Studies of soft tissue body composition using single and dual photon absorptiometry.
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Bone mineral content (BMC) and bone mineral density (BMD) of lumbar spine have been measured in 695 healthy postmenopausal and 64 type I osteoporotic Belgian, Caucasian females. Bone loss is strongly correlated to time elapse from menopause (Tm) with a maximum rate of bone loss during the first five years of menopause. BMC (gHA) = 461 + 0.662 ln Tm -0.481 (ln Tm)2 and BMD (gHA/cm2) = 0.91 + 0.00711 ln Tm - 0.00846 (ln Tm)2 (in both cases p less than 0.001 and Tm expressed in months of menopause). After 20 years of menopause, 50 to 60% of normal women have vertebral BMC and BMD values below the 90th percentile of women with vertebral fractures and, thus, might be considered to have asymptomatic osteoporosis. We conclude that prevention of postmenopausal osteoporosis should be initiated as soon as possible after the onset of menopause and that bone density screening should be extended in elderly in order to detect and allow treatment of asymptomatic "densitometric" osteoporosis.
Examining the bone mineral density (BMD's) slope of patients regularly followed in our department, we observed recently that the group of patients who had their last BMD during the last 6 months of 1989, had a different slope than patients who had their last BMD during the following 6 months. In order to investigate if a small time-related bias of measurement, unsuspected by the former quality control investigations, could exist, we performed the following analyses. A regression equation between BMD and time was calculated and a slope was obtained for 95 women who had been followed for at least 3 yr and had had at least 3 BMD measurements during that time. The women were divided in 3 groups according to when the last BMD measurement had been performed (July-December 1989, January-June 1990 or July-December 1990). The slopes of the 3 groups of patients were compared. For each value of BMD of every patient, a predicted BMD (BMDp) was calculated using the regression equation and the relative difference (RD) between BMDp and BMD was calculated and analysed in relation to time. There was a significant difference (p < 0.05) between the slopes of patients in relation to the time when the last BMD had been measured. Significant fluctuations (p < 0.001) in RD were observed in relation to time. These RD variations suggested the existence of a time-related error. The presence of this error is also substantiated by the fact that a parallelism existed between the curve of the RD variations and the curve of the mean values of BMD of all patients referred to our department, calculated per period of 4 months. Although the fluctuation of the latter curve was not statistically significant.(ABSTRACT TRUNCATED AT 250 WORDS)
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STUDY OBJECTIVE: To determine whether clinically available data on risk factors are adequate to identify perimenopausal women with either low or high bone mass. DESIGN: Cross-sectional observational study of a cohort of perimenopausal women (mean age, 50.8 years). SETTING: Community volunteers in a university hospital. SUBJECTS: One hundred twenty-four white volunteers established as perimenopausal by history and serum concentrations of estrogens and follicle-stimulating hormone. MEASUREMENTS AND MAIN RESULTS: Models were constructed to predict bone mass in the radius, lumbar spine, and hip using risk factors (age, height, weight, calcium and caffeine intake, alcohol and tobacco use, and urinary markers of bone turnover). Although highly significant predictive models were developed for all skeletal sites, none of the models correctly identified more than 70% of women with low bone mass at any site. However, for the radius, a model was constructed that never overestimated bone mass by more than 0.10 g/cm. A small subgroup (7%) with short stature, low body weight, low calcium intake, and who were heavy smokers always had low radial bone mass. Using these models, about 30% of our population could be assessed without bone mass measurements. Predictions for the spine and femur were less efficient, suggesting that direct measurements are required if therapy decisions are to be based on bone mass at these sites. CONCLUSIONS: Risk factors for osteoporosis are of limited use in identifying women with low bone mass around the time of menopause. Measurements of bone mass are probably necessary if the risk for osteoporosis is to be the basis for deciding on estrogen replacement therapy.
Multivariate classification methods were used to create an early detection technique for determining bone density. This biochemical index (QuiOs) is clinically useful as a potential adjunct in identifying the presence of biochemical deficiencies known to cause osteopenia and the devastating effects of osteoporosis. The test uses the following serum concentrations of a predetermined set of blood constituents: calcium, phosphorus, alkaline phosphatase (ALP), two alkaline phosphatase isoenzymes (liver and intestine), estradiol, and progesterone. Using the results of these six biochemical and hormonal tests, a correlation equation was developed that demonstrates a nonlinear relationship between QuiOs and Ward's triangle of DPA. A sensitivity of 86% and a specificity of 80% was demonstrated for this biochemical index against DPA in this clinical trial.
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We have evaluated, in a prospective study, the total and per unit area mass, measured in lumbar spine by Dual Photo-absorptiometry, in a group of 62 children on long-term anticonvulsant treatment. A second group of 58 normal children was used as a control. The total and per unit area bone mass increased with age, weight, height and bone maturity in all of the children studied. There were no significant differences found between the two groups. Children on multi-therapy and that were over six years of age showed statistically significantly less bone mass per area when compared th the control group (p less than 0.01). Phenobarbital, Carbamazepine and Valproic acid in monotherapy did not statistically diminish bone mass. Of these anticonvulsants, Phenobarbital was responsible for the most statistically significant decline in bone mass per area (p = 0.027). After six year of treatment, whether on mono-therapy or on poly-therapy, bone mass was lower with respect to the control series, although this was not statistically significant.
Biphotonic absorptiometry has begun to demonstrate its usefulness in the field of osteoporosis. In algodystrophy, the radiology and the degree of isotopic fixation suggest a bone disorder, although both techniques are unable to objectively quantify it. Biphotonic absorption is an scanning technique which allows the quantification of bone demineralization in the segment affected by algodystrophy and its evolutive follow-up.
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