The evidence-based medicine (EBM) paradigm, introduced in 1992, has had a major and positive impact on all aspects of health care. However, widespread use has also uncovered some limitations; these are discussed from the perspectives of two clinicians in this, the first of a two part narrative review. For example, there are credible reservations about the validity of hierarchical levels of evidence, a core element of the EBM paradigm. In addition, potential and actual methodological and statistical deficiencies have been identified, not only in many published randomized controlled trials but also in systematic reviews, both rated highly for evidence in EBM classifications. Ethical violations compromise reliability of some data. Clinicians need to be conscious of potential limitations in some of the cornerstones of the EBM paradigm, and to deficiencies in the literature.
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http://dx.doi.org/10.1017/s0317167100014542 | DOI Listing |
J Neurosurg
December 2024
22Department of Neurological Surgery, University of Virginia, Charlottesville, Virginia.
Objective: This study aimed to evaluate local control (LC) of tumors, patient overall survival (OS), and the safety of stereotactic radiosurgery (SRS) for esophageal cancer brain metastases (EBMs).
Methods: This retrospective cohort study used data from 15 International Radiosurgery Research Foundation facilities encompassing 67 patients with 185 EBMs managed using SRS between January 2000 and May 2022. The median patient age was 63 years, with a male predominance (92.
Entropy (Basel)
October 2024
Department of History and Philosophy, Montana State University, Bozeman, MT 59717, USA.
Empirical Bayes-based Methods () is an increasingly popular form of Objective Bayesianism (). It is identified in particular with the statistician Bradley Efron. The main aims of this paper are, first, to describe and illustrate its main features and, second, to locate its role by comparing it with two other statistical paradigms, Subjective Bayesianism () and Evidentialism's main formal features are illustrated in some detail by schematic examples.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
October 2024
Evidence-based medicine (EBM) represents a paradigm of providing patient care grounded in the most current and rigorously evaluated research. Recent advances in large language models (LLMs) offer a potential solution to transform EBM by automating labor-intensive tasks and thereby improving the efficiency of clinical decision-making. This study explores integrating LLMs into the key stages in EBM, evaluating their ability across evidence retrieval (PICO extraction, biomedical question answering), synthesis (summarizing randomized controlled trials), and dissemination (medical text simplification).
View Article and Find Full Text PDFFront Cardiovasc Med
September 2024
Cardiovascular Department, The Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.
Chaos
July 2024
Grantham Research Institute on Climate Change and the Environment, The London School of Economics and Political Science, Houghton Street, London WC2A 2AE, United Kingdom.
We first review the way in which Hasselmann's paradigm, introduced in 1976 and recently honored with the Nobel Prize, can, like many key innovations in complexity science, be understood on several different levels. It can be seen as a way to add variability into the pioneering energy balance models (EBMs) of Budyko and Sellers. On a more abstract level, however, it used the original stochastic mathematical model of Brownian motion to provide a conceptual superstructure to link slow climate variability to fast weather fluctuations, in a context broader than EBMs, and led Hasselmann to posit a need for negative feedback in climate modeling.
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