Prevalence of discordance between femoral and lumbar bone mineral density among older adults in a community-based setting.
Bibliographic record
Abstract
BACKGROUND: T-score measurement via dual-energy X-ray absorptiometry (DXA) is the gold standard for assessing and classifying the bone mineral density status of patients as normal, osteopenic, or osteoporotic according to the World Health Organization criteria. However, the diagnostic accuracy may be affected by the skeletal site selected for DXA. OBJECTIVES: Estimate the prevalence of femoral and lumbar BMD discordance in a community-based setting in Riyadh, Saudi Arabia. DESIGN: Cross-sectional. SETTING: Polyclinics at a tertiary care center. PATIENTS AND METHODS: This study included all patients aged ≥60 years who visited the Department of Family Medicine and underwent DXA screening between 2016 and 2022. MAIN OUTCOME MEASURES: Discordance was defined as a difference in BMD status between two skeletal sites. Minor discordance occurs when adjacent sites have different diagnoses; i.e., one site exhibits osteoporosis and the other exhibits osteopenia. In contrast, major discordance occurs when one site exhibits osteoporosis and the other exhibits normal BMD. SAMPLE SIZE: 1429 older adults. RESULTS: The study patients had a median age of 66 years (60-99, minimum-maximum). The prevalence of discordance was 41.6%, with major discordance present in 2.2% of patients and minor discordance in 39.4%. The distribution of discordance did not differ significantly among the sociodemographic factors. CONCLUSION: Discordance is prevalent among the Saudi geriatric population. During the analysis of DXA results, physicians should account for discordance when diagnosing and ruling out osteoporosis in high-risk patients. LIMITATIONS: All factors influencing discordance were not explored thoroughly; this study mainly focused on older adults. Furthermore, diverse age groups need to be investigated for a more comprehensive understanding of the analyzed factors.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".