Current Status, Diagnosis, and Treatment Recommendation for Tic Disorders in China
Bibliographic record
Abstract
Tic disorders (TD) are a group of neuropsychiatric disorders with childhood-onset characterized by tics, i.e. repetitive, sudden, and involuntary movements or vocalizations; and Tourette syndrome (TS) is the most severe form of TD. Their clinical manifestations are diverse; and are often associated with various psychopathological and/or behavioral comorbidities, including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, depression, and sleep disorders. Individual severity and response to treatment are highly variable, and there are some refractory cases, which are less responsive to conventional TD treatment. TD/TS is also common in the Chinese pediatric population. To help improve the understanding of TD for pediatricians and other health professionals, and to improve its diagnosis and treatment in China, the Chinese Child Neurology Society (CCNS) has developed an Expert Consensus on Diagnosis and Treatment of TD in China, which is based on our clinical experience and the availability therapeutic avenues. It is focused on clinical diagnosis and evaluation of TD and its comorbidities, psychological and educational intervention, nonpharmacological therapy, pharmacological treatment, including traditional Chinese medicine and acupuncture, as well as prognosis in children with TD in China. A summary of the current status of TD and up-to-date diagnosis and treatment recommendations for TD in China is presented here.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".