Add-On Sitagliptin Therapy for Insulin-Treated Type 2 Diabetes: An Analysis of Hemoglobin A1c and Other Variables Using ASSIST-K Follow-Up Data
Bibliographic record
Abstract
Background: Sitagliptin was the first dipeptidyl peptidase-4 (DPP-4) inhibitor approved in Japan. Its efficacy and safety have been demonstrated, both as monotherapy and in combination with oral antidiabetic agents or insulin. However, reduction of hemoglobin A1c (HbA1c) by sitagliptin is insufficient in some patients. Therefore, data from an observational study of sitagliptin as add-on therapy to insulin in patients with type 2 diabetes (ASSIST-K) were used to conduct factor analysis of the 12-month changes in HbA1c, body weight, estimated glomerular filtration rate (eGFR), and adverse events (AEs). Methods: At member institutions of Kanagawa Physicians Association specializing in diabetes, outpatients with type 2 diabetes receiving insulin were followed for 12 months after addition of sitagliptin. The HbA1c (National Glycohemoglobin Standardization Program), blood glucose (fasting/postprandial), body weight, eGFR, and AEs were evaluated at each specified time. Multivariate analysis was performed by using sex and age as explanatory variables and the following response variables: the change in HbA1c, body weight, or eGFR after 12 months of sitagliptin treatment, and occurrence of AEs. Results: Of 1,168 patients registered in the ASSIST-K study, 412 patients were included in this analysis, excluding those not receiving insulin before sitagliptin, those in whom the 12-month change in HbA1c could not be calculated, and those with missing data on explanatory variables. There was a significant decrease in HbA1c and eGFR, but no significant change in body weight. AEs observed in > 10 patients were severe hypoglycemia (14 patients, 3.4%) and constipation (13 patients, 3.2%). Factor analysis revealed the following points: 1) Concurrent dyslipidemia and baseline HbA1c influenced the 12-month change in HbA1c; 2) Baseline body mass index and HbA1c influenced the 12-month change in body weight; and 3) Concurrent dyslipidemia, baseline sulfonylurea treatment, baseline body mass index, and baseline eGFR influenced the 12-month change in eGFR. In addition, the risk of severe hypoglycemia or constipation was significantly influenced by baseline HbA1c. Conclusions: Patients with type 2 diabetes showing higher HbA1c levels after add-on sitagliptin therapy had concurrent dyslipidemia and a lower baseline HbA1c. Severe hypoglycemia or constipation was more likely to occur in patients with a low baseline HbA1c. J Endocrinol Metab. 2018;8(6):126-138 doi: https://doi.org/10.14740/jem540
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".