Practical Recommendations for the Use of ACE Inhibitors, Beta-Blockers, Aldosterone Antagonists and Angiotensin Receptor Blockers in Heart Failure: Putting Guidelines into Practice
Bibliographic record
Abstract
Surveys of prescribing patterns in both hospitals and primary care have usually shown delays in translating the evidence from clinical trials of pharmacological agents into clinical practice, thereby denying patients with heart failure (HF) the benefits of drug treatments proven to improve well-being and prolong life. This may be due to unfamiliarity with the evidence-base for these therapies, the clinical guidelines recommending the use of these treatments or both, as well as concerns regarding adverse events. ACE inhibitors have long been the cornerstone of therapy for systolic HF irrespective of aetiology. Recent trials have now shown that treatment with beta-blockers, aldosterone antagonists and angiotensin receptor blockers also leads to substantial improvements in outcome. In order to accelerate the safe uptake of these treatments and to ensure that all eligible patients receive the most appropriate medications, a clear and concise set of clinical recommendations has been prepared by a group of clinicians with practical expertise in the management of HF. The objective of these recommendations is to provide practical guidance for non-specialists, in order to increase the use of evidenced based therapy for HF. These practical recommendations are meant to serve as a supplement to, rather than replacement of, existing HF guidelines.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.072 | 0.224 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.024 | 0.023 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".