Acetylsalicylic Acid and Angiotensin-Converting Enzyme Inhibitors in Heart Failure: A Serious Hemodynamic Interaction? A Systematic Critique
Bibliographic record
Abstract
ABSTRACT The potential interaction between acetylsalicylic acid and angiotensin-converting enzyme inhibitors in patients with heart failure has received considerable attention lately. Opposing effects on prostaglandin synthesis and metabolism form the theoretical basis of an interaction. A review of the available literature revealed conflicting data from animal studies, human pharmacological studies, and clinical outcome studies. This paper illustrates a possible approach to examining complex and contradictory evidence, through systematic review and critique of the relevant studies. In summary, no substantial clinical evidence could be found that acetylsalicylic acid diminishes the benefits of angiotensinconverting enzyme inhibitors in heart failure. RESUME L’interaction potentielle entre l’acide acetylsalicylique et les inhibiteurs de l’enzyme de conversion de l’angiotensine chez les insuffisants cardiaques a retenu beaucoup l’attention dernierement. Des effets opposes sur la synthese et le metabolisme des prostaglandines constituent le fondement theorique de cette interaction. L’examen de la documentation, notamment d’etudes chez l’animal, d’etudes pharmacologiques chez l’humain et d’etudes d’effets cliniques, ont mis au jour des donnees contradictoires. Cet article presente une facon d’analyser ces donnees contradictoires et complexes, au moyen d’un examen et d’une critique systematiques des etudes pertinentes. En resume, il n’existe aucune donnee clinique substantielle qui montre que l’acide acetylsalicylique diminue les effets favorables des inhibiteurs de l’enzyme de conversion de l’angiotensine dans l’insuffisance cardiaque.
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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 | 0.195 | 0.456 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".