Asthma and risk of osteoporosis and osteoporotic fracture: A systematic review and meta-analysis of cohort studies
Bibliographic record
Abstract
Background: Emerging studies have suggested that patients with asthma are at a higher risk of developing osteoporosis and osteoporotic fractures. However, the data are inconclusive. We aim to determine the risk of incident osteoporosis and osteoporotic fracture in asthma patients. Methods: A systematic search of MEDLINE, Scopus, EMBASE, Cochrane Library, and medRxiv was performed to identify eligible cohort studies indexed until February 2024, examining the risk of osteoporosis and osteoporotic fracture among asthma patients versus healthy controls. Quality assessments were performed according to the Newcastle-Ottawa Scale (NOS). The PRISMA and Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guidelines were followed. The hazard ratios (HR) were pooled using random-effects meta-analysis. The HR from the model maximally adjusted for confounders were selected. Subgroup analysis was conducted according to gender. Publication bias was evaluated by funnel plot. Results: Three cohort studies (n=737,596) met the eligibility criteria and were included in the meta-analysis. A significant association was found between asthma and the risk of incident osteoporosis (pooled HR, 1.27; 95% CI, 1.16-1.40) and osteoporotic fracture (pooled HR, 1.12; 95% CI, 1.07-1.16). Subgroup analysis by gender revealed a persistent significantly increased risk of incident osteoporosis and osteoporotic fracture in both genders. No evidence of publication bias was observed. All studies are of high quality. Conclusions: Asthma patients are at an increased risk of incident osteoporosis and osteoporotic fracture. These risks should be considered in the management of asthma patients.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.035 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".