Explore chapters and articles related to this topic
Osteoporosis
Published in Jason Liebowitz, Philip Seo, David Hellmann, Michael Zeide, Clinical Innovation in Rheumatology, 2023
Mazen Nasrallah, Marcy B. Bolster
The diagnosis of osteoporosis currently relies on the use of imaging techniques to quantify bone mineral content and bone area. DXA imaging is the most used tool to diagnose osteopenia and osteoporosis among patients who are identified to be at higher risk of bone mass loss due to age or other risk factors (e.g. long-term glucocorticoid use, hypogonadism).
Trace Minerals
Published in Luke R. Bucci, Nutrition Applied to Injury Rehabilitation and Sports Medicine, 2020
Analysis of other patients exhibiting slow bone healing also found abnormally low serum levels of manganese, zinc, and copper. These anecdotal case studies spurred a collaborative effort with Dr. Reginster at the Medical School of the University of Liege in Belgium to examine serum and bone levels of trace minerals in postmenopausal osteoporotic women.924 Serum manganese in osteoporotic women was 0.01 ± 0.004 mg/1, whereas age-matched normal women exhibited serum manganese levels of 0.04 ± 0.03 mg/1, a significant difference. As expected, bone calcium, trabecular bone volume, bone mineral content, and bone mineral density were all significantly and substantially lower in the osteoporotic group. Interestingly, no differences between groups were found for serum levels of copper, zinc, bone Gla protein, and 1,25-dihydroxyvitamin D. While this study does not prove that manganese deficiency caused osteoporosis, it does provide further support along with other observations in animals and humans that a deficiency of manganese contributes to induction and progression of osteoporosis in humans.
Retrospect and Prospects
Published in Stanton H. Cohn, Non-Invasive Measurements of Bone Mass and Their Clinical Application, 2020
There is general agreement that an osteoporotic individual has a bone mineral content, 10 to 20% lower than a normal subject matched for age, size, and sex. About 18 to 30% of a population with clinically apparent osteoporosis have calcium levels that are not characterized as osteopenic by any of the non-invasive bone measurement techniques. Discriminant analysis using both the total body calcium and BMC values as predictor variables and membership in the two populations as criterion variables, appear to provide an adequate separation of osteoporotic and normal subjects.
Long-term changes of pancreatic function in patients with complicated walled-off necrosis
Published in Scandinavian Journal of Gastroenterology, 2022
Camilla Nøjgaard, Mikkel Werge, Astrid Naver, Anne Wilkens Knudsen, Nicolai J. Wewer Albrechtsen, Søren Møller, Lise Lotte Gluud, Srdan Novovic
Patients were evaluated at the time of the index endoscopy (baseline), 3–6 months after discharge and 12 months after discharge. None of the patients died during admission and follow-up. The patients were characterized with fecal elastase and fasting blood samples (HbA1c, C-peptide, plasma insulin, plasma glucose, plasma total amino acids, plasma glucagon and plasma cortisol). We determined both body composition as well as bone mineral content. Body composition (i.e., lean mass, fat mass and bone mineral density) was assessed by DXA-scan on a Lunar Prodigy scanner (GE Lunar, Madison, WI, USA) by trained technicians at Hvidovre University Hospital (Copenhagen, Denmark). Whole body DXA scans were performed using an iDXA fan beam densitometer (GE Lunar, Madison, WI, USA). The same scanner was used for all body scans and was carried out by one of three designated and trained technicians. Analyses of exams of patients were performed using Encore software version 16.0 [13].
The effects of methylphenidate on stress fractures in patients' ages 10–29: a national database study
Published in The Physician and Sportsmedicine, 2020
Steven F. DeFroda, Matthew Quinn, Daniel S. Yang, Alan H. Daniels, Brett D. Owens
These seemingly conflicting results have highlighted the need for further investigation into the role of MP on the bone health of active adults and how it impacts their risk for SF. Past authors have stated that MP protection against SFs may stem from an incomplete understanding of MP’s biochemical effect on adult bone. Specifically, authors suggest that bone mineral content may not entirely determine bone strength and that MP may provide unknown benefits for adult bone health [6]. Additionally, other authors have suggested that MP reduces high-risk behavior and thus reduces the incidence of SF [6,8]. Our study aimed to build upon the existing body of literature regarding adults on MP therapy for the treatment of their ADHD and their risk for SF. The hypothesis of our study is that individuals on MP therapy would have a reduced risk of SF when compared against controls not taking MP.
Association between high levels of gynoid fat and the increase of bone mineral density in women
Published in Climacteric, 2020
S. Aedo, J. E. Blümel, R. M. Carrillo-Larco, M. S. Vallejo, G. Aedo, G. G. Gómez, I. Campodónico
Dual-energy X-ray absorptiometry (Lunar Corporation, Madison, WI, USA) was performed on all study participants to measure whole and regional body composition. Percentage of fat mass, lean mass, and bone mineral content were measured. In addition, the BMD in both femoral necks was recorded. Determination of BMD in the vertebral spine was not used, to avoid any interference caused by osteoarthritis in the spine. The information retrieved included bone mineral content, mineral density, T-score, and Z-score, and was analyzed with the software provided by the manufacturer (version 4.7e). We calculated the appendicular lean mass as the sum of lean mass in the arms and legs11. Calibration for the measurement of BMD was performed using a phantom spine made of calcium hydroxyapatite and embedded in a lucite block. Scans of the phantom spine occurred every other day according to the manufacturer’s guidelines. The BMD values obtained from the calibration were stable over the entire study period (mean 0.991 g/cm2; coefficient of variation 0.08%).