Movement Disorders Due to Selective Basal Ganglia Lesions with Uremia
Bibliographic record
Abstract
BACKGROUND: Basal ganglia (BG) lesions are rarely reported in patients with uremia and may manifest by movement disorders. However, their exact incidence and pathogenesis have not been extensively studied. This study aimed to determine the frequency, types, risk variables (clinical, laboratory, and imaging), and manifestations of BG lesions with uremia and patients' neurologic outcomes. METHODS: This observational study included 70 adults (mean age: 45.87 ± 3.36 years; duration of uremia: 5.5 ± 1.5 years). They underwent extensive evaluations (clinical, laboratory, and neuroimaging) and had prospectively evaluated clinically every 3 months for 2 years. Repeated magnetic resonance imaging (MRI) brains were done to patients with movement disorders and correlated with their neurologic outcomes. RESULTS: BG lesions were found in 15 patients (21.4%) and 6 (8.6%) had movement disorders [Parkinsonism (n = 4), choreo-dystonia (n = 1) and dystonia (n = 1)] after the onset of uremia (mean = 10 months). There were no characteristic risk variables that distinguished patients with movement disorders from those without. Five developed movement disorders prior to the period of the study and one was de novo. The majority was females and had diabetes and higher frequencies of abnormal renal dysfunction, metabolic derangements, and white matter hyperintensities in MRIs. Movement disorders persisted in all patients despite the resolution of neuroimaging in three patients. CONCLUSIONS: There is no clear threshold for renal failure to result in movement disorders due to BG lesions. The clinical outcome is variables depending on each patient's comorbidities and complications. Persistent neuronal damage (due to uremic toxins/metabolic/nutritional and ischemic/microvascular factors) has been suggested as the cause of poor neurologic outcomes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".