Effects of SGLT2 inhibitors on right ventricular function in heart failure patients: Updated meta-analysis of the current literature
Bibliographic record
Abstract
BACKGROUND: There is some discrepancy in current studies concerning the effect of sodium-glucose cotransporter type 2 inhibitors (SGLT2i) on right ventricular (RV) functions in heart failure (HF) patients. Hence, this meta-analysis was focused on determining the impact of SGLT2i on RV functions in such individuals. MATERIAL AND METHODS: Two independent investigators searched PubMed, Google Scholar, and the Cochrane Library for articles of interest. To analyze heterogeneity, Higgins' I2 as well as prediction intervals and Egger's test were used to assess heterogeneity. The Newcastle-Ottawa standard ratings approach was used to assess the quality of observational studies. The ROBINS-I risk of bias algorithm was used to assess bias risks of randomized studies. RESULTS: This meta-analysis evaluated 8 studies in total. Over the follow-up time frame, patients who used SGLT2i had substantially lower systolic pulmonary artery pressure and higher tricuspid annular plane systolic excursion values (mean difference [MD] = -5.23 [-7.81; -2.66] and, MD = 1.47 [1.01; 1.93]; P <0.01, respectively). There was no significant difference in RVS' values between follow-up and baseline (MD = 1.54 [-0.19; 3.26]; P = 0.08). However, as compared to the baseline period, fractional area contraction values were substantially larger at the end of the follow-up (MD = 5.52 [4.23; 6.82]; P <0.01). CONCLUSION: To the best of our knowledge, this is the first meta-analysis assessing the impact of SGLT2i on RV function in HF patients. Our findings suggest that SGLT2i may improve RV performance in HF patients.
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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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.054 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".