Functional neurological disorder treated with psychoeducation: A case report
Bibliographic record
Abstract
RATIONALE: Psychogenic tremor (PT) is the most common subtype of psychogenic movement disorder, characterized by involuntary movement, and is usually related to occupational injuries or accidents. Psychogenic movement disorder falls under the category of functional neurological disorders, which are diagnosed based on the criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders. PATIENT CONCERNS: A 25-year-old Saudi male with a history of recurrent superior ventricular tachycardia presented to the emergency department with tremors affecting all his extremities for 8 days. Tremors were nonrhythmic, continuous, and worsened over time and were exacerbated by reaching objects. There was no history of similar presentations or neurological diseases. DIAGNOSES: Examination revealed high-frequency, high-amplitude tremors and rigidity in all extremities, and hyperreflexia in the lower limbs. Laboratory findings were unremarkable; thus, the psychiatric team was consulted for possible PTs. INTERVENTIONS: Psychiatric assessments showed no evidence of psychiatric disorders. The patient only received psychoeducation about his diagnosis. OUTCOMES: The tremor was completely resolved by the time of discharge. LESSONS: In our case, the patient's PT resolved entirely with education alone, differing from previous cases that included psychotherapy and medication, emphasizing the importance of the doctor-patient relationship and the need for future research on effective approaches to delivering diagnosis to patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".