What Is the Role of a Specialist Assessment Clinic for FND? Lessons From Three National Referral Centers
Bibliographic record
Abstract
OBJECTIVE: A growing interest in functional neurological disorders (FND) has led to the development of specialized clinics. This study aimed to better understand the structure and role of such clinics. METHODS: Data were retrospectively collected from clinical records at three national referral centers, two specifically for motor FND and one for FND in general. Data were for 492 consecutive patients referred over a 9- to 15-month period: 100 from the United Kingdom clinic, 302 from the Swiss clinic, and 90 from the Canadian clinic. Data included symptom subtype and duration, comorbid pain and fatigue, disability, and treatment recommendations. RESULTS: The mean age of the 492 patients was 44 years, and most (73%) were female. Most had a prolonged motor FND (mean symptom duration of 6 years); 35% were not working because of ill health, 26% received disability benefits, and up to 38% required a care giver for personal care. In the Swiss cohort, 39% were given a diagnosis of another somatic symptom disorder rather than an FND diagnosis. Pain was common in the United Kingdom (79%) and Canada (56%), as was fatigue (48% and 47%, respectively). Most patients (61%) were offered physiotherapy; referral to neuropsychiatry or psychology differed across centers (32%-100%). CONCLUSIONS: FND specialty clinics have an important role in ensuring correct diagnosis and appropriate treatment. Most patients with motor FND require specialized neurophysiotherapy. Patients readily accepted an integrated neuropsychiatric approach. Close collaboration between FND clinics and acute neurology facilities might improve early detection of FND and could improve 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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".