Blood Lipid Levels in Patients with Osteopenia and Osteoporosis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background: Considering the controversial relationship between blood lipid levels and osteopenia and osteoporosis (OP), we performed this meta-analysis. Methods: Using specific keywords and related words, we searched PubMed, Embase, and Cochrane Library databases. The Newcastle-Ottawa Scale form was used to evaluate the quality of the literature. According to the inclusion and exclusion criteria, we systematically screened the literature to extract relevant information and data. Revman 5.3 and Stata 13.0 software were used for statistical analysis. Results were expressed as the mean difference and 95% confidence interval. The heterogeneity test was conducted according to I 2 and Q tests. Egger’s test was used to quantitatively evaluate publication bias. Results: This analysis involved 12 studies and included 12,395 subjects. The quality of the literature was acceptable. Among subjects who were not taking lipid-lowering drugs, total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) in the osteopenia were not significantly increased/decreased. There were no significant differences in LDL-C in postmenopausal women in osteopenia. TG was unchanged in the OP group in subjects without taking lipid-lowering drugs. HDL-C was elevated in OP group but not in osteopenia group in all subjects Conclusions: HDL-C was elevated in patients with OP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.003 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| 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 teacher head, 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".