Abstract P171: Potential Mortality Reduction with Optimal Usage of sacubitril/valsartan Therapy for the Treatment of Heart Failure in Canada
Bibliographic record
Abstract
Background: Despite well-recognized standard of care therapies, heart failure (HF) continues to be characterized by high mortality rates. Sacubitril/valsartan, a first-in-class treatment for HF with reduced ejection fraction (HFrEF) provided incremental cardiovascular and overall survival benefit in PARADIGM-HF, the largest clinical trial ever conducted in HF patients. We hypothesized that optimal use of sacubitril/valsartan in the treatment of HFrEF in Canada would be associated with potential benefits in terms of deaths avoided. Objective: The objective of this analysis was to quantify the number of potential deaths avoided with optimal usage of sacubitril/valsartan in the treatment of HFrEF in Canada. Methods: Data from Statistics Canada was used to quantify the population above 18 years of age. A literature search was then conducted to determine the prevalence of HF in Canada, the proportion of these with NYHA class II and III, and finally the proportion of patients with HFrEF. The number needed to treat (NNT) to avoid one death, standardized to 12 months was derived from the PARADIGM-HF trial. The NNT using product limit survival rates and actual follow-up times from the PARADIGM-HF trial was also derived. The potential number of deaths prevented as a result of optimal usage of sacubitril/valsartan as per current approved usage in Canada (HFrEF patients with NYHA class II or III) were estimated along with multiple-way sensitivity analysis using the analysis-of-extremes method. The main outcome and measure was all-cause mortality. Results: A Canadian prevalence of 2.31% was applied to determine the number of HF patients. From those, 64% were classified as NYHA Class II and III of which 56% were considered as rEF. It was estimated that in Canada, approximately 242,200 patients are affected with HFrEF with NYHA class II and III. Based on a NNT of 80, optimal usage of sacubitril/valsartan therapy was estimated to prevent 3,014 deaths per year (range, 1,930 – 4,331 per year). Based on the alternate NNT (71.3) using the product limit survival rates and actual follow-up times from PARADIGM-HF, a total of 3,397 patient deaths could be potentially prevented each year (range, 2,718 – 4,076 per year). Conclusion: Standard of care treatment for HF is well-established and has shown important mortality reduction but there is still a need for additional therapies to further improve survival rates for patients living with HFrEF. The findings from this analysis suggest that a substantial number of deaths in Canada could potentially be avoided by optimal usage of sacubitril/valsartan therapy. This analysis supports the importance of rapidly implementing evidence-based therapy, in this case sacubitril/valsartan, into routine clinical practice to improve clinical outcomes for HFrEF patients in Canada.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".