General Practitioner and FRAX (computer-based algorithm)
Osteoporotic fractures became the most important cause of disability and an increasing burden to the public health costs in Italy and in many regions of the world. Health professionals play a central role in identifying people at high risk of osteoporosis and osteoporotic fractures. However it is im...
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| Published in | Clinical cases in mineral and bone metabolism Vol. 11; no. 2; pp. 120 - 122 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Italy
CIC Edizioni Internazionali
01.05.2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1724-8914 1971-3266 1724-8914 1971-3266 |
| DOI | 10.11138/ccmbm/2014.11.2.120 |
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| Summary: | Osteoporotic fractures became the most important cause of disability and an increasing burden to the public health costs in Italy and in many regions of the world. Health professionals play a central role in identifying people at high risk of osteoporosis and osteoporotic fractures. However it is important to have available methods that allow to identify patients showing high risk of fragility fractures, with lower costs and high sensitivity than those currently adopted, e.g. Dual Energy X-ray Absorptiometry (DEXA). The computer-based algorithm (FRAX®) developed by WHO shows some barriers in primary care, for instance the difficulty to access this tool by General Practitioners (since it is not available in their DATABASE). Moreover, since the incidence of fracture and the prevalence of associated risk factors change over time, risk prediction algorithms need to be dynamic, so that they can be remodelled over time. In Italy, the Health Search - CSD Longitudinal Patients Database (HSD) could potentially provide the data needed to support the development and validation of an applicable prediction tool in primary care. In this framework we aim to develop and validate a prognostic score for osteoporotic fractures in Italian General Practice and to establish a risk map. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1724-8914 1971-3266 1724-8914 1971-3266 |
| DOI: | 10.11138/ccmbm/2014.11.2.120 |