Rates of and Risk Factors for Trabecular and Cortical BMD Loss in Middle-Aged and Elderly African-Ancestry Men
Bibliographic record
Abstract
Low trabecular (Tb) and cortical (Ct) volumetric BMD (vBMD) are related to increased fracture risk, but little is known about the patterns and correlates of Tb and Ct vBMD loss with aging. We examined the rates of change in total, Tb.vBMD, and Ct.vBMD at the radius and tibia, and identified factors associated with vBMD loss among 1569 men of African descent aged 40 years and older. Quantitative computed tomography was used to measure vBMD 6 years apart. The annualized rate of loss in Tb.vBMD was significant at the radius (-0.047%/yr, p = 0.016) but not at the tibia. At the radius, a significant loss of Tb.vBMD was observed in men aged 40 to 49 years that appeared to be attenuated and not statistically significant among older age men. In contrast, the decline in Ct.vBMD was similar at both skeletal sites (-0.254 to -0.264%/yr, p < 0.0001) and was consistent across all age groups. Positive associations were found for vBMD changes with body weight (all but radius Ct.vBMD) and diabetes (Ct.vBMD only), whereas negative associations were found with hypertension (all but radius Tb.vBMD), smoking (Ct.vBMD only), and androgen deprivation therapy (cortical vBMD only). Trabecular and cortical vBMD loss appears to follow different patterns among middle- and older-aged men of African ancestry. Factors associated with the decline in vBMD also varied by compartment and anatomical site. Additional studies are needed to better understand the physiological mechanisms underlying early BMD loss among African-ancestry men.
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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 | 0.002 |
| 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".