The Correlation between Phalangeal Quantitative Ultrasonography and Dual Energy X-ray Absorptiometry in Women with Premature Ovarian Failure
Bibliographic record
Abstract
OBJECTIVES: With the growing demand for bone densitometry services there is a need for simple, cost-effective and ideally mobile devices which can identify individuals who are at risk of osteoporotic fracture. When new devices are evaluated, it is useful to examine the correlation with the established 'gold standard' technique of dual x-ray absorptiometry (DXA). This study examined the correlation between quantitative ultrasound (QUS) measurements performed at the phalanges and conventional DXA measurements of the spine and hip in women with premature ovarian failure--a known risk factor for osteoporosis. METHODS: Thirteen white Caucasian women suffering from premature ovarian failure and 19 age- and sex-matched controls were recruited into the study. DXA measurements were performed at the spine and hip, followed by quantitative ultrasonography at phalanges II-V of the non-dominant hand. RESULTS: Significant correlations were observed between the bone transit time (BTT) value from the Bone Profiler and bone mineral density measured at the spine (r=0.66). The spine Z-scores also correlated with many of the ultrasound values (r=0.44-0.63). Significant inverse correlations were observed between BMI, weight and ultrasound parameters (r=-0.48 to -0.78). CONCLUSION: We have reported moderate but significant correlations between phalangeal QUS and DXA parameters. The strongest correlation was observed between BTT and spine BMD, as well as between the Z-scores from the two devices. QUS parameters also demonstrated an inverse correlation with weight and BMI.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".