P.008 Developing the Calgary Functional Movement Disorder Registry: a preliminary report and baseline patient characteristics
Bibliographic record
Abstract
Background: Functional movement disorder (FMD), a subtype of functional neurological disorder, is a complex neuropsychiatric syndrome characterized by inconsistent and incongruent motor symptoms, such as tremor and gait disorder. Despite its prevalence and associated disability, FMD remains understudied. The multidisciplinary FMD Clinic in Calgary, Alberta offers an opportunity to describe characteristics of FMD, focusing on sex and gender differences, neuropsychiatric risk factors, healthcare utilization and motor phenotypes. Methods: This ongoing registry study evaluates adult FMD patients seen in the Calgary FMD Clinic by a movement disorders neurologist and neuropsychiatrist. Patients undergo detailed movement disorders and neuropsychiatric assessments, including identifying motor phenotypes, psychiatric comorbidities, and relevant psychological traits. Standardized scales evaluate symptom severity and impact. Descriptive statistics and measure of variance will be calculated for variables of interest. Results: The Calgary FMD Registry was approved in March 2024, with 53 participants currently enrolled. Data collection for this study is projected to conclude in March 2025. Conclusions: The Calgary FMD Registry is the first of its kind to systematically characterize FMD based on both movement disorders and neuropsychiatric variables. This study aims to improve our understanding of neuropsychiatric factors related to FMD. Future studies from this registry will examine short- and long-term 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".