-based medicine (EBM), several, partly overlapping, approaches have been identified that are more frequently used than EBM as a sole tool by GPs to deal with complexities, and are specific to these specialists, and are not used (or very rarely) by hospitalists (6). Thus, we can cite the following:
In summary, medical uncertainty is a widespread and important problem, but the strategies GPs use to manage it have not been systematically described. Exploring the uncertainty management strategies employed by GPs practising in community primary care settings, and organising these strategies within a conceptual taxonomy, is an important task that can guide efforts to understand and improve GPs' tolerance for clinical uncertainty. Providing a guiding framework for future research is essential to begin to understand how GPs undertake the task of managing uncertainty in the clinic; some way of imposing a useful order on the problem is needed. A conceptual taxonomy is presented here, and the prototypical uncertainty management strategies provide a provisional starting point. One of the obvious factors that make making decisions regarding human actions difficult is the complexity of life. Thus, we realise that to solve complex problems, the number of possible solutions is large and the simple choice between them is inadequate. to solve complex problems, the number of possible solutions is large and the simple choice between them is inadequate.
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