Validity of an ultrasound device to measure bone mineral density
Bibliographic record
Abstract
Abstract This study aims to examine the validity and reliability of the UltraScan650™, a portable ultrasound device, used to measure BMD at the 1/3rd radius position. Fifty‐two female first responders and healthcare providers were assessed using DXA (forearm, femur, lumbar, and total body) and the UltraScan650™. Fat and lean mass were also assessed using the DXA. Pearson correlations, Bland–Altman plots, t‐tests, and linear regressions were used to assess validity. Intra‐class correlation (ICC) coefficients were used to assess reliability. Inter‐rater reliability and repeatability were good (ICC = 0.896 [0.818; 0.942], p < 0.001) and excellent (ICC = 0.917 [0.785; 0.989], p < 0.001), respectively. BMD as measured by the UltraScan650™ was weakly correlated to the DXA (r = 0.382 [0.121; 0.593], p = 0.0052). Bland–Altman plots revealed that the UltraScan650™ underestimated BMD (−0.0569 g/cm2), this was confirmed with a significant paired t‐test (p < 0.001). A linear regression was performed (0.4744 × UltraScan650™ + 0.4170) to provide more information as to the issue of agreement. Bland–Altman plots revealed a negligible bias, supported by a paired t‐test (p = 0.9978). Pearson's correlation revealed a significant relationship (r = −0.771 [−0.862; −0.631], p < 0.0001) between adjusted UltraScan650™—DXA and the average of the two scans (i.e., adjusted UltraScan650™ and DXA), suggesting a proportional constant error and proportional constant variability in measurements of BMD from the UltraScan650™. The UltraScan650™ is not a valid alternative to DXA for diagnostic purposes; however, the UltraScan650™ could be used as a screening tool in the clinical and research setting given the linear transformation is employed.
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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 | 0.020 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".