The use of sacubitril/valsartan in anthracycline-induced cardiomyopathy: A mini case series
Bibliographic record
Abstract
BACKGROUND: Sacubitril/valsartan has been shown to significantly reduce cardiovascular mortality and hospitalizations due to heart failure in adult patients with reduced ejection fraction when compared to enalapril. To the best of our knowledge, the combination of sacubitril (neprilysin inhibitor) and valsartan (angiotensin receptor blocker) has not been evaluated in patients with chemotherapy-induced cardiomyopathy, as these patients were excluded from the recent pivotal trial, PARADIGM-HF. However, current guidelines for the evaluation and management of cardiovascular complications of cancer therapy, published by the Canadian Cardiovascular Society, direct clinicians to the Canadian Cardiovascular Society Heart Failure Guidelines for the management of cancer patients who develop clinical heart failure or an asymptomatic decline in left ventricular ejection fraction (e.g. >10% reduction from baseline or left ventricular ejection fraction <53%), which could include the use of sacubitril/valsartan. METHODS: Retrospective descriptive comparative case study of two patients treated with sacubitril/valsartan. RESULTS: We present data from two patients who experienced anthracycline-induced cardiomyopathy and were successfully managed with sacubitril/valsartan after suboptimal responses to traditional evidence-based heart failure therapies. Both patients demonstrated some recovery of function and normalization of N-terminal pro B-type natriuretic peptide levels. Sacubitril/valsartan was well tolerated with minimal side effects. To date, neither patient has required hospitalization or additional clinic interventions for heart failure. CONCLUSIONS: While further large scale studies are required to determine a comprehensive safety and efficacy profile, we report two cases of anthracycline-induced cardiomyopathy survivors managed with sacubitril/valsartan with minimal side effects and no hospitalizations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".