Number of Osteoporotic Sites and Fracture Risk Assessment: A Cohort Study From the Manitoba Bone Density Program
Bibliographic record
Abstract
UNLABELLED: Site-discordance in BMD assessment is common and significantly affects patient categorization. Greater number of osteoporotic sites correlates with lower T scores at each index site. This largely explains the positive association between number of osteoporotic sites and fracture risk. INTRODUCTION: Site-discordance in BMD is common when used to classify patients based on a cut-off T score of -2.5. It is unclear whether fracture risk assessment is improved by considering BMD information from multiple sites. Our objective was to assess the contribution of number of osteoporotic sites to overall fracture risk. MATERIALS AND METHODS: The study population was drawn from the regionally based clinical database of the Manitoba Bone Density Program that includes all clinical DXA test results for the Province of Manitoba, Canada. Analyses were limited to 16,505 women>or=50 years of age at the time of baseline DXA of the spine (L1-L4) and hip (three sites). During follow-up (3.2+/-1.5 years), longitudinal health service records showed 765 women with at least one osteoporotic fracture code (hip, forearm, spine, or humerus). RESULTS: Of 5012 women classified as osteoporotic by at least one site (T score -2.5 or lower), almost one half (2370; 47%) were abnormal at only a single site. Among the 1856 women with an osteoporotic total hip measurement, mean total hip T scores decreased as the number of additional osteoporotic sites increased (-2.58, no other osteoporotic sites; -2.69, one other site; -2.87, two other sites; -3.17, three other sites; Spearman r=-0.44, p<0.0001). Age-adjusted fracture risk from a Cox proportional hazards model increased as the number of osteoporotic sites increased (p<0.0001), but number of osteoporotic sites was no longer an independent predictor after total hip BMD was included as a covariate (p=0.19). Covariate adjustment for other sites of BMD measurement attenuated, but did not eliminate, the effect of number of osteoporotic sites. CONCLUSIONS: Site-discordance is common and significantly affects patient categorization when different skeletal sites are used for diagnosis. Greater number of osteoporotic sites correlates with lower T scores at each index site. This largely explains the positive association between number of osteoporotic sites and 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| 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".