Comparison of β-blocker agents and mortality in maintenance hemodialysis patients: an international cohort study
Bibliographic record
Abstract
Background: Despite a lack of clinical trial data, β-blockers are widely prescribed to dialysis patients. Whether specific β-blocker agents are associated with improved long-term outcomes compared with alternative β-blocker agents in the dialysis population remains uncertain. Methods: We analyzed data from an international cohort study of 10 125 patients on maintenance hemodialysis across 18 countries that were newly prescribed a β-blocker medication within the Dialysis Outcomes and Practice Patterns Study (DOPPS). The following β-blocker agents were compared: metoprolol, atenolol, bisoprolol and carvedilol. Multivariable Cox proportional hazards models were used to estimate the association between the newly prescribed β-blocker agent and all-cause mortality. Stratified analyses were performed on patients with and without a prior history of cardiovascular disease. Results: The mean (standard deviation) age in the cohort was 63 (15) years and 57% of participants were male. The most commonly prescribed β-blocker agent was metoprolol (49%), followed by carvedilol (29%), atenolol (11%) and bisoprolol (11%). Compared with metoprolol, atenolol {adjusted hazard ratio (HR) 0.77 [95% confidence interval (CI) 0.65-0.90]} was associated with a lower mortality risk. There was no difference in mortality risk with bisoprolol [adjusted HR 0.99 (95% CI 0.82-1.20)] or carvedilol [adjusted HR 0.95 (95% CI 0.82-1.09)] compared with metoprolol. These results were consistent upon stratification of patients by presence or absence of a prior history of cardiovascular disease. Conclusions: Among patients on maintenance hemodialysis who were newly prescribed β-blocker medications, atenolol was associated with the lowest mortality risk compared with alternative agents.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".