Effects of Sacubitril/Valsartan on all-cause hospitalizations in heart failure: participant-level pooled analysis of PARADIGM-HF and PARAGON-HF
Bibliographic record
Abstract
Abstract Background Sacubitril/valsartan is indicated to reduce the risk of cardiovascular (CV) death and heart failure (HF) hospitalizations in patients with chronic HF. However, many of these patients are older and have multiple comorbidities that increase the risk of hospitalizations other than HF, yet the effects of sacubitril/valsartan on hospitalizations of any cause have not been well described. Methods PARADIGM-HF and PARAGON-HF were phase-3, global multicenter randomized clinical trials that evaluated sacubitril/valsartan versus enalapril (in PARADIGM-HF) or valsartan (in PARAGON-HF) across the spectrum of left ventricular ejection fraction (LVEF; ≤40% in PARADIGM-HF and ≥45% in PARAGON-HF). We pooled individual participant-level data from these 2 trials to examine the effects of sacubitril/valsartan on time-to-first investigator-reported all-cause and cause-specific hospitalization using Cox proportional hazards models, stratified by geographic region and trial. We additionally examined heterogeneity in treatment response by LVEF. Results Over 2.8 years median follow-up, among 13,194 participants in the pooled PARADIGM-HF/PARAGON-HF, sacubitril/valsartan significantly reduced the risk of all-cause hospitalizations compared with renin-angiotensin system inhibitor (HR 0.92; 95% CI 0.88-0.97; P=0.002); Figure 1 Panel A. The absolute risk reduction (ARR) was 2.1 per 100 patient-years corresponding to a number-needed-to-treat (NNT) of 48 patient-years of treatment exposure to prevent 1 all-cause hospitalization. Reductions in overall hospitalizations among patients with identifiable causes (N=5,783) seemed to be primarily driven by lower rates of cardiac and pulmonary hospitalizations associated with sacubitril/valsartan. Patients treated with sacubitril/valsartan did not have a higher rate of composite non-cardiac hospitalizations (Figure 1 Panel B). Similarly, sacubitril/valsartan reduced the risk of the composite of all-cause hospitalization or all-cause mortality (HR 0.92; 95% CI 0.87-0.96; P<0.001), with an ARR of 2.5 per 100 patients-years and an NNT of 40 patient-years. For all-cause hospitalization, we observed significant heterogeneity by LVEF as a continuous measure (Pinteraction=0.027); treatment effects were most apparent in those with an LVEF below 60% (HR 0.91 95% CI 0.86-0.96; Figure 2). Conclusions In a pooled analysis of >13,000 patients with chronic HF, sacubitril/valsartan reduced hospitalization for any reason with benefits most apparent among those with an LVEF below normal.
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 | 0.027 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.034 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".