Postmenopausal women with osteopenia have higher cortical porosity and thinner cortices at the distal radius and tibia than women with normal aBMD: An in vivo HR-pQCT study
Bibliographic record
Abstract
Increases in cortical porosity (Ct.Po) and decreases in cortical thickness (Ct.Th) are associated with increased bone fragility. The purpose of this study was to validate an autosegmentation method for high-resolution peripheral quantitative computed tomography (HR-pQCT) scans to measure Ct.Po and Ct.Th and use it to compare Ct.Po and Ct.Th between pre- and postmenopausal women with normal, osteopenic, and osteoporotic areal bone mineral density (aBMD). The Ct.Po and Ct.Th measurements were validated using cadaver forearms (n = 10) and micro-computed tomography (microCT) as the gold standard. The analysis was applied to distal radius and tibia HR-pQCT scans from a subset of participants from the Calgary, Alberta, cohort of the Canadian Multicentre Osteoporosis Study (n = 280, 18 to 90 years). Analysis of covariance compared Ct.Po and Ct.Th outcomes between 63 normal premenopausal (dual-energy X-ray absorptiometry femoral neck T-score > -1), 87 normal postmenopausal, 121 osteopenic postmenopausal, and 9 osteoporotic postmenopausal women. Linear regression analysis and Bland-Altman plots were used to assess the agreement between the HR-pQCT and microCT measurements, resulting in r(2) values of 0.80 for Ct.Po and 0.98 for Ct.Th. At both sites, Ct.Po was higher in postmenopausal (all groups) than in premenopausal women (3.2% to 12.9%, p < .001). Ct.Th was not significantly different between normal premenopausal and postmenopausal women at either site; however, both osteopenic and osteoporotic women had thinner (-12.8% to -30.3%, p < .01), more porous (2.1% to 8.1%, p < .001) cortices than normal postmenopausal women. Our method offers promise as a valuable tool to measure Ct.Po and Ct.Th in vivo and investigate associations among cortical bone structure, age, and disease status.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".