Efficacy and Safety of Vildagliptin as an Add-On Therapy in Inadequately Controlled Type 2 Diabetes Patients Treated With Basal Insulin
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to investigate the efficacy and safety of vildagliptin as an add-on therapy for patients with type 2 diabetes mellitus inadequately controlled with basal insulin. METHODS: Twenty-four patients treated with basal insulin and oral anti-diabetes drugs were randomly allocated into two groups: the control group (did not receive any add-on drugs) and vildagliptin group (received vildagliptin 100 mg/day for 6 months). The primary outcome was changes in hemoglobin A1c (HbA1c) from baseline to end of study. RESULTS: Treatment with vildagliptin significantly reduced HbA1c from 8.1±0.7% at baseline to 7.1±0.7% (P < 0.01), while there was no significant change of HbA1c in the control group. Vildagliptin group showed significant reduction of HbA1c compared with control group (-1.0±0.3% vs. 0.2±0.8%, P < 0.01). In addition, vildagliptin group showed a significant increase in 1,5-anhydroglucitol compared with the control group (4.5 ± 3.4 vs. 0.5 ± 4.1 μg/mL, P < 0.05). Mild hypoglycemia was reported in one patient of the vildagliptin group and two patients of the control group. CONCLUSION: Vildagliptin improved glycemic control without increasing hypoglycemia in Japanese type 2 diabetes inadequately controlled with basal insulin treatment and other oral anti-diabetes drugs. This study was registered with UMIN (University Hospital Medical Information Network ID#000010849).
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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".