Updated practice guideline for dual-energy X-ray absorptiometry (DXA)
Bibliographic record
Abstract
The introduction of dual-energy X-ray absorptiometry (DXA) technology in the 1980s revolutionized the diagnosis, management and monitoring of osteoporosis, providing a clinical tool which is now available worldwide. However, DXA measurements are influenced by many technical factors, including the quality control procedures for the instrument, positioning of the patient, and approach to analysis. Reporting of DXA results may be confounded by factors such as selection of reference ranges for T-scores and Z-scores, as well as inadequate knowledge of current standards for interpretation. These points are addressed at length in many international guidelines but are not always easily assimilated by practising clinicians and technicians. Our aim in this report is to identify key elements pertaining to the use of DXA in clinical practice, considering both technical and clinical aspects. Here, we discuss technical aspects of DXA procedures, approaches to interpretation and integration into clinical practice, and the use of non-bone mineral density measurements, such as a vertebral fracture assessment, in clinical risk assessment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".