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153 Fracture risk estimation with FRAX®: is the bone mineral density test necessary?

2022· article· en· W4281712765 on OpenAlexaffabout
Roni Kraut, Mao Ding, Оксана Бабенко

Bibliographic record

VenueAbstracts · 2022
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFRAXMedicineBone mineralInterquartile rangeOsteoporosisRetrospective cohort studyMedical prescriptionPopulationHip fracturePhysical therapyInternal medicineEnvironmental healthOsteoporotic fracture

Abstract

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Objectives Fractures can have a devastating impact on the function of older adults, and population-based screening is recommended by many organizations to help prevent fractures. The Fracture Risk Assessment tool (FRAX®) is a validated, widely used, 12-question tool to predict 10-year fracture risk and can be calculated with or without bone mineral density (BMD) results. FRAX without BMD results has been shown to be a valid screening tool; yet, to our knowledge, there has not been a Canadian study based in primary care providing such evidence. The objectives of our study were to 1) determine the difference in risk estimates using FRAX with BMD and FRAX without BMD, and 2) assess the direct cost of BMD. Method Retrospective chart review. Patients between the ages of 50–74 affiliated with a primary care clinic in Edmonton, Canada were eligible if they 1) had a BMD completed by Medical Imaging Consultants from 2017–2022; and 2) did not have a prescription for a bisphosphonate at the time of the BMD. The on-line FRAX calculator for Canada was used to calculate the risk of major osteoporotic fracture, and this risk was then categorized as low (<10%), moderate (10%-20%), or high (>20%). The variables for the FRAX calculation were extracted from BMD reports and patients’ charts. The direct cost (physician billing) was calculated using the Alberta Medical Association health service code X128. Results There were 90 eligible patients. The median age was 65 years old (interquartile range [IQR] 58–67); 98% (n = 88) were female; 6% (n = 5) had a previous fragility fracture; 10% (n = 9) had a parent with a hip fracture; 3% (n = 3) were smoking tobacco; 1% (n = 1) were positive for exposure to oral glucocorticoids; 0% (n = 0) had a disorder that favored secondary osteoporosis; 0% (n = 0) imbibed ≥3 units of alcohol daily; and the median femoral neck t-score was -1.3 (IQR -1.95 to - 0.5). Risk estimates using FRAX with and without BMD were concordant for 86% of patients (n = 77):72% (n = 65) had low risk and 13% (n = 12) had moderate risk of fracture. Risk estimates were discordant for 14% of patients (n = 13): 12% (n = 11) had discordance in the low-moderate risk classification; 1% (n = 1) had discordance in the moderate-high risk classification; and 1% (n = 1) had discordance in the low-high risk classification. The median risk difference in the discordance scores was 4% (IQR 3.1%-4.5%). The total cost of physician billings for BMD was $12,764. Conclusions For most patients affiliated with this primary care clinic, using the FRAX tool without BMD did not change the risk classification of future fracture risk but resulted in additional costs. Further, most of the discordance revolved around the low-to-moderate risk classification, which is less likely to change clinical management per Osteoporosis Canada guidelines. These results are consistent with other studies that have found including BMD in the FRAX tool may not be necessary for fracture screening.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.236
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2022
Admission routes2
Has abstractyes

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