Digital X-ray radiogrammetry of hand or wrist radiographs can predict hip fracture risk—a study in 5,420 women and 2,837 men
To assess whether digital X-ray radiogrammetry (DXR) analysis of standard clinical hand or wrist radiographs obtained at emergency hospitals can predict hip fracture risk.
A total of 45,538 radiographs depicting the left hand were gathered from three emergency hospitals in Stockholm, Sweden. Radiographs with insufficiently included metacarpal bone, fractures in measurement regions, foreign material or unacceptable positioning were manually excluded. A total of 18,824 radiographs from 15,072 patients were analysed with DXR, yielding a calculated BMD equivalent (DXR-BMD). Patients were matched with the national death and inpatient registers. Inclusion criteria were age ≥ 40 years, no prior hip fracture and observation time > 7 days. Hip fractures were identified via ICD-10 codes. Age-adjusted hazard ratio per standard deviation (HR/SD) was calculated using Cox regression.
8,257 patients (65.6 % female, 34.4 % male) met the inclusion criteria. One hundred twenty-two patients suffered a hip fracture after their radiograph. The fracture group had a significantly lower DXR-BMD than the non-fracture group when adjusted for age. The HR/SD for hip fracture was 2.52 and 2.08 in women and men respectively. The area under the curve was 0.89 in women and 0.84 in men.
DXR analysis of wrist and hand radiographs obtained at emergency hospitals predicts hip fracture risk in women and men.
• Digital X-ray radiogrammetry of emergency hand/wrist radiographs predicts hip fracture risk.
• Digital X-ray radiogrammetry (DXR) predicts hip fracture risk in both women and men.
• Osteoporosis can potentially be identified in patients with suspected wrist fractures.
• DXR can potentially be used for selective osteoporosis screening.
- Digital X-ray radiogrammetry of hand or wrist radiographs can predict hip fracture risk—a study in 5,420 women and 2,837 men
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Volume 23, Issue 5 , pp 1383-1391
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- Hip fracture
- Digital X-ray radiogrammetry
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- Author Affiliations
- 1. Karolinska Institutet, Department for Clinical Science, Intervention and Technology, Division of Radiology, Karolinska University Hospital, Stockholm, Sweden
- 6. Frejgatan 34, 113 26, Stockholm, Sweden
- 2. Sectra Imtec AB, Linköping, Sweden
- 3. Centre for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- 4. Department of Medicine Solna, Unit of Clinical Epidemiology, Karolinska Institutet, Stockholm, Sweden
- 5. Kermanshah University of Medical Sciences, Kermanshah, Islamic Republic of Iran