Association Between a Hospitalization for Heart Failure and the Initiation/Discontinuation of Guideline-Recommended Treatments: An Analysis from the Swedish Heart Failure Registry
Bibliographic record
Abstract
AIMS: To investigate whether a heart failure (HF) hospitalization is associated with initiation/discontinuation of guideline-directed medical HF therapy (GDMT) and consequent outcomes. METHODS AND RESULTS: Among patients in the Swedish HF registry with an ejection fraction <50% enrolled in 2009-2018, initiation/discontinuation of GDMT was investigated by assessing dispensations of GDMT in those with versus without a HF hospitalization. Of 14 737 patients, 6893 (47%) were enrolled when hospitalized for HF. Initiation of GDMT was more likely than discontinuation following a HF hospitalization compared to a control group of patients without a HF hospitalization (odds ratio range 2.1-4.0 vs. 1.4-1.6 for the individual medications), although the proportion of patients not on GDMT was still high (8.1-44.0%). Key patient characteristics triggering less use of GDMT (i.e. less initiation or more discontinuation) were older age and worse renal function. Following a HF hospitalization, initiation of renin-angiotensin system inhibitors/angiotensin receptor-neprilysin inhibitors or beta-blockers was associated with lower and their discontinuation with higher mortality risk, but no association with mortality was observed for initiation/discontinuation of mineralocorticoid receptor antagonists. CONCLUSIONS: Following a HF hospitalization, initiation of GDMT was more likely than discontinuation, although still limited. Perceived or actual low tolerance were barriers to GDMT implementation. Early re-/initiation of GDMT was associated with better survival. Our findings represent a call for further implementing the current guideline recommendation for an early re-/initiation of GDMT following a HF hospitalization.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".