Use of Guideline-Directed Medical Therapy in Patients Aged 80 Years or Older With Heart Failure With Reduced Ejection Fraction
Bibliographic record
Abstract
Background: Guideline-directed medical therapy (GDMT) reduces morbidity and mortality in patients with heart failure with reduced ejection fraction (HFrEF). Use of GDMT is recommended in all adults with HFrEF, but it is potentially underutilized in patients with advanced age. This study sought to characterize use of GDMT in octogenarians and nonagenarians with HFrEF and identify barriers to initiation and uptitration. Methods: This retrospective cohort study included patients aged 80-99 years at 3 heart failure clinics in the Lower Mainland region of British Columbia, Canada. Patients with a left ventricular ejection fraction ≤ 40% and heart failure hospitalization < 12 months were included. Data were collected between September 2019 and August 2021, for up to 24 months from the initial clinic visit. Results: A total of 91 patients were included. The mean age was 85 years, and the mean left ventricular ejection fraction was 30%. About 50% of patients had New York Heart Association class II symptoms. Throughout the study follow-up period, approximately 91% of patients were on a beta-blocker, 72% were on a renin-angiotensin system (RAS) inhibitor, 31% were on a mineralocorticoid receptor antagonist (MRA), and 4% were on a sodium-glucose cotransporter 2 (SGLT2) inhibitor. The target dose was achieved in 19% of patients on a beta-blocker, 7% on an RAS inhibitor, 11% on an MRA, and 100% on an SGLT2 inhibitor. Frequent barriers to GDMT initiation and/or uptitration were renal dysfunction, hypotension, and hyperkalemia. Conclusions: The levels of use of RAS inhibitors and beta-blockers in patients aged 80-99 years with HFrEF were reasonable, whereas the levels of use of MRAs and SGLT2 inhibitors were low. Achievement of target doses of GDMT was rare, owing to common adverse effects.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".