Functional movement disorder gender, age and phenotype study: a systematic review and individual patient meta-analysis of 4905 cases
Bibliographic record
Abstract
Functional movement disorder (FMD) is a common manifestation of functional neurological disorder presenting with diverse phenotypes such as tremor, weakness and gait disorder. Our current understanding of the basic epidemiological features of this condition is unclear. We aimed to describe and examine the relationship between age at onset, phenotype and gender in FMD in a large meta-analysis of published and unpublished individual patient cases. An electronic search of PubMed was conducted for studies from 1968 to 2019 according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Individual patient data were collected through a research network. We described the distribution of age of onset and how this varied by gender and motor phenotype. A one-stage meta-analysis was performed using multilevel mixed-effects linear regression, including random intercepts for country and data source. A total of 4905 individual cases were analysed (72.6% woman). The mean age at onset was 39.6 years (SD 16.1). Women had a significantly earlier age of onset than men (39.1 years vs 41.0 years). Mixed FMD (23.1%), tremor (21.6%) and weakness (18.1%) were the most common phenotypes. Compared with tremor (40.7 years), the mean ages at onset of dystonia (34.5 years) and weakness (36.4 years) were significantly younger, while gait disorders (43.2 years) had a significantly later age at onset. The interaction between gender and phenotype was not significant. FMD peaks in midlife with varying effects of gender on age at onset and phenotype. The data gives some support to 'lumping' FMD as a unitary disorder but also highlights the value in 'splitting' into individual phenotypes where relevant.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.034 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".