Sex Disparities in Longitudinal Use and Intensification of Guideline-Directed Medical Therapy Among Patients With Newly Diagnosed Heart Failure With Reduced Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: Guideline-directed medical therapies (GDMTs) are the mainstay of treatment for heart failure with reduced ejection fraction (HFrEF), but they are underused. Whether sex differences exist in the initiation and intensification of GDMT for newly diagnosed HFrEF is not well established. METHODS: Patients with incident HFrEF were identified from the 2016 to 2020 Optum deidentified Clinformatics Data Mart Database, which is derived from a database of administrative health claims for members of large commercial and Medicare Advantage health plans. The primary outcome was the use of optimal GDMT within 12 months of HFrEF diagnosis. Consistent with the guideline recommendations during the time period of the study, optimal GDMT was defined as ≥50% of the target dose of evidence-based beta-blocker plus ≥50% of the target dose of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, or any dose of angiotensin receptor neprilysin inhibitor plus any dose of mineralocorticoid receptor antagonist. The probability of achieving optimal GDMT on follow-up and predictors of optimal GDMT were evaluated with time-to-event analysis with adjusted Cox proportional hazard models. RESULTS: The study cohort included 63 759 patients (mean age, 71.3 years; 15.2% non-Hispanic Black race; 56.6% male). Optimal GDMT use was achieved by 6.2% of patients at 12 months after diagnosis. Female (compared with male) patients with HFrEF had lower use across every GDMT class and lower use of optimal GDMT at each time point at follow-up. In an adjusted Cox model, female sex was associated with a 23% lower probability of achieving optimal GDMT after diagnosis (hazard ratio [HR], 0.77 [95% CI, 0.71–0.83]; P <0.001). The sex disparities in GDMT use after HFrEF diagnosis were most pronounced among patients with commercial insurance (females compared with males; HR, 0.66 [95% CI, 0.58–0.76]) compared with Medicare (HR, 0.85 [95% CI, 0.77–0.92]); P interaction sex×insurance status=0.005) and for younger patients (age <65 years: HR, 0.65 [95% CI, 0.58–0.74]) compared with older patients (age ≥65 years: HR, 87 [95% CI, 80–96]) P interaction sex×age=0.009). CONCLUSIONS: Overall use of optimal GDMT after HFrEF diagnosis was low, with significantly lower use among female (compared with male) patients. These findings highlight the need for implementation efforts directed at improving GDMT initiation and titration.
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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) | 0.000 | 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".