Bone Microarchitecture Assessment by High-Resolution Peripheral Quantitative Computed Tomography in Patients with Systemic Lupus Erythematosus Taking Corticosteroids
Bibliographic record
Abstract
OBJECTIVE: We assessed the relationship between vertebral fracture and bone microarchitecture in patients with systemic lupus erythematosus (SLE) on chronic corticosteroid therapy using high-resolution peripheral quantitative computed tomography (HR-pQCT). METHODS: Fifty-nine Chinese women with SLE taking corticosteroid were selected to participate in a cross-sectional study. Vertebral fracture was confirmed semiquantitatively by lateral radiographs of the thoracic and lumbar spine. Density and microarchitecture at the distal radius were measured with HR-pQCT. Areal bone mineral density (aBMD) at hip and lumbar spine was measured by dual-energy X-ray absorptiometry (DEXA). RESULTS: Twelve patients had vertebral fractures. The aBMD of spine or hip did not differ between those with and without vertebral fractures. Measures by HR-pQCT revealed that patients with vertebral fractures had significantly lower level of average bone density (p = 0.007), cortical bone density (p = 0.029), trabecular bone density (p = 0.024), trabecular bone volume to tissue volume (p = 0.023), and trabecular thickness (p = 0.011) than those without vertebral fractures. Independent explanatory variables associated with higher risk of vertebral fractures were older age (p = 0.013) and lower average cortical bone density (p = 0.029). CONCLUSION: Vertebral fracture in patients with SLE on chronic corticosteroid treatment was associated with alterations of bone density and microarchitectures measured by HR-pQCT and DEXA. However, alterations were more pronounced in measurements by HR-pQCT. Low cortical bone density and old age were significant predictors of vertebral fracture risk.
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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 | 0.002 |
| 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".