Effects of selective heart rate reduction with ivabradine on left ventricular remodelling and function: results from the SHIFT echocardiography substudy
Bibliographic record
Abstract
AIMS: The SHIFT echocardiographic substudy evaluated the effects of ivabradine on left ventricular (LV) remodelling in heart failure (HF). METHODS AND RESULTS: Eligible patients had chronic HF and systolic dysfunction [LV ejection fraction (LVEF) ≤35%], were in sinus rhythm, and had resting heart rate ≥70 bpm. Patients were randomly allocated to ivabradine or placebo, superimposed on background therapy for HF. Complete echocardiographic data at baseline and 8 months were available for 411 patients (ivabradine 208, placebo 203). Treatment with ivabradine reduced LVESVI (primary substudy endpoint) vs. placebo [-7.0 ± 16.3 vs. -0.9 ± 17.1 mL/m(2); difference (SE), -5.8 (1.6), 95% CI -8.8 to -2.7, P< 0.001]. The reduction in LVESVI was independent of beta-blocker use, HF aetiology, and baseline LVEF. Ivabradine also improved LV end-diastolic volume index (-7.9 ± 18.9 vs. -1.8 ± 19.0 mL/m(2), P= 0.002) and LVEF (+2.4 ± 7.7 vs. -0.1 ± 8.0%, P< 0.001). The incidence of the SHIFT primary composite outcome (cardiovascular mortality or hospitalization for worsening HF) was higher in patients with LVESVI above the median (59 mL/m2) at baseline (HR 1.62, 95% CI 1.03-2.56, P= 0.04). Patients with the largest relative reductions in LVESVI had the lowest event rates. CONCLUSION: Ivabradine reverses cardiac remodelling in patients with HF and LV systolic dysfunction.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".