Literature DB >> 11716183

Identifying bone-mass-related risk factors for fracture to guide bone densitometry measurements: a systematic review of the literature.

M Espallargues1, L Sampietro-Colom, M D Estrada, M Solà, L del Rio, J Setoain, A Granados.   

Abstract

Available evidence suggests that fracture prediction with bone densitometry may improve when used on people at high risk of osteoporotic fractures. The objectives of this literature review were: (1) to identify risk factors for fracture that are associated with the development of a low bone mass for both men and women; (2) to describe and assess the relationship between these factors and the risk of fracture; and (3) to classify them according to the strength of their association with fracture incidence. Studies were identified from MEDLINE (1982-1997), HealthSTAR (1975-1997) and The Cochrane Library (1997) databases. Pre-stated inclusion criteria (original analytic studies assessing risk factors for osteoporotic fractures in men and women) and methodologic quality were assessed by two independent investigators. Information on the study design and analysis, characteristics of participants, exposure (risk factor) and outcome measures (relative risk and odds ratios for fracture incidence), control for potential confounding factors and risk estimates was extracted using a standardized protocol. Qualitative and meta-analytic techniques were used for data synthesis. As a result, risk factors were classified into three groups according to their strength of association with fracture: high risk (RR > or = 2), moderate risk (1 < RR < 2) and no risk or protective (RR < or = 1). Of approximately 80 risk factors identified from 94 cohort and 72 case-control studies, 15% were classified in the high-risk group, including low body weight, loss of weight, physical inactivity, the consumption of corticosteroids or anticonvulsants, primary hyperparathyroidism, diabetes mellitus type 1, anorexia nervosa, gastrectomy, pernicious anemia, and aging (> 70-80 years). Eighteen percent and 8% of risk factors were classified in the moderate and no risk group respectively, whereas 60% showed either a lack of scientific evidence confirming their association with fracture or contradictory results. An efficient strategy for bone densitometry provision may thus be its selective use in those individuals who present with several strong or moderate risk factors for fracture related to bone mass loss.

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Year:  2001        PMID: 11716183     DOI: 10.1007/s001980170031

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


  67 in total

Review 1.  Preventing fractures in elderly people.

Authors:  Anthony D Woolf; Kristina Akesson
Journal:  BMJ       Date:  2003-07-12

2.  Young patients with hip fracture: a population-based study of bone mass and risk factors for osteoporosis.

Authors:  C M Lofthus; E K Osnes; H E Meyer; I S Kristiansen; L Nordsletten; J A Falch
Journal:  Osteoporos Int       Date:  2006-08-29       Impact factor: 4.507

3.  Performance of four clinical screening tools to select peri- and early postmenopausal women for dual X-ray absorptiometry.

Authors:  B Rud; J E B Jensen; L Mosekilde; S P Nielsen; J Hilden; B Abrahamsen
Journal:  Osteoporos Int       Date:  2004-09-30       Impact factor: 4.507

4.  Lordoplasty: report on early results with a new technique for the treatment of vertebral compression fractures to restore the lordosis.

Authors:  Rene Orler; Lars H Frauchiger; Uta Lange; Paul F Heini
Journal:  Eur Spine J       Date:  2006-05-25       Impact factor: 3.134

5.  Low holotranscobalamin and cobalamins predict incident fractures in elderly men: the MrOS Sweden.

Authors:  C Lewerin; H Nilsson-Ehle; S Jacobsson; H Johansson; V Sundh; M K Karlsson; Ö Ljunggren; M Lorentzon; J A Kanis; U H Lerner; S R Cummings; C Ohlsson; D Mellström
Journal:  Osteoporos Int       Date:  2013-10-16       Impact factor: 4.507

6.  A triage strategy based on clinical risk factors for selecting elderly women for treatment or bone densitometry: the EPIDOS prospective study.

Authors:  P Dargent-Molina; S Piault; G Bréart
Journal:  Osteoporos Int       Date:  2004-11-27       Impact factor: 4.507

Review 7.  A new perspective on mechanisms governing skeletal complications in type 1 diabetes.

Authors:  Zeynep Seref-Ferlengez; Sylvia O Suadicani; Mia M Thi
Journal:  Ann N Y Acad Sci       Date:  2016-08-29       Impact factor: 5.691

Review 8.  Perspectives on osteoporosis in pediatric inflammatory bowel disease.

Authors:  Manisha Harpavat; David J Keljo
Journal:  Curr Gastroenterol Rep       Date:  2003-06

Review 9.  Osteoporosis in men.

Authors:  Sundeep Khosla; Shreyasee Amin; Eric Orwoll
Journal:  Endocr Rev       Date:  2008-05-01       Impact factor: 19.871

10.  Forearm bone mineral density in an unselected population of 2,779 men and women--the HUNT Study, Norway.

Authors:  Siri Forsmo; Arnulf Langhammer; Lisa Forsen; Berit Schei
Journal:  Osteoporos Int       Date:  2004-09-22       Impact factor: 4.507

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