One year remission of type 1 diabetes mellitus in a patient treated with sitagliptin
Bibliographic record
Abstract
UNLABELLED: Type 1 diabetes mellitus (T1DM) is a chronic disease characterized by the autoimmune destruction of pancreatic β-cells. This paper describes the case of a 19-year-old male patient who presented with glutamic acid decarboxylase (GAD) antibody positive and diabetic ketoacidosis, which mandated intensive insulin treatment. Once the ketoacidosis was controlled, an oral dose of 100 mg of sitagliptin was administered once a day. Ketoacidosis was managed by insulin and insulin daily requirement began to dwindle after one month, until its complete withdrawal at 8 weeks, when partial remission was reached. The patient has now remained on sitagliptin treatment alone for a year, without requiring insulin. The benefit observed with this medication is possibly associated with its immunological effects. Inhibition of dipeptidyl peptidase 4 in animal models deregulates the Th1 immune response, increases secretion of Th2 cytokines, activates CD4+CD25+FoxP3+ regulatory T-cells, and prevents IL17 production. LEARNING POINTS: The use of insulin-dose-adjusted HbA1c constitutes the best way to define partial remission in T1DM patients.The use of sitagliptin in T1DM patients could help to decrease daily requirement of insulin by delaying β-cell loss and improving endogenous insulin production.The determination of antibodies against insulin, islet cells, and GAD permits differentiation of T1DM patients from those with atypical or ketosis-prone diabetes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".