Sacubitril/Valsartan Versus Enalapril in Chronic Chagas Cardiomyopathy
Bibliographic record
Abstract
Chronic Chagas cardiomyopathy (CCC) has unique pathogenic and clinical features with worse prognosis than other causes of heart failure (HF), despite the fact that patients with CCC are often younger and have fewer comorbidities. Patients with CCC were not adequately represented in any of the landmark HF studies that support current treatment guidelines. PARACHUTE-HF (Prevention And Reduction of Adverse outcomes in Chagasic Heart failUre Trial Evaluation) is an active-controlled, randomized, phase IV trial designed to evaluate the effect of sacubitril/valsartan 200 mg twice daily vs enalapril 10 mg twice daily added to standard of care treatment for HF. The study aims to enroll approximately 900 patients with CCC and reduced ejection fraction at around 100 sites in Latin America. The primary outcome is a hierarchical composite of time from randomization to cardiovascular death, first HF hospitalization, or relative change from baseline to week 12 in NT-proBNP levels. PARACHUTE-HF will provide new data on the treatment of this high-risk population. (Efficacy and Safety of Sacubitril/Valsartan Compared With Enalapril on Morbidity, Mortality, and NT-proBNP Change in Patients With CCC [PARACHUTE-HF]; NCT04023227).
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".