Gender Differences in Cardiac Function Following Three-Month Administration of Tofogliflozin in Patients With Diabetes Mellitus
Bibliographic record
Abstract
Background: Patients with type 2 diabetes mellitus (T2DM) are at increased risk for impairment in heart failure and diastolic relaxation while preserving ejection fraction (EF). Recently, several sodium glucose cotransporter-2 (SGLT2) inhibitors have demonstrated to decrease cardiovascular disease (CVD) events in elderly diabetic patients, although gender difference in the effect of SGLT2 inhibitors is unknown. The objective of the present study was to evaluate gender difference in the effect of tofogliflozin, one of the SGLT2 inhibitors, on CVD function in patients with diabetes mellitus. Methods: This was a retrospective study. Patients received 20 mg of tofogliflozin daily for 3 months. EF, ratio of early filling to atrial filling (E/A), a change in mitral inflow E and mitral e' annular velocities (E/e'), left atrial dimension (LAD) and maximal diameter of inferior vena cava (IVC max ), including various physiological parameters were measured between baseline, 1 month and 3 months after administration of tofogliflozin. Interaction between gender and time after administration was evaluated using mixed effect model. Results: The results showed significant decrease in E/e' (P < 0.01) and significant interaction between time and gender in E/A (P < 0.01), following administration of tofogliflozin for 3 months. EF was constantly higher significantly in women (P < 0.01). Conclusion: It is concluded that 3-month administration of tofogliflozin decreased E/e' with gender difference in EF and E/A. J Clin Med Res. 2020;12(8):530-538 doi: https://doi.org/10.14740/jocmr4278
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".