Comparative assessment of treatment outcomes of empagliflozin add-on metformin and sitagliptin add-on metformin therapies in uncontrolled type 2 diabetes mellitus: findings from an observational study in Pakistan
Bibliographic record
Abstract
BACKGROUND: Uncontrolled type 2 diabetes mellitus warrant the utilization of different combination antidiabetic therapies, however, the addition of these newer agents as add-on therapy increases the risk of side effects and needs to be further investigated in terms of their risk to benefit to the patient. Therefore, the current study aims to evaluate the clinical and safety outcomes in patients taking empagliflozin and Sitagliptin in addition to metformin. METHOD: A cross-sectional study was conducted using a non-probability consecutive sampling technique to gather data at the Diabetes and Foot Care Clinic in Abbottabad from July 2023 to December 2023. This is an exploratory observational study in which a total of 155 study participants were selected and divided into two groups: Group A, treated with Sitagliptin add-on Metformin (n = 79), and Group B, treated with Empagliflozin add-on Metformin (n = 76), Biochemical parameters (HbA1c, serum creatinine) were collected and eGFR was calculated at baseline and after a 3-month follow-up. All statistical analyses were performed using IBM SPSS version 23. RESULTS: Among the participant's majority (53.5%) were males whereas the mean age of the participants was 51.7 ± 10.5 years. Baseline HbA1c and serum creatinine of all the patients were found to be 9.5 ± 1.8% and 1.02 ± 0.2 mg/dL respectively. There was a statistically significant decrease in mean HbA1c values in both the groups at baseline and follow-up (p < 0.001) whereas both the groups were found to be similar in their ability to reduce HbA1c (p = 0.25). Furthermore, there was a statistically significant decrease in serum creatinine values in both the groups at baseline and follow-up (p = 0.002) whereas Empagliflozin add-on Metformin was found to have more ability to reduce serum creatinine (p = 0.01) as compared to Sitagliptin add-on Metformin (p = 0.06). As a result, Empagliflozin add-on Metformin improved the patients' eGFR significantly (p = 0.001). CONCLUSION: Empagliflozin as add on therapy in uncontrolled T2DM provided improvements in patients HbA1c, serum creatinine, and eGFR hence improving overall clinical outcomes and patient safety.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".