Low bone mineral density and coronary artery disease: A systematic review and meta-analysis
Bibliographic record
Abstract
Coronary artery disease (CAD) and osteoporosis both cause significant morbidity and mortality. Recent interest in inflammation and the bone-vascular axis suggests a mechanistic link between the two conditions. This review and meta-analysis was conducted to examine the potential association between low bone mineral density (BMD) and CAD in adults. Two authors searched for studies that examined the association between low BMD and CAD. Risk of bias assessment was conducted using the modified Newcastle Ottawa score. Ten studies were selected from the 2258 unique records identified. Pooled analysis showed a significant association between low BMD and CAD (OR 1.65, 95%CI 1.37-2.39, p < 0.01). Subgroup analysis investigating males and females separately was not significant. The subgroup analyses looking for any differences across geographic locations and differences between coronary imaging modalities were also negative. Studies with adjusted ORs (n = 4) were also pooled (OR 3.01, 95%CI 0.91-9.99, p = 0.07). Low BMD is associated with CAD; however, it is unclear whether this result is confounded by common risk factors given the heterogeneity between study populations and methodologies. Further large-scale epidemiological studies are required.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".