Glycogen Storage Disease Type Ia: Current Management Options, Burden and Unmet Needs
Bibliographic record
Abstract
Glycogen storage disease type Ia (GSDIa) is caused by defective glucose-6-phosphatase, a key enzyme in carbohydrate metabolism. Affected individuals cannot release glucose during fasting and accumulate excess glycogen and fat in the liver and kidney, putting them at risk of severe hypoglycaemia and secondary metabolic perturbations. Good glycaemic/metabolic control through strict dietary treatment and regular doses of uncooked cornstarch (UCCS) is essential for preventing hypoglycaemia and long-term complications. Dietary treatment has improved the prognosis for patients with GSDIa; however, the disease itself, its management and monitoring have significant physical, psychological and psychosocial burden on individuals and parents/caregivers. Hypoglycaemia risk persists if a single dose of UCCS is delayed/missed or in cases of gastrointestinal intolerance. UCCS therapy is imprecise, does not treat the cause of disease, may trigger secondary metabolic manifestations and may not prevent long-term complications. We review the importance of and challenges associated with achieving good glycaemic/metabolic control in individuals with GSDIa and how this should be balanced with age-specific psychosocial development towards independence, management of anxiety and preservation of quality of life (QoL). The unmet need for treatment strategies that address the cause of disease, restore glucose homeostasis, reduce the risk of hypoglycaemia/secondary metabolic perturbations and improve QoL is also discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".