Lower Bone Density, Impaired Microarchitecture, and Strength Predict Future Fragility Fracture in Postmenopausal Women: 5-Year Follow-up of the Calgary CaMos Cohort
Bibliographic record
Abstract
The aim of this prospective study was to use high-resolution peripheral quantitative computed tomography (HR-pQCT) to determine if baseline skeletal parameters can predict incident fragility fracture in women and, secondly, to establish if women that fracture lose bone at a faster rate than those who do not fracture. Women older than 60 years who experienced a fragility fracture during the 5-year follow-up period (incident fracture group, n = 22) were compared with those who did not experience a fragility fracture during the study (n = 127). After image registration between baseline and follow-up measures, standard and cortical morphological analyses were conducted. Odds ratios were calculated for baseline values and annualized percent change of HR-pQCT and finite element variables. At the radius, baseline HR-pQCT results show women who fractured had lower total bone mineral density (Tt.BMD; 19%), trabecular bone mineral density (Tb.BMD; 25%), and trabecular number (Tb.N; 14%), with higher trabecular separation (Tb.Sp; 19%) than women who did not fracture. At the tibia, women with incident fracture had lower Tt.BMD (15%), Tb.BMD (12%), cortical thickness (Ct.Th; 14%), cortical area (Ct.Ar; 12%), and failure load (10%) with higher total area (Tt.Ar; 7%) and trabecular area (Tb.Ar; 10%) than women who did not fracture. Odds ratios (ORs) at the radius revealed every SD decrease of Tt.BMD (OR = 2.1), Tb.BMD (OR = 2.0), and Tb.N (OR = 1.7) was associated with a significantly increased likelihood of fragility fracture. At the tibia, every SD decrease in Tt.BMD (OR = 2.1), Tb.BMD (OR = 1.7), Ct.Th (OR = 2.2), Ct.Ar (OR = 1.9), and failure load (OR = 1.7) were associated with a significantly increased likelihood of fragility fracture. Irrespective of scanning modality, the annualized percent rate of bone loss was not different between fracture groups. The results suggest baseline bone density, microarchitecture, and strength rather than change in these variables are associated with incident fragility fractures in women older than 60 years. Furthermore, irrespective of fragility fracture status, women experienced changes in skeletal health at a similar rate. © 2017 American Society for Bone and Mineral Research.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".