Sodium–glucose cotransporter 2 inhibition through henagliflozin ameliorates cognitive impairment in patients with type 2 diabetes
Bibliographic record
Abstract
AIMS/INTRODUCTION: To assess whether the sodium-glucose cotransporter 2 inhibitor, henagliflozin, improves cognitive impairment in patients with type 2 diabetes. MATERIALS AND METHODS: We carried out a prospective study on 290 patients with type 2 diabetes and cognitive impairment. Montreal Cognitive Assessment scores and plasma phosphorylated tau181 levels were used to assess cognition. The association between henagliflozin use and changes in cognition was examined using multivariable logistic regression analysis. RESULTS: Montreal Cognitive Assessment scores at enrollment and after 6 months were 21 (interquartile range [IQR]19-23) versus 22 (IQR 20-25; P < 0.0001) in all patients, 21 (IQR 19-23) versus 24 (IQR 22-26; P < 0.0001) in the henagliflozin group and 21 (IQR 19-22) versus 21 (IQR 19-23; P > 0.05) in the non-sodium-glucose cotransporter 2 inhibitor group. Logistic regression analysis showed that henagliflozin treatment was associated with Montreal Cognitive Assessment score improvement independent of potential confounders (odds ratio [OR] 3.670, 95% confidence interval [CI] 2.224-6.056, P < 0.0001). Additionally, plasma phosphorylated tau181 levels significantly decreased at 6-month follow up in all patients (OR 11.5, 95% CI 9.9-13.7 vs OR 10.1, 95% CI 7.8-12.9, P < 0.0001) and in the henagliflozin group (OR 11.5, 95% CI 10.3-13.0 vs OR 9.2, 95% CI 7.1-10.7, P < 0.0001), but not in the non-sodium-glucose cotransporter 2 inhibitor group. Henagliflozin treatment was independently associated with decreased phosphorylated tau181 levels (OR 3.670, 95% CI 1.598-4.213, P < 0.0001). CONCLUSIONS: Henagliflozin treatment was independently associated with improvements in Montreal Cognitive Assessment scores and plasma phosphorylated tau181 levels, indicating significant beneficial effects on cognitive impairment in patients with type 2 diabetes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".