Importance of Distinguishing Between Mitochondrial Encephalomyopathy With Elderly Onset of Stroke-Like Episodes and Cerebral Infarction
Bibliographic record
Abstract
The most common disease-causing mitochondrial DNA (mtDNA) mutation in mitochondrial encephalomyopathy (ME) with lactic acidosis and stroke-like episodes (MELAS) is m.3243A>G. In the future, the incidence of patients with cerebral infarction and diabetes mellitus is expected to increase tremendously. Additionally, the A3243G mutation typical of diabetes is estimated to be present in approximately 2% of all diabetes patients, which suggests that the potential disease population with a mitochondrial disorder is greater than previously thought, and there may have been many cases among the elderly that were misdiagnosed. Considering this background, MELAS with the onset of stroke-like episodes should be considered an important differential diagnosis for elderly patients with cerebral infarction, although it might have been overlooked until now. A 68-year-old Japanese female developed convulsive seizures and was admitted to Hospital of International University of Health and Welfare for epilepsy. She had been hospitalized twice in the previous year for cerebral infarction and seizures. She experienced sensorineural hearing loss at a young age. Thus, although she was elderly, we suspected MELAS and detected elevations of pyruvic and lactic acid. A genetic test revealed a point mutation in the mtDNA (m.3243A>G) that led to a definitive diagnosis of MELAS. To date, MELAS has been regarded as a disease of the relatively young. The incidence of patients with cerebral infarction and diabetes mellitus is expected to greatly increase. Thus, we should evaluate cerebral infarction in the elderly with caution to prevent missed diagnoses of MELAS.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".