The Effect of Sodium–Glucose Cotransporter 2 Inhibitors on Left Cardiac Remodelling in Heart Failure with Reduced Ejection Fraction: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
ABSTRACT Aims The therapeutic mechanism of sodium–glucose cotransporter 2 inhibitors (SGLT2i) on left cardiac remodelling in patients with heart failure with reduced ejection fraction (HFrEF) is not well-established. This study meta-analysed the impact of SGLT2i on left cardiac structure and function in patients with HFrEF. Methods and results Online databases were queried up to April 2023 for trials reporting indicators of left cardiac structure and function in patients with HFrEF treated with SGLT2i. Data from studies were pooled using a random-effects model to derive weighted mean differences (WMDs) and 95% confidence intervals (CIs). Six trials were included (n = 555). Compared with control, SGLT2i significantly improved left ventricular end-diastolic volume (LVEDV; WMD: −17.07 ml [−23.84, −10.31]; p < 0.001), LVEDV index (WMD: −5.62 ml/m2 [−10.28, −0.97]; p = 0.02), left ventricular end-systolic volume (LVESV; WMD: −15.63 ml [−26.15, −5.12]; p = 0.004), LVESV index (WMD: −6.90 ml/m2 [−10.68, −3.11]; p = 0.001), left ventricular ejection fraction (WMD: 2.71% [0.70, 4.72]; p = 0.008), and left atrial volume index (WMD: −2.19 ml/m2 [−4.26, −0.11]; p = 0.04) in patients with HFrEF. SGLT2i use was associated with a non-significant trend towards a reduction in left ventricular mass index (WMD: −6.25 g/m2 [−12.79, 0.28]; p = 0.06). No significant impact on left ventricular global longitudinal strain was noted (WMD: 0.21% [−0.25, 0.67]; p = 0.38). Conclusions Sodium–glucose cotransporter 2 inhibitors improve cardiac structure and function 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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".