Background: Detection of early lymphedema is important for effective treatment outcome and reduction of disease burden. The aims of this study were to determine normal inter-limb variance in the hand and four segments of the arm using bioimpedance spectroscopy (BIS) to provide diagnostic thresholds for detection of early lymphedema development, to determine the intra-rater reliability of these measurements, and to compare the inter-limb BIS ratios to differences based on arm circumference measures.
Methods And Results: One hundred women, aged 49.1 (SD 13.8) years without history of breast cancer or lymphedema participated. Impedance measures for the hand and four 10 cm length arm segments were used to determine the inter-limb segment BIS ratios. Circumference difference and segment volumes were calculated from circumference measures obtained with a tape measure. A subgroup of women was measured on two occasions, one week apart. Thresholds were determined for the dominant and nondominant limb, based on two and three standard deviations (SD) above the mean. The 2SD and 3SD thresholds for the dominant arm ranged from 1.121 to 1.150 and 1.172 to 1.209, respectively, and for the nondominant limb ranged from 1.057 to 1.107 and 1.103 to 1.169, respectively. Intra-rater reliability was high (ICC: 0.945-0.983). BIS ratio and circumference-based measures did not identify the same segments as being over threshold.
Conclusions: BIS diagnostic thresholds for the hand and four segments of the arm, based on normative data, taking into consideration arm dominance have been developed. Segmental BIS has been shown to be highly reliable.
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http://dx.doi.org/10.1089/lrb.2013.0050 | DOI Listing |
J Med Internet Res
January 2025
Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Background: Patients undergoing liver transplantation (LT) are at risk of perioperative neurocognitive dysfunction (PND), which significantly affects the patients' prognosis.
Objective: This study used machine learning (ML) algorithms with an aim to extract critical predictors and develop an ML model to predict PND among LT recipients.
Methods: In this retrospective study, data from 958 patients who underwent LT between January 2015 and January 2020 were extracted from the Third Affiliated Hospital of Sun Yat-sen University.
Invest Ophthalmol Vis Sci
January 2025
State Key Laboratory of Ophthalmology, Optometry, and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Purpose: Changes associated with Alzheimer's disease (AD) may have measurable effects on the retina, which may facilitate early detection due to the eye's accessibility. Retinal pathology and the regulation of serine racemase (SR) were investigated in the retinas of APP(SW)/PS1(∆E9) mice.
Methods: SR in the retinas and the content of D-serine in the aqueous humor were analyzed.
JAMA Netw Open
January 2025
Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Importance: Lung cancer in individuals who have never smoked (INS) is a growing global concern, with a rapidly increasing incidence and proportion among all lung cancer cases. Particularly in East Asia, opportunistic lung cancer screening (LCS) programs targeting INS have gained popularity. However, the sex-specific outcomes and drawbacks of screening INS remain unexplored, with data predominantly focused on women.
View Article and Find Full Text PDFPurpose Of Review: The 2024 mpox outbreak, primarily driven by the possibly more virulent clade Ib strain, prompted the WHO declaring it a public health emergency of international concern (PHEIC) on August 14, 2024. This review provides essential guidance for clinicians managing mpox cases, as it contrasts the features of the 2024 outbreak with those of the 2022 epidemic to support better clinical decision-making.
Recent Findings: The review highlights significant differences between the 2024 and 2022 outbreaks, including total case numbers, demographic distribution, and fatality rates.
Clin Exp Nephrol
January 2025
Kawasaki Medical School, Department of Nephrology and Hypertension, Kurashiki, Japan.
Background: Chronic kidney disease (CKD) represents a significant public health challenge, with rates consistently on the rise. Enhancing kidney function prediction could contribute to the early detection, prevention, and management of CKD in clinical practice. We aimed to investigate whether deep learning techniques, especially those suitable for processing missing values, can improve the accuracy of predicting future renal function compared to traditional statistical method, using the Japan Chronic Kidney Disease Database (J-CKD-DB), a nationwide multicenter CKD registry.
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