SGLT2 Inhibitors and Cardiac Remodelling: A Systematic Review and Meta-Analysis of Randomized Cardiac Magnetic Resonance Imaging Trials
Bibliographic record
Abstract
Abstract Aims Recent large randomized controlled trials (RCTs) have demonstrated efficacy of sodium-glucose cotransporter-2 inhibitors (SGLT2i) in both preventing and treating heart failure (HF). SGLT2i-induced reversal of left ventricular remodelling has been proposed as a mechanism contributing to this effect. Methods and results We performed a systematic review and meta-analysis of RCTs to compare SGLT2i versus placebo (treatment duration >3 months) on cardiac remodelling parameters as measured by cardiac magnetic resonance imaging (cMRI) in patients with HF and/or diabetes. The PubMed and ClinicalTrials.gov databases were searched until 15 June 2021. Our primary outcome was change in absolute left ventricular mass (LVM) from baseline to study endpoint. Secondary outcomes included changes in LVM indexed to body surface area, left ventricular end-systolic volume (LVESV), left ventricular end-diastolic volume (LVEDV), and left ventricular ejection fraction (LVEF) from baseline to study endpoint. The Cochrane Collaboration's tool was used to assess risk of bias. Five studies representing 408 patients were included. SGLT2i was associated with greater LVM regression compared to placebo (MD, −5.76 g; 95% CI, −10.87 g to −0.64 g, I2 = 73%; overall effect, P < 0.03; four RCTs). Statistical subgroup differences were not observed in our sensitivity analysis focusing on HF with reduced ejection fraction (P = 0.37) and were observed in our sensitivity analysis focusing on diabetes (P < 0.001). SGLT2i was not associated with statistical changes in LV mass indexed to body surface area (I2 = 75%; P = 0.16; five RCTs), LVESV (I2 = 87%; P = 0.07; five RCTs), LVEDV (I2 = 81%; P = 0.20; five RCTs), nor LVEF (I2 = 85%; P = 0.19; five RCTs) versus placebo. Sixty per cent of RCTs had low risk of bias. Conclusions Sodium-glucose cotransporter-2 inhibitors treatment was associated with a reduction in left ventricular mass as assessed by cMRI.
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| 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".