The Difference in Glucagon Response to Breakfast Between Non-Obese Patients With Long-Duration Type 1 and Type 2 Diabetes
Bibliographic record
Abstract
Background: A balanced action of insulin and glucagon is essential for treating diabetes. This study aimed to assess the change in blood glucagon levels from fasting to a postprandial state and to compare them between patients with type 1 diabetes (T1DM) and type 2 diabetes (T2DM). Methods: This study enrolled patients with T1DM (n = 13) who had undetectable serum C-peptide levels (< 0.02 ng/mL) and patients with T2DM (n = 13) whose age, gender, and body mass index were matched to cases (1:1) as controls. Plasma glucose, serum C-peptide, and plasma glucagon in fasting and 2 h after consuming a standard breakfast for diabetic patients were measured and compared between groups. Results: There were no significant differences in plasma glucose and hemoglobin A1c levels between patients with T1DM and T2DM. However, fasting plasma glucagon levels were significantly lower in patients with T1DM than those in patients with T2DM (19.2 ± 13.0 pg/mL vs. 31.6 ± 18.3 pg/mL, P = 0.029). Furthermore, the glucagon’s response to a standardized meal for diabetic patients differed between patients with T1DM and T2DM. Conclusions: The significant difference in glucagon response to the meal may be caused by the abnormal postprandial secretion of glucagon in patients with T1DM. The nutrient ratio of the meal may also influence glucagon secretion. J Endocrinol Metab. 2022;12(4-5):134-139 doi: https://doi.org/10.14740/jem834
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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 | 0.001 | 0.000 |
| 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) | 0.002 | 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".