Bidirectional association between cardiovascular disease and hip fracture: a systematic review and meta-analysis
Bibliographic record
Abstract
The aim of this study was to comprehensively analyze the bidirectional association between cardiovascular disease (CVD) and hip fracture (HF). We searched PubMed, EMBASE, Web of Sciences, Cochrane Library, ScienceDirect and China National Knowledge Infrastructure for relevant studies. The Newcastle-Ottawa scale was used to evaluate the risk of bias. We conducted random effects model for meta-analysis and subgroup analysis of different ethnic groups. Sensitivity analysis and publication bias of this study were also evaluated. This study followed the PRISMA and MOOSE guidelines for systematic reviews and meta-analyses. This research included 18 cohort studies and case-control studies with a total sample of 1,854,441 individuals. The results showed ischemic heart disease might increase the risk of HF (OR = 1.41, 95%CI[1.05, 1.89], I2 = 96%). Stroke might be a risk factor for HF (OR = 2.23, 95%[1.18, 4.19], I2 = 97%), and HF might likewise be a risk factor for Stroke ( OR = 2.22, 95% CI [1.81, 2.71], I2 = 78%). Heart failure might increase the risk of HF (OR = 2.89, 95%CI [1.22, 6.85], I2 = 91%), and HF might increase the risk of heart failure (OR = 2.74, 95%CI [1.27, 5.89], I2 = 92%). Hypertension might increase the risk of HF (OR = 1.55, 95%CI[1.34, 1.8], I2 = 87%), and HF might increase the risk of hypertension (OR = 3.75, 95%CI[3.3, 4.26], I2 = 98%). Cerebrovascular disease (OR = 1.96, 95%CI[1.61, 2.4], I2 = 79%) and diseases of arteries, arterioles, and capillaries (OR = 1.58, 95%CI[1.49, 1.68], I2 = 0%) might increase the risk of HF. HF might increase the risk of myocardial infarction (OR = 2, 95%CI[1.17, 3.41], I2 = 97%) and CVD-related death (OR = 1.78, 95%CI[1.05, 3.02], I2 = 50%). Subgroup analyses showed that among Asians IHD might not raise the risk of HF (OR = 1.33, 95% CI [1.00, 1.78], I2 = 95%). In caucasians, IHD might also not raise HF risk (OR = 1.52, 95%CI [0.64, 4.56], I2 = 95%). This study supports possible bidirectional associations between CVD and HF, but more mechanistic studies of CVD and HF were warranted. However, high heterogeneity and potential confounding by unmeasured variables warrant cautious interpretation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".