In 100 patients with various types of endocrine dysfunction, we measured bone mineral density (BMD) at the midradius (greater than 95% cortical bone) and distal radius (75% cortical and 25% trabecular bone) by single photon absorptiometry and at the lumbar spine (greater than 66% trabecular bone) using the new technique of dual photon absorptiometry. BMD in each endocrine disorder deviated in at least one site from the sex-specific age regression of 187 normal subjects. For patients with primary hyperparathyroidism, hypercortisolism, and hyperthyroidism this deviation was negative (suggesting bone loss), whereas for patients with secondary hyperparathyroidism due to chronic renal failure, acromegaly, and postsurgical hypoparathyroidism it was positive (suggesting bone gain). When all six states of endocrine dysfunction were compared concomitantly by multivariate analysis of variance, the profile of the changes in BMD differed significantly (P less than 0.001), indicating a nonuniform response of bone to the various hormonal alterations. When values for BMD at each of the three scanning sites were compared the midradius and distal radius did not differ significantly; either of the radius measurements, however, differed significantly (P less than 0.001) from the lumbar spine. Thus, the BMD of the axial skeleton cannot be reliably predicted from measurements made in the appendicular skeleton. We conclude that the effects of endocrine dysfunction on bone density are complex and are both disease and site specific.
E Seeman, H W Wahner, K P Offord, R Kumar, W J Johnson, B L Riggs
Usage data is cumulative from January 2024 through January 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 259 | 2 |
60 | 44 | |
Scanned page | 232 | 1 |
Citation downloads | 38 | 0 |
Totals | 589 | 47 |
Total Views | 636 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.