Background: Vitamin D deficiency is common in obese adolescents and a risk factor for insulin resistance. We investigated if prevailing serum 25-OH vitamin D might predict the body fat loss in a group of obese adolescents undergoing a residential weight loss program.
Methods: In 92 (35 male) obese adolescents (aged 10.6-19 years) undergoing a residential weight loss program in Belgium, fasting serum 25-OH vitamin D (25-OH-D), insulin, glucose and lipid levels were measured and body composition was assessed by dual-energy X-ray absorptiometry (DXA).
Results: Baseline median (range) serum 25-OH-D level was 17.7 µg/L (3.8-41.8). In total, 55 adolescents had a serum 25-OH-D below 20 µg/L. In 31 adolescents with a low baseline 25-OH-D level, median increase in serum 25-OH-D was 2.4 µg/L (-4.2 to 7.2) after 10 months. This resulted in normal 25-OH-D levels in seven adolescents, whereas median BMI decreased with 1.0 SDS and body fat percentage diminished with 9.9%. Obese adolescents with or without a 25-OH-D level below or above 20 µg/L at baseline had similar changes in body weight, BMI SDS, body fat percentage and body fat mass at the end of the program. The change in serum 25-OH-D did not correlate with change in serum insulin, BMI SDS or body fat percentage and body fat mass.
Conclusion: Vitamin D deficiency was present in 55 out of 92 obese adolescents at the start of the summer. Serum 25-OH-D concentration did not predict changes in body fat loss after a residential weight loss program.
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http://dx.doi.org/10.1530/EC-19-0364 | DOI Listing |
Cancer Med
January 2025
The Huntsman Cancer Institute at the University of Utah, Salt Lake City, Utah, USA.
Introduction: The purpose of this study was to evaluate the association between body composition, overall survival, odds of receiving treatment, and patient-reported outcomes (PROs) in individuals living with metastatic non-small-cell lung cancer (mNSCLC).
Methods: This retrospective analysis was conducted in newly diagnosed patients with mNSCLC who had computed-tomography (CT) scans and completed PRO questionnaires close to metastatic diagnosis date. Cox proportional hazard models and logistic regression evaluated overall survival and odds of receiving treatment, respectively.
Eur Heart J Cardiovasc Imaging
January 2025
Sorbonne Université, unité d'imagerie cardiovasculaire et thoracique, Hôpital La Pitié Salpêtrière (AP-HP), Laboratoire d'Imagerie Biomédicale, INSERM, CNRS, Institute of Cardiometabolism and Nutrition, ACTION Group, Paris, France.
Purpose: Epicardial adipose tissue (EAT) could contribute to the specific atherosclerosis profile observed in premature coronary artery disease (pCAD) characterized by accelerated plaque burden (calcified and non-calcified), high risk plaque features (HRP) and ischemic recurrence. Our aims were to describe EAT volume and density in pCAD compared to asymptomatic individuals matched on CV risk factors and to study their relationship with coronary plaque severity extension and vulnerability.
Materials And Methods: 208 patients who underwent coronary computed tomography angiography (CCTA) were analyzed.
EClinicalMedicine
October 2024
Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Unity Health Toronto, Toronto, ON M5B 1W8, Canada.
Background: Use of health applications (apps) to support healthy lifestyles has intensified. Different app features may support effectiveness, including gamification defined as the use of game elements in a non-game situation. Whether health apps with gamification can impact behaviour change and cardiometabolic risk factors remains unknown.
View Article and Find Full Text PDFSarcopenia is defined as a muscle-wasting syndrome that occurs with accelerated aging, while cachexia is a severe wasting syndrome associated with conditions such as cancer and immunodeficiency disorders, which cannot be fully addressed through conventional nutritional supplementation. Sarcopenia can be considered a component of cachexia, with the bidirectional interplay between adipose tissue and skeletal muscle potentially serving as a molecular mechanism for both conditions. However, the underlying mechanisms differ.
View Article and Find Full Text PDFWorld J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
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