The current study had two objectives. (1) to compare objective and self-report measures in patients with chronic fatigue syndrome (CFS) according to the 1994 Center for Disease Control (CDC) criteria, patients with multiple sclerosis (MS), and healthy controls, and (2) to contrast CFS patients who only fulfill CDC criteria to those who also fulfill the criteria for myalgic encephalomyelitis (ME), the 2003 Canadian criteria for ME/CFS, or the comorbid diagnosis of fibromyalgia (FM). One hundred six participants (48 CFS patients diagnosed following the 1994 CDC criteria, 19 MS patients, and 39 healthy controls) completed questionnaires assessing symptom severity, quality of life, daily functioning, and psychological factors. Objective measures consisted of activity monitoring, evaluation of maximal voluntary contraction and muscle recovery, and cognitive performance. CFS patients were screened whether they also fulfilled ME criteria, the Canadian criteria, and the diagnosis of FM. CFS patients scored higher on symptom severity, lower on quality of life, and higher on depression and kinesiophobia and worse on MVC, muscle recovery, and cognitive performance compared to the MS patients and the healthy subjects. Daily activity levels were also lower compared to healthy subjects. Only one difference was found between those fulfilling the ME criteria and those who did not regarding the degree of kinesiophobia (lower in ME), while comorbidity for FM significantly increased the symptom burden. CFS patients report more severe symptoms and are more disabled compared to MS patients and healthy controls. Based on the present study, fulfillment of the ME or Canadian criteria did not seem to give a clinically different picture, whereas a diagnosis of comorbid FM selected symptomatically worse and more disabled patients.
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http://dx.doi.org/10.1007/s10067-014-2793-x | DOI Listing |
Drugs Aging
January 2025
Department of Geriatric Medicine, Jeroen Bosch Hospital, 's Hertogenbosch, The Netherlands.
Purpose: Renin-angiotensin-aldosterone system inhibitors (RAASi) are widely used in treatment of cardiovascular and renal disease. While effective, they pose a risk of hyperkalemia. In the general population, risk factors for hyperkalemia include chronic kidney disease, congestive heart failure, and use of medication affecting potassium balance.
View Article and Find Full Text PDFJ Clin Med
December 2024
Stichting CardioZorg, Kraayvel 5, 1171 JE Badhoevedorp, The Netherlands.
: While the diagnosis of postural orthostatic tachycardia syndrome (POTS) is based on heart rate (HR) and blood pressure (BP) criteria, the pathophysiology of POTS is not fully understood as multiple pathophysiological mechanisms have been recognized. Also, cardiac function, being dependent on preload, afterload, contractility, and HR, has not been properly studied. Preload and contractility changes can be inferred from stroke volume index (SVI) changes during a tilt test.
View Article and Find Full Text PDFHealthcare (Basel)
December 2024
Stichting Cardio Zorg, Kraayveld 5, 1171 JE Badhoevedorp, The Netherlands.
Introduction: Orthostatic intolerance is highly prevalent in patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and is caused by an abnormal reduction in cerebral blood flow (CBF). In healthy controls (HCs), the regulation of CBF is complex and cardiac output (CO) is an important determinant of CBF: a review showed that a 30% reduction in CO results in a 10% reduction in CBF. In previous and separate ME/CFS studies, we showed that CO and CBF decreased to a similar extent during tilt testing.
View Article and Find Full Text PDFLancet Reg Health Eur
February 2025
Institute of Medical Immunology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, Berlin, 13353, Germany.
Comput Biol Med
January 2025
Computer Engineering Department, Technology Faculty, Marmara University, Maltepe, Istanbul, Turkey. Electronic address:
Background: To address critical security challenges in the Internet of Medical Things (IoMT), this study develops a feature selection framework to improve detection accuracy and computational efficiency in IoMT cybersecurity. By optimizing feature selection, the framework aims to enhance the security and operational integrity of real-time healthcare systems.
Method: This study integrates Random Subset Feature Selection (RSFS) with Correlation Feature Selection (CFS) to create a novel feature selection framework tailored to IoMT datasets.
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