Literature DB >> 18936788

Common mistakes in the clinical use of bone mineral density testing.

E Michael Lewiecki1, Nancy E Lane.   

Abstract

Bone mineral density (BMD) testing is used to diagnose osteoporosis, assess fracture risk and monitor changes in BMD over time. A variety of devices and technologies are used to measure BMD or other surrogate markers of bone strength. Measurements obtained with these devices are often reported according to different proprietary standards, and the comparability of values obtained with different instruments is often poor. In addition, there is a high degree of variability in the skills of the technologists performing the tests and the clinicians interpreting the results. Heterogeneity in the guidelines for using BMD measurements together with poor-quality BMD testing and reporting can result in inappropriate clinical decisions, causing unnecessary worry and expense for the patient and possible harm due to unnecessary treatment or treatment being withheld. This Review describes and discusses the mistakes commonly made in BMD testing, and emphasizes the importance of maintaining high-quality standards in order to optimize patient management.

Entities:  

Mesh:

Year:  2008        PMID: 18936788      PMCID: PMC3891842          DOI: 10.1038/ncprheum0928

Source DB:  PubMed          Journal:  Nat Clin Pract Rheumatol        ISSN: 1745-8382


  23 in total

1.  Enhanced precision with dual-energy X-ray absorptiometry.

Authors:  R Mazess; C H Chesnut; M McClung; H Genant
Journal:  Calcif Tissue Int       Date:  1992-07       Impact factor: 4.333

Review 2.  Meta-analyses of therapies for postmenopausal osteoporosis. I. Systematic reviews of randomized trials in osteoporosis: introduction and methodology.

Authors:  Ann Cranney; Peter Tugwell; George Wells; Gordon Guyatt
Journal:  Endocr Rev       Date:  2002-08       Impact factor: 19.871

3.  Peripheral dual-energy X-ray absorptiometry in the management of osteoporosis: the 2007 ISCD Official Positions.

Authors:  Didier B Hans; John A Shepherd; Elliott N Schwartz; David M Reid; Glen M Blake; John N Fordham; Thomas Fuerst; Peyman Hadji; Akira Itabashi; Marc-Antoine Krieg; E Michael Lewiecki
Journal:  J Clin Densitom       Date:  2008 Jan-Mar       Impact factor: 2.617

Review 4.  Update on bone density testing.

Authors:  E Michael Lewiecki
Journal:  Curr Osteoporos Rep       Date:  2005-12       Impact factor: 5.096

Review 5.  Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group.

Authors: 
Journal:  World Health Organ Tech Rep Ser       Date:  1994

Review 6.  Premenopausal bone health assessment.

Authors:  E Michael Lewiecki
Journal:  Curr Rheumatol Rep       Date:  2005-03       Impact factor: 4.592

Review 7.  Radiation exposure in bone mineral density assessment.

Authors:  C F Njeh; T Fuerst; D Hans; G M Blake; H K Genant
Journal:  Appl Radiat Isot       Date:  1999-01       Impact factor: 1.513

8.  Fracture prediction for the proximal femur using finite element models: Part I--Linear analysis.

Authors:  J C Lotz; E J Cheal; W C Hayes
Journal:  J Biomech Eng       Date:  1991-11       Impact factor: 2.097

9.  Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures.

Authors:  D Marshall; O Johnell; H Wedel
Journal:  BMJ       Date:  1996-05-18

Review 10.  What is the role of serial bone mineral density measurements in patient management?

Authors:  Leon Lenchik; Gary M Kiebzak; Barbara A Blunt
Journal:  J Clin Densitom       Date:  2002       Impact factor: 2.963

View more
  16 in total

Review 1.  Osteoporosis: Treat-to-Target.

Authors:  E Michael Lewiecki
Journal:  Curr Osteoporos Rep       Date:  2017-04       Impact factor: 5.096

Review 2.  Augmenting Osteoporosis Imaging with Machine Learning.

Authors:  Valentina Pedoia; Francesco Caliva; Galateia Kazakia; Andrew J Burghardt; Sharmila Majumdar
Journal:  Curr Osteoporos Rep       Date:  2021-12       Impact factor: 5.096

3.  Reverse engineering the FRAX algorithm: Clinical insights and systematic analysis of fracture risk.

Authors:  Jules D Allbritton-King; Julia K Elrod; Philip S Rosenberg; Timothy Bhattacharyya
Journal:  Bone       Date:  2022-02-28       Impact factor: 4.626

4.  Pelvic floor disorder symptoms and bone strength in postmenopausal women.

Authors:  Isuzu Meyer; Sarah L Morgan; Alayne D Markland; Jeff M Szychowski; Holly E Richter
Journal:  Int Urogynecol J       Date:  2020-02-29       Impact factor: 2.894

5.  Effects of clinical reanalysis in dual energy X-ray absorptiometry reports.

Authors:  Filiz Tuna; Selçuk Yavuz; Derya Demirbağ Demirbağ Kabayel; Ali Sarıkaya
Journal:  Turk J Phys Med Rehabil       Date:  2017-05-16

6.  The facial skeleton in patients with osteoporosis: a field for disease signs and treatment complications.

Authors:  Athanassios Kyrgidis; Thrasivoulos-George Tzellos; Konstantinos Toulis; Konstantinos Antoniades
Journal:  J Osteoporos       Date:  2011-02-16

7.  Fracture risk assessment after BMD examination: whose job is it, anyway?

Authors:  S Allin; S Munce; L Carlin; D Butt; K Tu; G Hawker; J Sale; S Jaglal
Journal:  Osteoporos Int       Date:  2014-03-08       Impact factor: 4.507

8.  Assessment of osteoporotic fracture risk in urban Indian population using quantitative ultrasonography & FRAX tool.

Authors:  Raju Vaishya; Vipul Vijay; Amit K Agarwal; Prashant Maheshwari
Journal:  Indian J Med Res       Date:  2017-11       Impact factor: 2.375

9.  A Transmission-Based Dielectric Property Probe for Clinical Applications.

Authors:  Paul Meaney; Tomas Rydholm; Helena Brisby
Journal:  Sensors (Basel)       Date:  2018-10-16       Impact factor: 3.576

10.  Bone health in elite Norwegian endurance cyclists and runners: a cross-sectional study.

Authors:  Oddbjørn Klomsten Andersen; Benjamin Clarsen; Ina Garthe; Morten Mørland; Trine Stensrud
Journal:  BMJ Open Sport Exerc Med       Date:  2018-12-27
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.