Movement Disorders and Other Neurologic Impairment Associated With Hypomagnesemia
Bibliographic record
Abstract
Purpose of Review: The objective of this study was to explore the clinical spectrum of movement disorders and associated neurologic findings in hypomagnesemia and challenges in diagnosis and treatment. Recent Findings: Sixty patients were identified in the literature for analysis. Movement disorders observed were postural tremor (23.3%, n = 14), resting tremor (8.3%, n = 5), intention tremor (10%, n = 6), ataxia involving the trunk (48.3%, n = 29) or limbs (25%, n = 15) and dysarthria (21.7%, n = 13), athetosis (8.3%, n = 5), myoclonus (6.7%, n = 4), and chorea (1.8%, n = 1). Symptoms may be accompanied by downbeat nystagmus, tetany, drowsiness, vertigo, and proximal muscle weakness. Residual deficits were noted in 16 (26.67%) patients. Serum magnesium was 1.3 mg/dL or lower in 53 patients (88.3%). Imaging findings include bilateral cerebellar (20%, n = 11) and vermis hyperintensities (9.09%, n = 5) and normal imaging. Proton pump inhibitors are the commonest etiology. Summary: The movement disorders linked with hypomagnesemia can be associated with varied neurologic symptoms. A high degree of suspicion will enable early diagnosis to prevent residual deficits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".