Network Meta-Analysis of Quality of Life in Heart Failure With Reduced Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: Although the effects of various combinations of treatments on mortality and morbidity outcomes in heart failure with reduced ejection fraction (HFrEF) have been evaluated, the impact on quality of life is unknown. This study evaluated and compared the composite impact of pharmacological therapies on quality of life in HFrEF using a frequentist network meta-analysis and systematic review methodology. METHODS: We searched MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials for randomized controlled trials published between January 1, 2021 and August 10, 2024. We included all contemporary and efficacious HFrEF therapies used in adults. The primary outcome was change in quality of life measured through the Kansas City Cardiomyopathy Questionnaire and the Minnesota Living with Heart Failure Questionnaire, expressed as mean difference (MD). RESULTS: We identified 41 randomized controlled trials representing 41 145 patients (76.5% male). The trials had a median of 276 participants (105-464), a mean left ventricular ejection fraction of 28%, and a median follow-up time of 5 months (3-8). A combination of angiotensin receptor blocker/neprilysin inhibitors (ARNi)+β-blockers (BB)+sodium-glucose cotransporter 2 inhibitors (SGLT2i; MD, +5.3 [+0.4, +10.3]) was the most effective at improving quality of life followed by ARNi+BB+mineralocorticoid receptor antagonists (MRA)+SGLT2i (MD, +7.1 [-1.0 to +15.2]), ACE inhibitor+BB+MRA+SGLT2i (MD, +5.3 [-2.6, to +13.3]), and ACE inhibitor+BB+MRA+ivabradine (MD, +5.2 [-3.1 to +13.6]), which were not statistically significant. Individually, the most effective treatments for improving quality of life were SGLT2i (MD, +3.4 [+1.4 to +5.30]), ivabradine (MD, +3.3 [+0.1 to +6.4]), ARNi (MD, +2.6 [-3.2 to +8.5]), and MRA (MD, +1.8 [-4.8 to +8.4]). CONCLUSIONS: A composite of ARNi+BB+SGLT2i or ARNi+BB+MRA+SGLT2i was the most effective at improving quality of life in patients with HFrEF.
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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 | 0.027 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.045 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".