Sodium-Glucose Cotransporter 2 Inhibitors Reduce Prandial Insulin Doses in Type 2 Diabetic Patients Treated With the Intensive Insulin Therapy
Bibliographic record
Abstract
BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are anti-diabetic drugs which improve blood glucose control by blocking reabsorption of glucose from the proximal tubule of kidney. Anti-atherosclerotic properties and cardiovascular protective effects of SGLT2i have been demonstrated by recent studies; however, the efficacy and safety of addition of SGLT2i to the intensive insulin therapy remain largely unknown. METHODS: We retrospectively picked up patients hospitalized for treatment of type 2 diabetes, who had been treated by the intensive insulin therapy and whose treatment using by SGLT2i started during their hospitalization. Such patients were picked up between June 2014 and May 2017 based on medical charts. RESULTS: We found 12 eligible patients. Observation period was 10.2 ± 4.7 days, and SGLT2i was started at 12.2 ± 12.9 days after the admission. During observation period, nobody developed hypoglycemia. In spite of showing decrease of blood glucose (non-significant) before each meal, the addition of SGLT2i significantly reduced daily prandial insulin doses by approximately 4.6 units/day (-66%). The SGLT2i addition also decreased body weight by approximately 1.3 kg. CONCLUSION: Present study demonstrated that the addition of SGLT2i to intensive insulin therapy reduced prandial insulin doses and body weight, without the development of hypoglycemia. This result may be due to SGLT2i-mediated improvement of postprandial hyperglycemia by increasing urinary glucose excretion not via insulin secretion.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".