↓ Skip to main content

Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women

Overview of attention for article published in BMC Musculoskeletal Disorders, June 2016
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
6 X users
facebook
1 Facebook page

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
57 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women
Published in
BMC Musculoskeletal Disorders, June 2016
DOI 10.1186/s12891-016-1096-6
Pubmed ID
Authors

Rafael Azagra, Marta Zwart, Gloria Encabo, Amada Aguyé, Juan Carlos Martin-Sánchez, Nuria Puchol-Ruiz, Paula Gabriel-Escoda, Sergio Ortiz-Alinque, Emilio Gené, Milagros Iglesias, David Moriña, Miguel Angel Diaz-Herrera, Mireia Utzet, Josep Maria Manresa, On behalf of GROIMAP study group

Abstract

The FRAX® tool estimates the risk of a fragility fracture among the population and many countries have been evaluating its performance among their populations since its creation in 2007. The purpose of this study is to update the first FRIDEX cohort analysis comparing FRAX with the bone mineral density (BMD) model, and its predictive abilities. The discriminatory ability of the FRAX was assessed using the 'area under curve' of the receiver operating characteristic (AUC-ROC). Predictive ability was assessed by comparing estimated risk fractures with incidence fractures after a 10-year follow up period. One thousand three hundred eight women ≥ 40 and ≤ 90 years followed up during a 10-year period. The AUC for major osteoporotic fractures using FRAX without DXA was 0.686 (95 % CI 0.630-0.742) and using FN T-score of DXA 0.714 (95 % CI 0.661-0.767). Using only the traditional parameters of DXA (FN T-score), the AUC was 0.706 (95 % CI 0.652-0.760). The AUC for hip osteoporotic fracture was 0.883 (95 % CI 0.827-0.938), 0.857 (95 % CI 0.773-0.941), and 0.814 (95 % CI 0.712-0.916) respectively. For major osteoporotic fractures, the overall predictive value using the ratio Observed fractures/Expected fractures calculated with FRAX without T-score of DXA was 2.29 and for hip fractures 2.28 and with the inclusion of the T-score 2.01 and 1.83 respectively. However, for hip fracture in women < 65 years was 1.53 and 1.24 respectively. The FRAX tool has been found to show a good discriminatory capacity for detecting women at high risk of fragility fracture, and is better for hip fracture than major fracture. The test of sensibility shows that it is, at least, not inferior than when using BMD model alone. The predictive capacity of FRAX tool needs some adjustment. This capacity is better for hip fracture prediction and better for women < 65 years. Further studies in Catalonia and other regions of Spain are needed to fine tune the FRAX tool's predictive capability.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 56 98%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 9 16%
Student > Master 8 14%
Student > Doctoral Student 6 11%
Student > Bachelor 5 9%
Librarian 5 9%
Other 14 25%
Unknown 10 18%
Readers by discipline Count As %
Medicine and Dentistry 28 49%
Nursing and Health Professions 8 14%
Mathematics 2 4%
Social Sciences 2 4%
Agricultural and Biological Sciences 1 2%
Other 4 7%
Unknown 12 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 June 2016.
All research outputs
#7,565,249
of 24,860,845 outputs
Outputs from BMC Musculoskeletal Disorders
#1,434
of 4,332 outputs
Outputs of similar age
#116,608
of 360,302 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#30
of 79 outputs
Altmetric has tracked 24,860,845 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 4,332 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one has gotten more attention than average, scoring higher than 66% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 360,302 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.