Use of Valsartan in Post-Myocardial Infarction and Heart Failure Patients
Bibliographic record
Abstract
Left ventricular (LV) dysfunction and/or heart failure (HF) are frequent complications of hypertension and myocardial infarction (MI), placing affected patients at increased risk of significant morbidity and premature death. Given that the renin-angiotensin-aldosterone system (RAAS) is activated and of pathophysiological importance in such patients, a strong therapeutic rationale exists to target the main effector mechanism (that is, angiotensin II [Ang II]) in order to lessen the associated morbidity and mortality burden. Angiotensin-converting enzyme (ACE) inhibitors have been shown to reduce mortality and LV dysfunction and to slow disease progression in patients with HF, including high-risk, post-MI patients. However, ACE inhibitors (ACE-Is) may not provide optimal long-term RAAS blockade (a finding that is associated with a worse prognosis) and many patients are unable to tolerate such therapy (because of troublesome dry cough, for example). In contrast, Ang II receptor blockers (ARBs) may block the RAAS more completely than ACE-Is and appear to be better tolerated. Several large-scale trials gave evaluated the efficacy of ARBs in patients with LV dysfunction and/or HF (including high-risk, post-MI patients), and have confirmed their utility as an efficacious and well-tolerated alternative to ACE-Is in this setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".