Characterising cortical density in the mid-tibia: intra-individual variation in adolescent girls and boys
Bibliographic record
Abstract
BACKGROUND: Inter-individual differences in cortical bone volumetric density (CoD), such as those related to sex, are a product of differences in remodelling rates. While cortical bone is often treated as a uniform tissue, remodelling rates also vary within individual bones. This level of adaptation has largely been overlooked in analyses of peripheral quantitative computed tomography (pQCT) images. Further, such variation in CoD has never been assessed in growing bones. We hypothesised that CoD varied significantly within the same cross-section of the mid-tibia of adolescents. We further hypothesised that due to the profound impact of oestrogen on remodelling, this variation would be different between sexes. METHODS: Subjects were 183 adolescents (99 girls and 84 boys) in grade 6 and 7 with a mean age of 12.1 years. We used age at peak height velocity to adjust for maturational differences between sexes. Image data from a mid-tibia pQCT scan of each subject were assessed regionally within eight sectors distributed about the cortex and aligned by the anterior tibial crest. We used a repeated measures general linear model to assess intra-individual variation in CoD while controlling for differences in ethnicity, maturity, height, weight, physical activity level and total cross-sectional bone area (ToA). RESULTS: Sector based variation in CoD was significant (p<0.001), with the anterior cortex having lower density than the posterior cortex. The largest percentage difference (anterior vs posteromedial sectors) was 12.2%. A significant sector*sex interaction (p = 0.018) was detected; however, its impact was relatively small with girls having 1.1-3.6% denser bones than boys depending on the sector (2.7% average difference). CONCLUSIONS: The magnitude of the variation in CoD across sectors within individuals of both sex was far greater than the mean differences between the sexes. This finding indicates that the microstructural variation within the mid-tibia is detectable by pQCT and its magnitude suggests an important level of adaptation to loading.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".