Prospective <scp>follow‐up</scp> study of youth and adults with onset of functional tic‐like behaviours during the <scp>COVID</scp>‐19 pandemic
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Very little is known about the long-term prognosis of patients with functional tic-like behaviours (FTLBs). We sought to characterize the trajectory of symptom severity over a 12-month period. METHODS: Patients with FTLBs were included in our prospective longitudinal child and adult clinical tic disorder registries at the University of Calgary. Patients were prospectively evaluated 6 and 12 months after their first clinical visit. Tic inventories and severity were measured with the Yale Global Tic Severity Scale (YGTSS). RESULTS: Eighty-three youths and adults with FTLBs were evaluated prospectively until April 2023. Mean YGTSS total tic severity scores were high at baseline, with a mean score of 29.8 points (95% confidence interval [CI] = 27.6-32.1). Fifty-eight participants were reevaluated at 6 months, and 32 participants were reevaluated at 12 months. The YGTSS total tic severity score decreased significantly from the first clinical visit to 6 months (raw mean difference = 8.9 points, 95% CI = 5.1-12.7, p < 0.0001), and from 6 to 12 months (raw mean difference = 6.4 points, 95% CI = 0.8-12.0, p = 0.01). Multivariable linear regression demonstrated that tic severity at initial presentation and the presence of other functional neurological symptoms were associated with higher YGTSS total tic scores at 6 months, whereas younger age at baseline, receiving cognitive behavioural therapy for anxiety and/or depression, and prescription of selective serotonin reuptake inhibitors were associated with lower YGTSS total tic scores at 6 months. CONCLUSIONS: We observed a meaningful improvement in tic severity scores in youth and adults with FTLBs over a period of 6-12 months.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".