Pediatric Functional Movement Disorders: Experience from a Tertiary Care Centre
Bibliographic record
Abstract
OBJECTIVES: Functional movement disorders (FMDs) pose significant diagnostic and management challenges. We aimed to study the socioeconomic and cultural factors, underlying psychopathology and the phenomenology of FMDs in children. METHODS: The study is a retrospective chart review of 39 children (16 girls and 23 boys) who attended our neurology OPD and the movement disorders clinic at the National Institute of Mental Health and Neurosciences (NIMHANS) between January 2011 and May 2020. The diagnosis of FMD was based on Fahn and Williams criteria and the patients were either diagnosed as "documented" or "clinically established". All the relevant demographic data including the ethnicity, socioeconomic and cultural background, examination findings, electrophysiological, and other investigations were retrieved from the medical records. RESULTS: The mean age at onset was 12.69 ± 3.13 years. Majority of the children were from urban regions (56.41%) and belonging to low socioeconomic status (46.15%). Thirty (76.92%) were found to have a precipitating factor. Myoclonus was the most common phenomenology observed in these patients (30.76%), followed by tremor (20.51%), dystonia (17.94%), and gait abnormality (7.69%). Chorea (5.12%) and tics (2.56%) were uncommon. Tremor (37.5%) and dystonia (18.75%) were more common in girls, whereas myoclonus (39.13%) was more common in boys. CONCLUSIONS: The symptoms of FMD have great impact on the mental health, social, and academic functioning of children. It is important to identify the precipitating factors and associated psychiatric comorbidities in these children as prompt alleviation of these factors by engaging parents and the child psychiatrist will yield better outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".