Efficacy of combination therapy with GABA, a DPP-4i and a PPI as an adjunct to insulin therapy in patients with type 1 diabetes
Bibliographic record
Abstract
Introduction: The purpose of this retrospective clinic chart review study was to determine the potential of a combination therapy (CT) consisting of γ-aminobutyric acid (GABA), a dipeptidyl peptidase-4 inhibitor (DPP-4i), and a proton pump inhibitor (PPI) to improve glycemic control as an adjunct to insulin therapy in patients with type 1 diabetes (T1D). Research design and methods: Nineteen patients with T1D on insulin therapy were treated with additional CT in oral form. Fasting blood glucose (FBG), HbA1c, insulin dose-adjusted HbA1c (IDA-A1c), daily insulin dose, insulin/weight ratio (IWR), and fasting plasma C-peptide were measured after 26-42 weeks of treatments. Results: FBG, HbA1c, IDA-A1c, insulin dose and IWR were all significantly decreased while plasma C-peptide was significantly increased by the CT. Treatment outcomes were further analyzed by separation of the 19 patients into two groups. One group started on the CT within 12 months of insulin treatment (early therapy, 10 patients) and another group started on this therapy only after 12 months of insulin treatment (late therapy, 9 patients). FBG, IDA-A1c, insulin dose, and IWR decreased significantly in both the early and late CT groups, however to a better extent in the early therapy group. Moreover, plasma C-peptide increased significantly only in the early therapy group, and 7 of the 10 patients in this group were able to discontinue insulin treatment while maintaining good glycemic control to study end compared with none of the 9 patients in the late therapy group. Conclusion: These results support the concept that the combination of GABA, a DPP-4i and a PPI as an adjunct to insulin therapy improves glycemic control in patients with T1D, and that the insulin dose required for glycemic control can be reduced or even eliminated in some patients receiving this novel therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".