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PubMed Publications| Keyword search (4,163 papers available) |  |
"isk assessment" Keyword-tagged Publications:
| Title: | Simultaneous automated ascertainment of prevalent vertebral fracture and abdominal aortic calcification in clinical practice: role in fracture risk assessment | ||||
| Authors: | Schousboe JT, Lewis JR, Monchka BA, Reid SB, Davidson MJ, Kimelman D, Jozani MJ, Smith C, Sim M, Gilani SZ, Suter D, Leslie WD | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/38699950/ | ||||
| DOI: | 10.1093/jbmr/zjae066 | ||||
| Publication: | Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research | ||||
| Keywords: | DXA; Fracture Risk Assessment; General Population Studies; Osteoporosis; Screening; | ||||
| PMID: | 38699950 | Category: | Date Added: | 2024-05-03 | |
| Dept Affiliation: |
ENCS
1 Park Nicollet Clinic and HealthPartners Institute, Minneapolis MN. 2 Division of Health Policy and Management, University of Minnesota, Minneapolis MN. 3 Nutrition & Health Innovation Research Institute, Edith Cowan University, Perth, Australia. 4 Medical School, University of Western Australia, Perth, Australia. 5 Centre for Kidney Research, School of Public Health, The University of Sydney, Sydney. 6 George & Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg. 7 Department of Computer Science, Concordia University, Montreal, Canada. 8 Department of Medicine, University of Manitoba, Winnipeg, Canada. 9 Department of Statistics, University of Manitoba, Winnipeg, Canada. 10 Centre for AI & ML, School of Science, Edith Cowan University, Perth, Australia. 11 Computer Science and Software Engineering, University of Western Australia, Perth. |
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Description: |
Whether simultaneous automated ascertainments of prevalent vertebral fracture (auto-PVFx) and abdominal aortic calcification (auto-AAC) on vertebral fracture assessment (VFA) lateral spine bone density (BMD) images jointly predict incident fractures in routine clinical practice is unclear. We estimated the independent associations of auto-PVFx and auto-AAC primarily with incident major osteoporotic and secondarily with incident hip and any clinical fractures in 11 013 individuals (mean [SD] age 75.8 [6.8] years, 93.3% female) who had a BMD test combined with VFA between March 2010 and December 2017. Auto-PVFx and auto-AAC were ascertained using convolutional neural networks (CNNs). Proportional hazards models were used to estimate the associations of auto-PVFx and auto-AAC with incident fractures over a mean (SD) follow-up of 3.7 (2.2) years, adjusted for each other and other risk factors. At baseline, 17% (n = 1881) had auto-PVFx and 27% (n = 2974) had a high level of auto-AAC (= 6 on scale of 0 to 24). Multivariable-adjusted hazard ratios (HR) for incident major osteoporotic fracture (95% C.I.) were 1.85 (1.59, 2.15) for those with compared to those without auto-PVFx, and 1.36 (1.14, 1.62) for those with high compared to low auto-AAC. The multivariable-adjusted HRs for incident hip fracture were 1.62 (95% C.I. 1.26 to 2.07) for those with compared to those without auto-PVFx, and 1.55 (95% C.I. 1.15 to 2.09) for those high auto-AAC compared to low auto-AAC. The 5-year cumulative incidence of major osteoporotic fracture was 7.1% in those with no auto-PVFx and low auto-AAC, 10.1% in those with no auto-PVFx and high auto-AAC, 13.4% in those with auto-PVFx and low auto-AAC, and 18.0% in those with auto-PVFx and high auto-AAC. While physician manual review of images in clinical practice will still be needed to confirm image quality and provide clinical context for interpretation, simultaneous automated ascertainment of auto-PVFx and auto-AAC can aid fracture risk assessment. |
