The Combination of Beta-Blockers and ACE Inhibitors Across the Spectrum of Cardiovascular Diseases
Bibliographic record
Abstract
Cardiovascular disease is the leading cause of mortality worldwide, affecting a wide range of patients at different stages across the cardiovascular continuum. Hypertension is one of the earliest risk factors in this continuum and can be controlled in most patients with currently available antihypertensive agents. However, goals are often not met because treatments are not optimized in terms of tailoring therapy to individual patients based on their hypertension subclass and cardiovascular risk profile and initiating early use of adapted-dose, single-pill combinations. In this context, beta-blockers in combination with angiotensin-converting enzyme (ACE) inhibitors are of special interest as a result of their complementary actions on the sympathetic nervous system and renin-angiotensin-aldosterone system, two interlinked pathways that influence cardiovascular risk and disease outcomes. In addition to their antihypertensive actions, beta-blockers are used to manage arrhythmias and treat angina pectoris and heart failure, while ACE inhibitors provide cardioprotection in patients with acute coronary syndromes and treat congestive heart failure. A broad range of patients may therefore receive the combination in routine clinical practice. This paper examines the supporting evidence for beta-blockers and ACE inhibitors in each of the above indications and considers the rationale for combining these agents into a single pill, using data from bisoprolol and perindopril randomized controlled trials as supporting evidence. Combining these established antihypertensive agents into a single pill continues to provide effective blood pressure lowering and improved cardiovascular outcomes while allowing a greater proportion of patients to rapidly achieve treatment targets.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".