The utility and limitations of using trabecular bone score with FRAX
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".