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Record W4280556342 · doi:10.1002/brb3.2606

Prognosis of rapid onset functional tic‐like behaviors: Prospective follow‐up over 6 months

2022· article· en· W4280556342 on OpenAlexaff
Megan Howlett, Davide Martino, Christelle Nilles, Tamara Pringsheim

Bibliographic record

VenueBrain and Behavior · 2022
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsHotchkiss Brain InstituteCentre for Addiction and Mental HealthUniversity of Calgary
Fundersnot available
KeywordsTicsProspective cohort studyTourette syndromeDepression (economics)PsychologyAnxietyCohortInternal medicinePsychiatryMedicinePediatrics

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The prognosis of rapid onset functional tic-like behaviors (FTLBs) is unknown. This prospective cohort study describes the course and treatment of rapid onset FTLBs in adolescents (n = 20) and adults (n = 9) previously reported in two case series. METHODS: Yale Global Tic Severity Scale (YGTSS) scores were compared between first clinical presentation and 6-month follow-up assessment. All treatments used for FTLBs and any psychiatric comorbidities were recorded. RESULTS: In adolescents with FTLBs, motor tics, vocal tics, total tics, impairment, and global scores on the YGTSS significantly improved at 6 months, with a mean decrease in the YGTSS global score of 31.9 points, 95% confidence interval (CI) 15.4, 48.4, p = .0005. In adults with FTLBs, only impairment and global scores significantly improved, with a mean decrease in the YGTSS global score of 19.6 points, 95% CI -3.2, 42.3, p = .04. Selective serotonin reuptake inhibitors (SSRIs) and cognitive behavioral therapy (CBT) for anxiety and depression were the most used treatment in both age groups. CONCLUSIONS: This prospective study suggests that adolescents have a better prognosis than adults with FTLBs. Management of comorbidities with SSRIs and CBT seems effective.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.016
GPT teacher head0.286
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2022
Admission routes1
Has abstractyes

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