P4988Beta-blockers in diabetes with stable coronary heart disease - a cause for concern?
Bibliographic record
Abstract
Abstract Background Beta-blocker (BB) therapy is a cornerstone for the treatment of coronary heart disease (CHD). The evidence of the benefit from long-term BB therapy in diabetic patients with stable CHD is scarce. This meta-analysis summarises the evidence relating to the BB therapy in diabetic patients with stable CHD. Methods A meta-analysis was performed according to PRISMA and MOOSE guidelines for reporting of systematic reviews of observational studies. PubMed, Embase, and Cochrane central were searched and two authors independently screened studies for eligibility. The quality of studies was assessed with the Newcastle Ottawa scale. The primary outcome of interest was all-cause mortality, cardiovascular (CV) mortality and major adverse cardiovascular events (MACE) in diabetic patients with and without BB therapy. A generic inverse variance model was used to pool the odds ratio or hazards ratio from included studies to calculate the overall effect estimate. The significance threshold was set at p-value <0.05. Heterogeneity was assessed by I2. Results Four non-randomized studies with 9,515 participants were selected for the analyses. Four studies were post-hoc analyses of randomised controlled trials, and 1 article was an analysis of a nationally representative survey. In a fixed effects model, BB therapy in diabetic patients with stable CHD was found to be associated with increased risk of CV mortality, and MACE (27%, and 32% respectively; p-value <0.05) and was not associated with a reduction in all-cause mortality (HR 1.12; 95% CI 0.94–1.33; p-value =0.22). Conclusion BB therapy in diabetic patients with stable CHD appears to be linked to higher mortality. Large randomised trials are needed in this population to confirm these findings. Acknowledgement/Funding None
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.028 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".