Searchable abstracts of presentations at key conferences on calcified tissues
Bone Abstracts (2019) 7 P86 | DOI: 10.1530/boneabs.7.P86

ICCBH2019 Poster Presentations (1) (226 abstracts)

Disease-specific pathological traits of youth at risk of secondary osteoporosis as determined through peripheral Quantitative Computed Tomography

Paola Chivers 1, , Mark Jenkins 2 , Nicolas Hart 1, , Timo Rantalainen 1, , Fleur McIntyre 1 , Beth Hands 1 , Sophia Nimphius 2 , Karen Rothacker 4 , Belinda Beck 5 , Benjamin Weeks 5 , Brendan Beeson 4 & Aris Siafarikas 1,


1The University of Notre Dame Australia/Institute for Health Research, Fremantle, Australia; 2Edith Cowan University, Joondalup, Australia; 3University of Jyvaskyla, Jyvaskyla, Finland; 4Perth Children’s Hospital, Nedlands, Australia; 5Griffith University, Brisbane, Australia.


Objectives: This cross-sectional observational study examined peripheral long bone material and structural differences in youth at risk of secondary osteoporosis across disease-specific profiles using peripheral Quantitative Computed Tomography (pQCT).

Methods: Scans of the upper (radius; ulna) and lower (tibia; fibula) limbs of children at 4% distal and 66% mid-shaft sites were undertaken using pQCT. Specific groups were those with (1) increased risk of secondary osteoporosis (neuromuscular disorders [cerebral palsy, Duchenne Muscular Dystrophy and Prolonged immobilisation]; chronic diseases; endocrine diseases; inborn errors of metabolism; iatrogenic conditions), (2) developmental coordination disorder or low motor competence and (3) non-affected controls. Bone outcome parameters included cortical density (CoD), cortical area (CoA), stress-strain index (SSI), total area (ToA), bone strength index (BSI), muscle density (MuD), muscle area (MuA), subcutaneous fat area, fat percentage, endocortical radius, pericortical radius, mid-cortical ring density and trabecular density. General linear models (GLM) with Bonferroni adjustment, controlling for age, sex and bone length examined disease group differences.

Results: Compared to the non-affected controls, children with neuromuscular disorders, developmental coordination disorder or low motor competence had significantly poorer bone parameter outcomes. CoA was significantly lower to the control group for all eight bone sites, with pericortical radius, SSI, ToA, and BSI significantly lower to the control group for seven of the eight bone sites. Endocortical radius, MuA, and mid-cortical ring density were not significantly different to the control group for any bone sites. Other chronic diseases did not show significant differences although small samples were noted for disease groups inborn errors of metabolism (n=5) and iatrogenic conditions (n=12), despite the 5-year study period.

Conclusion: Neuromuscular disorders and the presence of low motor competence have a strong correlation to bone health for regional appendicular bone parameters in youth at risk of secondary osteoporosis, which suggest a mechanical loading influence. Given that effects of mechanical loading can be seen in regional bone analyses, we conclude that detailed characterisation of peripheral bone health using pQCT has the potential to identify areas for targeted exercise interventions to optimise bone health particularly in patients who present for treatment for other diseases and disorders.

Disclosure: The authors declared no competing interests.

Volume 7

9th International Conference on Children's Bone Health

ICCBH 

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