Literature DB >> 28756457

A comparison of electronic and manual fracture risk assessment tools in screening elderly male US veterans at risk for osteoporosis.

S T Williams1,2, P T Lawrence3, K L Miller4, J L Crook5, J LaFleur6, G W Cannon4, R E Nelson5.   

Abstract

This study compares four screening tools in their ability to predict osteoporosis. We found that there was no significant difference between the tools. These results provide support for the use of automated screening tools which work in conjunction with the electronic medical record and help improve screening rates for osteoporosis.
INTRODUCTION: The purpose of this study is to compare the performance of four fracture risk assessment tools (FRATs) in identifying osteoporosis by bone mineral density (BMD) T-score: Veterans Affairs Fracture Absolute Risk Assessment Tool (VA-FARA), World Health Organization's Fracture Risk Assessment Tool (FRAX), electronic FRAX (e-FRAX), and Osteoporosis Self-Assessment Screening Tool (OST).
METHODS: We performed a cross-sectional analysis of all patients enrolled in the VA Salt Lake City bone health team (BHT) who had completed a DXA scan between February 1, 2012, and February 1, 2013. DXA scan results were obtained by chart abstraction. For calculation of FRAX, osteoporosis risk factors were obtained from a screening questionnaire completed prior to DXA. For VA-FARA and e-FRAX, risk factors were derived from the electronic medical record (EMR). Clinical risk scores were calculated and compared against the gold standard of DXA-based osteoporosis. Sensitivity, specificity, and predictive values were calculated. Receiver operator characteristic (ROC) curves were plotted, and areas under the curve (AUC) were compared.
RESULTS: A cohort of 463 patients met eligibility criteria (mean age 80.4 years). One hundred twelve patients (24%) had osteoporosis as defined by DXA T-score ≤-2.5. Sensitivity, specificity, and predictive values were calculated. ROC statistics were compared and did not reach statistical significance difference between FRATs in identifying DXA-based osteoporosis.
CONCLUSIONS: Our study suggests that all FRATs tested perform similarly in identifying osteoporosis among elderly, primarily Caucasian, male veterans. If these electronic screening methods perform similarly for fracture outcomes, they could replace manual FRAX and thus improve efficiency in identifying individuals who should be sent for DXA scan.

Entities:  

Keywords:  FRAX; Fracture risk assessment tool; Osteoporosis; Screening

Mesh:

Year:  2017        PMID: 28756457     DOI: 10.1007/s00198-017-4172-3

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


  24 in total

Review 1.  The Osteoporosis Self-Assessment Tool versus alternative tests for selecting postmenopausal women for bone mineral density assessment: a comparative systematic review of accuracy.

Authors:  B Rud; J Hilden; L Hyldstrup; A Hróbjartsson
Journal:  Osteoporos Int       Date:  2008-08-21       Impact factor: 4.507

Review 2.  Systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for osteoporosis or low bone density.

Authors:  S Nayak; D L Edwards; A A Saleh; S L Greenspan
Journal:  Osteoporos Int       Date:  2015-02-03       Impact factor: 4.507

3.  Postmenopausal Osteoporosis.

Authors:  Dennis M Black; Clifford J Rosen
Journal:  N Engl J Med       Date:  2016-05-26       Impact factor: 91.245

4.  FRAX without bone mineral density versus osteoporosis self-assessment screening tool as predictors of osteoporosis in primary screening of individuals aged 70 and older.

Authors:  Wee Yang Pang; Charles A Inderjeeth
Journal:  J Am Geriatr Soc       Date:  2014-03-11       Impact factor: 5.562

5.  Incidence and economic burden of osteoporosis-related fractures in the United States, 2005-2025.

Authors:  Russel Burge; Bess Dawson-Hughes; Daniel H Solomon; John B Wong; Alison King; Anna Tosteson
Journal:  J Bone Miner Res       Date:  2007-03       Impact factor: 6.741

6.  Estimation and Comparison of Receiver Operating Characteristic Curves.

Authors:  Margaret Pepe; Gary Longton; Holly Janes
Journal:  Stata J       Date:  2009-03-01       Impact factor: 2.637

7.  Burden of illness for osteoporotic fractures compared with other serious diseases among postmenopausal women in the United States.

Authors:  Andrea Singer; Alex Exuzides; Leslie Spangler; Cynthia O'Malley; Chris Colby; Karissa Johnston; Irene Agodoa; Jessica Baker; Risa Kagan
Journal:  Mayo Clin Proc       Date:  2014-12-04       Impact factor: 7.616

8.  Screening for osteoporosis in men aged 70 years and older in a primary care setting in the United States.

Authors:  Sian Yik Lim; Joon Hee Lim; Dan Nguyen; Rie Okamura; Hoda Mojazi Amiri; Michael Calmes; Kenneth Nugent
Journal:  Am J Mens Health       Date:  2013-02-25

9.  Clinician's Guide to Prevention and Treatment of Osteoporosis.

Authors:  F Cosman; S J de Beur; M S LeBoff; E M Lewiecki; B Tanner; S Randall; R Lindsay
Journal:  Osteoporos Int       Date:  2014-08-15       Impact factor: 4.507

10.  The Bone Health Team: A Team-Based Approach to Improving Osteoporosis Care for Primary Care Patients.

Authors:  Phillip T Lawrence; Marissa P Grotzke; Yanina Rosenblum; Richard E Nelson; Joanne LaFleur; Karla L Miller; Junjie Ma; Grant W Cannon
Journal:  J Prim Care Community Health       Date:  2017-01-17
View more
  1 in total

Review 1.  Population-Based Osteoporosis Primary Prevention and Screening for Quality of Care in Osteoporosis, Current Osteoporosis Reports.

Authors:  William D Leslie; Carolyn J Crandall
Journal:  Curr Osteoporos Rep       Date:  2019-12       Impact factor: 5.096

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.