• Tuberculosis and Respiratory Diseases
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• v.47 no.1
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• pp.90-96
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• 1999

Background : Osteoporosis has been reported in patients with chronic obstructive pulmonary disease, but this association is not well established. This study was undertaken to determine whether the prevalence of osteoporosis was increased in patients with chronic obstructive pulmonary disease and we examined the relationship of corticosteroid administration with osteoporosis. Method: Subjects were 23 patients with chronic obstructive pulmonary disease and 20 control patients. We reviewed hospital records and measured bone mineral density using dual-energy x-ray absorptiometry(Lunar. USA). Results: Mean bone mineral density(BMD) of spine in COPD group was $0.683{\pm}0.154 g/cm^2$ and $0.971{\pm}0.212g/cm^2$ in controls(p<0.01). But there was no significant difference in femoral neck BMD. There were seventeen cases of osteoporosis and six cases of osteopenia in COPD group and three patients of osteoporosis and one case of osteopenia in controls. But, there was no significant correlation between disease duration of COPD and spinal T score(r=-0.395, p>0.05). Ten patients were received corticosteroid in COPD group. Spinal T score in steroid receiving patients were $-3.82{\pm}0.94(SD)$ and $-2.82{\pm}0.97(SD)$ in not having steroid patients(p<0.01). Cumulative dose of corticosteroid was associated with spinal T score(r=-0.424, p<0.05) and duration of corticosteroid administration also associated with spinal T score(r=-0.457. p<0.05). Spinal BMD of patients not having corticosteroid in COPD group(n=13) were significantly lower than that of controls($0.71{\pm}0.13 g/cm^2$ and $0.97{\pm}0.21 g/cm^2$, p<0.01). Conclusion : Prevalence of osteoporosis is increased in patients with chronic obstructive pulmonary disease. Especially patients who are receiving corticosteroid have high risk of osteoporosis or osteopenia and need for preventive management.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.1
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• pp.107-113
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• 2004

This study explored the association between the bone nutrition indicators and the bone mineral density (BMD) in 138 apparently healthy elderly (male: 38, female: 100) dwelling in a low income area of the city. Dietary intakes were estimated from two meals (breakfast ＆ dinner) and snack using 24 hr-recall method and lunch with weighing over 3 consecutive days. Female elderly showed significant lower intakes (p<0.001∼p<0-05) for most of the nutrients except calcium and vitamin C than the elderly male. Calcium and vitamin D intakes for both male and female were 331.0 mg, 1.89 $\mu\textrm{g}$ and 308.6 mg, 1.21 $\mu\textrm{g}$, respectively and they were below the 50% of the RDA. Both the BMDs at lumbar spine (LS) and femoral neck (FN) were positively correlated with the energy intake, calcium intake and vitamin D intake (p<0.05, respectively) for male. In female BMDs of the both sites were positively correlated with the intakes of carbohydrates, protein, lipid, calcium and vitamin D (p<0.01∼p<0.05). Female showed higher serum osteocalcin (p<0.01) and urinary deoxypyridinoline/creatinine (DPYR/CR) (p<0.001), meaning that female had elevated rate in bone turn over and bone resorption. The proportion of subjects with vitamin D deficiency assessed with serum 25(OH)VitD$_3$<10 mg/mL was 35.0% for female and 23.7% for male, respectively Both the BMDs at lumbar spine and trochanter were positively correlated with serum 25(OH)VitD$_3$ but BMDs in most of the sites were negatively associated with urinary DPYR/CR, phosphate/CR. Stepwise multiple regression showed physical activity, serum alkaline phosphatase, weight, vitamin D explained 47.6% of the variation of the LS BMD. The indicator variable for serum alkaline phosphatase was negatively associated with LS BMD. However, the indicator variable for weight and vitamin D intake were positive and significant (p=0.0087, p=0.0007, respectively). For FN BMD, the indicator variable for age and serum alkaline phosphatase were negative and significant (p<0.0075, p<0.0015, respectively) and the weight was positively associated with the FN BMD.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.