Factors Influencing Changes in Hemoglobin A1c and Body Weight During Treatment of Type 2 Diabetes With Ipragliflozin: Interim Analysis of the ASSIGN-K Study
Bibliographic record
Abstract
BACKGROUND: Ipragliflozin is a selective sodium glucose co-transporter 2 (SGLT2) inhibitor that blocks glucose reabsorption in the proximal tubules. SGLT2 inhibitors are expected to be effective in patients with insulin resistance and obesity, but it is important to select treatment according to patient background factors that minimizes the risk of adverse events. There have been a limited number of investigations into the relationship between the clinical efficacy (reducing hemoglobin A1c (HbA1c) and body weight (BW)) or safety of SGLT2 inhibitors and patient characteristics. METHODS: ASSIGN-K is an investigator-initiated, multicenter, prospective observational study examining the efficacy and safety of ipragliflozin (50 - 100 mg/day for 52 weeks) in Japanese patients with type 2 diabetes mellitus (T2DM) who had inadequate glycemic control with HbA1c ≥ 6.0% (National Glycohemoglobin Standardization Program) despite diet and exercise therapy or diet and exercise plus antidiabetic drug therapy. We conducted an interim analysis of the relationship between changes in HbA1c or BW and characteristics in patients who had been on treatment for more than 12 weeks. RESULTS: In 257 patients completing 12 weeks of treatment, HbA1c decreased significantly from 8.23% to 7.55% (-0.68%, P < 0.01). The change in HbA1c after 12 weeks was -0.17%, -0.33%, and -1.16% when baseline HbA1c was < 7%, 7% to < 8%, and ≥ 8%, respectively (P < 0.05, P < 0.01, and P < 0.01, respectively), and -1.30%, -0.62%, and -0.62% when baseline body mass index (BMI) was < 25, 25 to < 30, and ≥ 30, respectively (all P < 0.01). Stratified analysis showed that age, gender, or BMI did not have a significant influence on the improvement in HbA1c. Multiple regression analysis showed that reduction in HbA1c was greater as baseline HbA1c increased and the duration of diabetes decreased. A higher baseline HbA1c was associated with less weight loss. CONCLUSIONS: Ipragliflozin significantly improved HbA1c in patients with T2DM. HbA1c improved more when baseline HbA1c was higher and the duration of diabetes was shorter, suggesting that current treatment policies for diabetes could be re-examined.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".