Impact of adding distal forearm DXA to hip and spine measurements on DXA report
Bibliographic record
Abstract
Dual energy X-ray absorptiometry (DXA) is the gold standard modality for non-invasive diagnosis of osteoporosis but controversy exists about the optimal site (s) for bone mineral density (BMD) measurement. The objective was to find out impact of adding distal forearm BMD to hip and spine measurements on final diagnosis of a DXA study. This prospective study recruited 279 consecutive patients [female 256 (92%); male 23 (8%)] with a mean age of 63.25 ± 10.62 years from April 2011 to April 2012. The BMD was measured over hip (total hip and femoral neck), spine and distal forearm in all patients. Based on T-Score values of hip and spine (2 sites), diagnosis was normal in 34%, low bone mass in 40% and osteoporosis in 26% patients. However, adding distal forearm BMD and T-score (3 sites), diagnosis was normal in 28%, low bone mass in 37% and osteoporosis in 35%. Therefore, distal forearm BMD has upstaged the diagnosis from normal to low bone mass in 14%, from normal to osteoporosis in 2% and from low bone mass to osteoporosis in 18% patients. We conclude that combining distal forearm BMD with spine and hip can identify more patients with low bone mass or osteoporosis.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".