Abstract 4145759: Guideline Directed Medical Therapy and the Impact of Sex on Patient Reported and Clinical Outcomes in a Specialized Heart Failure Clinic
Bibliographic record
Abstract
Introduction: Despite new advances in heart failure (HF) management, underutilization of guideline-directed medical therapy (GDMT) persists. In addition, contemporary data on GDMT utilization and whether sex differences exist is unclear. We aim to characterize GDMT use across HF subtypes, investigate sex-based disparities in utilization, and explore these impacts on patient quality of life markers and clinical outcomes. Methods: Patients with HF were enrolled in the heart function clinic (HFC) in Edmonton, Alberta, from Feb 2018 to Nov 2022. Medication records (renin-angiotensin system inhibitors [RAASi], angiotensin receptor neprilysin inhibitors [ARNI], β-blockers, mineralocorticoid inhibitors [MRA], sodium-glucose cotransporter 2 inhibitors [SGLT2i], and glucagon-like peptide 1 receptor agonist [GLP-1 RA]) over 3 years and clinical comorbidities using ICD-10 codes were obtained. We administered the Kansas City Cardiomyopathy Questionnaire Score (KCCQ-12) at enrolment and 6—or 12-month follow-ups, with changes ≥5 defined as clinically significant. We assessed the association between GDMT and sex to changes in KCCQ-12 scores and clinical outcomes. Results: Our HFC cohort of 1431 HF patients (median age 68, 29% female) included 52% with reduced (HFrEF), 20% with mildly reduced (HFmrEF), and 28% with preserved (HFpEF) ejection fraction. Median baseline KCCQ-12 score was 75 (IQR 33) and was similar between HF subtypes. ARNI, SGLT2i, and MRA use in HFpEF remains lower compared to HFrEF/HFmrEF (p<0.001), with gaps in treatment persisting over 3 years. Across HF subtypes, GDMT utilization rates were similar between sexes except for SGLT2i in HFmrEF (19.1% male vs. 7.5% female, p=0.02). Controlling for clinical covariates, RAASi (aHR 0.54, 95% CI 0.41-0.70), ARNI (aHR 0.58, 95% CI 0.43-0.80), GLP-1 RA (aHR 0.43, 95% CI 0.19-0.97), and females (aHR 0.72, 95% CI 0.58-0.91) were associated with lower all-cause mortality. ARNI use was also associated with improved follow-up KCCQ12 scores (aOR 1.57, 95% CI 1.00-2.45). Conclusion: Despite evidence of improved KCCQ-12 scores and reduced all-cause mortality, GDMT remains underutilized, particularly in HFpEF patients. While we found no sex-based disparities in GDMT utilization, females showed better clinical outcomes in our HF cohort. To improve patient outcomes, further research is needed to address barriers to implementing new GDMT across the heart failure spectrum.
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 | 0.003 |
| 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) | 0.003 | 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".