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Record W2801362458 · doi:10.1097/bor.0000000000000504

The utility and limitations of using trabecular bone score with FRAX

2018· review· en· W2801362458 on OpenAlexaff
Patrick Martineau, William D. Leslie

Bibliographic record

VenueCurrent Opinion in Rheumatology · 2018
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of ManitobaUniversity of Ottawa
Fundersnot available
KeywordsTrabecular bone scoreFRAXMedicineOsteoporosisBone mineralOsteoporotic fractureLumbar spineLumbarPhysical therapyBone densityDentistryQuantitative computed tomographyInternal medicineRadiologySurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Trabecular bone score (TBS) is a texture index derived from the lumbar spine dual-energy X-ray absorptiometry which can assess skeletal quality and provide information about fracture risk independent of bone mineral density (BMD). TBS is useful in assessing osteoporotic fracture risk, with lower TBS values associated with increased fracture risk. In this article, we review the current state of TBS, including its utility and limitations in the assessment and management of osteoporosis, with particular emphasis on the recent literature. RECENT FINDINGS: Ten-year fracture risk assessment using the FRAX tool can be improved through the use of a TBS adjustment. The use of TBS-adjusted FRAX can change management in a modest but significant number of patients, particularly in those close to an intervention threshold. Change in lumbar spine TBS for patients undergoing antiresorptive treatment is not a useful indicator of antifracture effect. SUMMARY: Lumbar spine TBS provides information complementary to conventional BMD, and has been shown to be clinically useful for enhancing fracture risk prediction.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.348
GPT teacher head0.467
Teacher spread0.119 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations37
Published2018
Admission routes1
Has abstractyes

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