Mechanism-based classification of pain has been advocated widely to aid tailoring of interventions for individuals experiencing persistent musculoskeletal pain. Three pain mechanism categories (PMCs) are defined by the International Association for the Study of Pain: nociceptive, neuropathic, and nociplastic pain. Discrimination between them remains challenging. This study aimed to build on a framework developed to converge the diverse literature of PMCs to systematically review methods purported to discriminate between them; synthesise and thematically analyse these methods to identify the convergence and divergence of opinion; and report validation, psychometric properties, and strengths/weaknesses of these methods. The search strategy identified articles discussing methods to discriminate between mechanism-based categories of pain experienced in the musculoskeletal system. Studies that assessed the validity of methods to discriminate between categories were assessed for quality. Extraction and thematic analysis were undertaken on 184 articles. Data synthesis identified 200 methods in 5 themes: clinical examination, quantitative sensory testing, imaging, diagnostic and laboratory testing, and pain-type questionnaires. Few methods have been validated for discrimination between PMCs. There was general convergence but some disagreement regarding findings that discriminate between PMCs. A combination of features and methods, rather than a single method, was generally recommended to discriminate between PMCs. Two major limitations were identified: an overlap of findings of methods between categories due to mixed presentations and many methods considered discrimination between 2 PMCs but not others. The results of this review provide a foundation to refine methods to differentiate mechanisms for musculoskeletal pain.
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http://dx.doi.org/10.1097/j.pain.0000000000002113 | DOI Listing |
Clin Oncol (R Coll Radiol)
December 2024
Radiation Oncology Network, Westmead Hospital, Westmead, NSW, Australia; Sydney Medical School, The University of Sydney, Camperdown, NSW 2006, Australia. Electronic address:
Aims: Unresectable cutaneous squamous cell cancer of the head and neck (HNcSCC) poses treatment challenges in elderly and comorbid patients. Radiation therapy (RT) is often employed for locoregional control. This study aimed to determine progression-free survival (PFS) and overall survival (OS) outcomes achieved with upfront RT in unresectable HNcSCC.
View Article and Find Full Text PDFAm J Emerg Med
January 2025
Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA; Center for Outcomes Research and Evaluation, Yale University, New Haven, CT, USA.
Background: This study aimed to examine how physician performance metrics are affected by the speed of other attendings (co-attendings) concurrently staffing the ED.
Methods: A retrospective study was conducted using patient data from two EDs between January-2018 and February-2020. Machine learning was used to predict patient length of stay (LOS) conditional on being assigned a physician of average speed, using patient- and departmental-level variables.
Am J Emerg Med
January 2025
Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain; Emergency Department, Hospital Clínico Universitario, Gerencia Regional de Salud de Castilla y León, Valladolid, Spain.
Background: The study of the inclusion of new variables in already existing early warning scores is a growing field. The aim of this work was to determine how capnometry measurements, in the form of end-tidal CO2 (ETCO2) and the perfusion index (PI), could improve the National Early Warning Score (NEWS2).
Methods: A secondary, prospective, multicenter, cohort study was undertaken in adult patients with unselected acute diseases who needed continuous monitoring in the emergency department (ED), involving two tertiary hospitals in Spain from October 1, 2022, to June 30, 2023.
Biomed Phys Eng Express
January 2025
Department of Ophthalmology, Hospital Universitario de Canarias, Carretera Ofra S/N, La Laguna, Santa Cruz de Tenerife, 38320, SPAIN.
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodological novelty, were used to relate features highlighted in the saliency maps to the geometrical clues that experts consider in glaucoma diagnosis. Despite their simplicity, these images retained sufficient information for accurate classification, with balanced accuracies ranging from 0.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Shandong University of Traditional Chinese Medicine, Qingdao Academy of Chinese Medical Sciences, Jinan, Shandong, 250355, CHINA.
Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease, and it can be used as an important indicator of disease progression. However, many existing methods focus mainly on the image itself when processing brain imaging data, ignoring other non-imaging data (e.g.
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