Chorea hyperglycemia basal ganglia (CHBG) syndrome: A Case Report
Bibliographic record
Abstract
Chorea, characterized by sudden, involuntary movements of the face and limbs, arises from various causes, including neurodegenerative diseases, metabolic disorders, and structural brain changes, notably in the basal ganglia. Acute lesions in the basal ganglia due to ischemia or vascular pathology can also precipitate chorea. Hyperglycemia-induced basal ganglia changes, termed chorea hyperglycemia basal ganglia, predominantly affect elderly females with type 2 diabetes. We report a 62-year-old female with poorly managed diabetes presenting with involuntary jerking movements, initially in the right leg, progressing to the right arm, face, and lips over three days. Her history included hyperlipidemia and hypertension, and lab results showed significant hyperglycemia (601 mg/dL) [fasting <140 mg/dl], hyponatremia, renal impairment, and a high Hemoglobin A1C (HbA1c) (10.4) [<6 %]. Imaging revealed left putamen hypodensity on Computed Tomography (CT) and confirmed microhemorrhage on magnetic resonance imaging (MRI). Diagnosed with Hyperosmolar Hyperglycemic State (HHS) and hemichorea, she was treated with intravenous (IV) insulin and fluids, leading to symptom resolution within two days. This case highlights the link between non-ketotic hyperglycemia and chorea, involving hyperviscosity-induced GABAergic neuron dysfunction in the putamen. Diagnosis relies on choreiform movements, elevated blood glucose, and striatal hyperintensity on T1 MRI. Effective management includes treating underlying HHS with hydration and glycemic control, occasionally supplemented with anti-chorea medications. Recognizing diabetic striatopathy is crucial for prompt treatment and symptom resolution, emphasizing the need for early diagnosis and intervention in patients with uncontrolled diabetes presenting with new-onset chorea.
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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) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| 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".