Cognitive Function Characteristics in Patients with Myasthenia Gravis
Bibliographic record
Abstract
Introduction: Myasthenia gravis (MG) is one of the most common neuromuscular junction disorders with various clinical presentations. Several studies showed cognitive function decline in MG patients which affects cognitive domains in memory, attention, executive function, and verbal. The involvement of the central cholinergic system, known as central cholinergic deficits are thought to manifests as impaired cognitive function in patients with MG. The purpose of this study was to evaluate cognitive function characteristic in patients with myasthenia gravis. Method: This study used a cross-sectional design, involved 33 myasthenia gravis patients in Neurology Outpatient Clinic of Haji Adam Malik Central General Hospital and 33 subjects in healthy control group. Cognitive function tests were performed using the Indonesia version of Montreal Cognitive Assessment (MoCA-Ina). Mann-whitney test was performed to evaluate cognitive performance difference in both groups. Results: : The results were compared between MG and healthy control group. The mean of MoCA-Ina score was significantly lower in MG group compared to healthy control group. The result of this study showed difference in cognitive performance between MG patients and healthy control group (p<0.001). This study showed delayed memory, attention, verbal, abstraction, visuospatial and executive function performance was decline in MG patients. Conclusion: This study concludes significant difference of cognitive performance based on MoCA-Ina scores between myasthenia gravis patients and healthy control group.
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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 | 0.000 | 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) | 0.001 | 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".