The Impact of Sotagliflozin on Renal Function, Albuminuria, Blood Pressure, and Hematocrit in Adults With Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE In people with type 2 diabetes, sodium–glucose cotransporter 2 inhibitors (SGLT2i) reduce cardiovascular risk and progression of diabetic kidney disease. Our aim was to determine whether sotagliflozin (SOTA), a dual SGLT1i and SGLT2i, had favorable effects on clinical biomarkers suggestive of kidney protection in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS In this 52-week pooled analysis, 1,575 adults enrolled in the inTandem1 and inTandem2 trials were randomized to SOTA 200 mg, 400 mg, or placebo in addition to optimized insulin therapy. Changes in cardiorenal biomarkers were assessed. RESULTS At 52 weeks, in response to SOTA 200 and 400 mg, the placebo-corrected least squares mean change from baseline in estimated glomerular filtration rate was −2.0 mL/min/1.73 m2 (P = 0.010) and −0.5 mL/min/1.73 m2 (P = 0.52), respectively. Systolic blood pressure difference was −2.9 and −3.6 mmHg (P < 0.0001 for both); diastolic blood pressure changed by −1.4 (P = 0.0033) and −1.6 mmHg (P = 0.0008). In participants with baseline urinary albumin-to-creatinine ratio (UACR) ≥30 mg/g, UACR decreased by 23.7% (P = 0.054) and 18.3% (P = 0.18) for SOTA 200 and SOTA 400 mg, respectively, versus placebo. Increases in serum albumin and hematocrit and reductions in uric acid were observed throughout 52 weeks with both SOTA doses. CONCLUSIONS SOTA was associated with short- and long-term renal hemodynamic changes, which were similar to those seen with SGLT2i in type 2 diabetes. Further investigation around cardiorenal effects of SOTA in people with type 1 diabetes is justified.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".