Identifying mild dehydration (≤2% of body mass) is important to prevent the negative effects of more severe dehydration on human health and performance. It is unknown whether a single hydration marker can identify both mild intracellular dehydration (ID) and extracellular dehydration (ED) with adequate diagnostic accuracy (≥0.7 receiver-operating characteristic-area under the curve [ROC-AUC]). Thus, in 15 young healthy men, the authors determined the diagnostic accuracy of 15 hydration markers after three randomized 48-hr trials; euhydration (water 36 ml·kg-1·day-1), ID caused by exercise and 48 hr of fluid restriction (water 2 ml·kg-1·day-1), and ED caused by a 4-hr diuretic-induced diuresis begun at 44 hr (Furosemide 0.65 mg/kg). Body mass was maintained on euhydration, and dehydration was mild on ID and ED (1.9% [0.5%] and 2.0% [0.3%] of body mass, respectively). Urine color, urine specific gravity, plasma osmolality, saliva flow rate, saliva osmolality, heart rate variability, and dry mouth identified ID (ROC-AUC; range 0.70-0.99), and postural heart rate change identified ED (ROC-AUC 0.82). Thirst 0-9 scale (ROC-AUC 0.97 and 0.78 for ID and ED) and urine osmolality (ROC-AUC 0.99 and 0.81 for ID and ED) identified both dehydration types. However, only the thirst 0-9 scale had a common dehydration threshold (≥4; sensitivity and specificity of 100%; 87% and 71%, 87% for ID and ED). In conclusion, using a common dehydration threshold ≥4, the thirst 0-9 scale identified mild intracellular and ED with adequate diagnostic accuracy. In young healthy adults', thirst 0-9 scale is a valid and practical dehydration screening tool.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1123/ijsnem.2019-0022 | DOI Listing |
BMC Pulm Med
January 2025
Universal Scientific Education and Research Network (USERN), Tehran, Iran.
Objective: Lung cancer (LC), the primary cause for cancer-related death globally is a diverse illness with various characteristics. Saliva is a readily available biofluid and a rich source of miRNA. It can be collected non-invasively as well as transported and stored easily.
View Article and Find Full Text PDFSci Rep
January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
View Article and Find Full Text PDFEur Arch Otorhinolaryngol
January 2025
Faculty of Applied Sciences, Department of Accounting and Financial Management, Necmettin Erbakan University, Konya, Turkey.
Purpose: Vestibular neuritis (VN) is a common cause of vertigo with significant impact on patients' quality of life. This study aimed to analyze global research trends in VN using bibliometric methods to identify key themes, influential authors, institutions, and countries contributing to the field.
Methods: We conducted a comprehensive search of the Web of Science Core Collection database for publications related to VN from 1980 to 2024.
NPJ Digit Med
January 2025
Neurofibromatosis Type 1 Center and Laboratory for Neurofibromatosis Type 1 Research, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Anesthesiology and Surgical Intensive Care Unit, Kunming Children's Hospital, Kunming, Yunnan, China.
Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!