Familial Permanent Neonatal Diabetes with KCNJ11 Mutation and the Response to Glyburide Therapy - A Three-Year Follow-Up
Bibliographic record
Abstract
We describe 3 years follow-up of glyburide therapy in a child with permanent neonatal diabetes mellitus (PND) born to a 19 year-old mother with congenital diabetes mellitus. Genetic analysis identified a KCNJ11 mutation (R201H) in both the child and her mother. After 2 years of insulin therapy, the patient was switched to oral glyburide. After initial stabilization, glyburide therapy resulted in a marked decrease in glucose excursions in comparison to insulin. The patient had 3-10 episodes of hypoglycemia per week, including a total of eight episodes resulting in seizures, while on insulin. In contrast, no severe hypoglycemia was reported on glyburide. The patient's basal C-peptide was undetectable on insulin therapy (< 166 pmol/l) but was easily detectable on glyburide (189-761 pmol/l). The range of HbA1c improved significantly from 8-12% on insulin to 4.7-6% on glyburide. The frequency of glucose monitoring was gradually decreased from 4-8 times to 2-3 times a day on oral glyburide. This report confirms the superiority of sulfonylurea therapy in the treatment of PND with Kir6.2 mutations and shows sustained improved glycemic control over a 3-year follow-up period. Genetic exploration in other family members with diabetes might provide further insight into the nature of familial neonatal 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".