Effects of Sitagliptin on Pancreatic Beta Cell Function and Microangiopathy in Japanese Patients With Type 2 Diabetes Mellitus: Follow-Up for 4 Years
Bibliographic record
Abstract
Background: This study was aimed at investigating the effect of long-term sitagliptin treatment in improving the pancreatic beta cell function and its influence on microangiopathy in patients with type 2 diabetes mellitus. Methods: The study was designed as a retrospective analysis of the data of 27 patients with type 2 diabetes mellitus who did not have any evident reduction of the renal function and had received sitagliptin treatment for 4 years or longer. The fasting plasma C-peptide level corrected for the fasting blood glucose level (C-peptide index (CPI)), hemoglobin A1c (HbA1c) and body weight were determined every year during the 4-year period, and the status of retinopathy and nephropathy at the end of the fourth year of sitagliptin treatment was compared with the pre-treatment status. Results: Both the HbA1c and body weight were significantly decreased by 6 months after the start of treatment. Thereafter, the HbA1c showed no further rise during the subsequent 4-year period, while the body weight continued to decrease over the 4-year period. No significant change of the CPI, as compared to the pre-treatment level (0.95 ± 0.49), was observed at any time during the follow-up. The retinopathy and nephropathy remained unchanged in severity in most cases; however, progression of retinopathy was seen in seven cases (29%) and that of nephropathy in three cases (11%). Conclusions: Maintenance of good blood glucose control for 4 years by sitagliptin treatment allowed the pancreatic beta cell function to be preserved. However, it was not possible to suppress progression of microangiopathy completely by treatment for a short period of 4 years. J Endocrinol Metab. 2015;5(4):245-249 doi: http://dx.doi.org/10.14740/jem297w
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".