Use of Sacubitril/Valsartan Prior to Primary Prevention Implantable Cardioverter Defibrillator Implantation
Bibliographic record
Abstract
Background: Implantable cardioverter defibrillators (ICDs) are an adjunct to guideline-directed medical therapy for heart failure with reduced ejection fraction. The uptake of sacubitril/valsartan in this population is not well described. We report the uptake and factors associated with sacubitril/valsartan use in patients with left ventricular dysfunction undergoing ICD implantation. Methods: primary prevention ICD implantation between October 2015 and December 2021 (n = 422) at Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. Pre-procedure sacubitril/valsartan use was determined. Logistic regression analysis was performed to examine factors associated with sacubitril/valsartan use. A Bayesian estimator of abrupt change was employed to determine a time period in which a change in the rate of sacubitril/valsartan use occurred. Results: Loop diuretic use (odds ratio [OR] = 2.20) and higher severity of New York Heart Association class symptoms (OR = 1.62) were associated with sacubitril/valsartan use. Sacubitril/valsartan use increased during the study period, to 59% in December 2021. This increase was larger among those aged ≥ 65 years (OR = 1.09). A change in the rate of sacubitril/valsartan use occurred 3 years after drug approval, 1 year after provincial drug coverage became available, and 6 months after being strongly recommended in clinical guidelines. Conclusions: In a contemporary cohort of ICD patients, sacubitril/valsartan use increased between 2015 and 2021, notably in those aged ≥ 65 years and after government drug coverage became available. Understanding barriers to sacubitril/valsartan use in ICD patients is recommended to improve clinical outcomes and survival in this population.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".