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Abstract

Abstract: The aim of our research is to determine the risk of bone disease in hypercalciuric kidney stone formers and their families by establishing an algorithm that takes into account bone mineral density (BMD), demographic characteristics diet history, and urine and serum chemistries, including markers of bone turnover. The algorithm will allow us to determine which hypercalciurics need clinical evaluation for osteoporosis and will form the basis of a disease management product. In the process of creating this algorithm, we will be the first to determine the prevalence of bone disease in hypercalciuric stone formers and their families and over time make some estimates of incidence rates. A longer- term goal of our research is to study the genetic underpinnings of osteoporosis and nephrolithasis in these families. PROPOSED COMMERCIAL APPLICATIONS: Litholink provides disease management services for kidney stone patients. We hope to use the algorithm developed in this research to expand out services to include bone disease management in kidney stone forming patients and their families.

Thesaurus Terms:
artificial intelligence, bone density, disease /disorder proneness /risk, hypercalciuria, nephrocalcinosis, nephrolithiasis, osteoporosis
computer program /software, computer system design /evaluation, human population study, mathematical model
clinical research, human subject, photon absorptiometry

Institution:	LITHOLINK CORPORATION
	2250 W CAMPBELL PARK DR
	CHICAGO, IL 60612
Fiscal Year:	2002
Department:
Project Start:	01-MAY-2002
Project End:	30-APR-2004
ICD:	NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
IRG:	ZRG1