A Patient with Proximal Myotonic Myopathy and Parkinsonism
Bibliographic record
Abstract
INTRODUCTION: There are two case reports of patients who had proximal myotonic myopathy (PROMM)/myotonic dystrophy (DM) Type 1 and parkinsonism. The combination of myotonic myopathy and parkinsonism is so rare that it may appear to be just a coincidence. However, previous neuropathological examinations of patients who had myotonic dystrophy showed that there were intracytoplasmic inclusion bodies in the nigra and striatum, which raises the possibility that myotonic myopathy may be associated with parkinsonism. In this report we describe a patient with PROMM and a clinically definite parkinsonism to highlight this possibility. CASE REPORT: A 65-year-old man developed proximal muscle weakness, myotonia and atrophy around the age of 55 and was diagnosed as having PROMM at the age of 62. Needle electromyography and muscle biopsy supported the diagnosis. A gene study of the DM Type 1 showed a normal CTG repeat length. At age 63, he developed rest tremor, bradykinesia, hypomimia, stooped posture, and gait disturbance. The postural instability worsened rapidly. The tremor and rigidity were much worse in his right side, where myotonia was more severe. Levodopa therapy was only partially effective. CONCLUSION: This is a case report of a patient with PROMM that shows an association with a rapidly progressive form of parkinsonism. We suggest that this may be a novel form of a neurodegenerative disorder, which we name 'Parkinsonism-Myotonic Myopathy-Complex'.
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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) | 0.001 | 0.001 |
| 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 | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".