
NEW YORK (Reuters Health), Sep 18 - Abnormal bone mineral density is common in children, adolescents, and young adults with epilepsy, Italian researchers have shown.
In the September issue of Epilepsia, Dr. Giangennaro Coppola, of Second University of Naples, and colleagues report on their assessment of bone mineral density in 96 patients with epilepsy and 63 controls between the ages of 3 and 25 years.
Among the patients, 47 (48.9%) had cerebral palsy and 66 (68.7%) had mental retardation. Fifty-seven patients (59.4%) could walk on their own, 11 (11.5%) walked with assistance, and 28 (29.1%) could not walk at all.
The average duration of epilepsy was 8.5 years, and the mean time on anticonvulsant therapy was 7.9 years.
Fifty-six patients (58.3%) had abnormal bone mineral density as measured by dual-energy x-ray absorptiometry (DEXA) scan of the lumbar spine (L1-L4), with osteopenia in 42 and osteoporosis in 14. There were significant differences between the patients and controls in bone mineral density, z score, and body mass index.
Furthermore, abnormal bone mineral density was significantly correlated with inability to walk independently, severe mental retardation, long duration of antiepileptic therapy, topiramate as adjunctive therapy, and less physical activity.
Cerebral palsy was also more frequently found in patients with abnormal bone mineral density, but not to a statistically significant extent.
Overall, the authors note, only two of the patients had "major clinical problems" related to low bone density, "which essentially consisted of fractures."
"To shed light on the individual role played by multiple independent risk factors that affect bone status, we are planning a study designed to compare the abnormal bone mineral density of epileptic patients ... not only with healthy children and adolescents, as we did in the present study, but also with nonepileptic children and adolescents, affected by cerebral palsy and mental retardation (both with and without autonomous gait)," the investigators maintain.
Epilepsia 2009;50:2140-2146.
Last Updated: 2009-09-16 18:39:03 -0400 (Reuters Health)
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![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)






