Tics Moderate Sertraline, but Not Cognitive-Behavior Therapy Response in Pediatric Obsessive-Compulsive Disorder Patients Who Do Not Respond to Cognitive-Behavior Therapy
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to investigate whether the presence of tic disorder is negatively associated with sertraline (SRT) outcomes, but not with continued cognitive-behavioral therapy (CBT), in a sample of youth who were unresponsive to an initial full course of CBT. METHODS: In the Nordic Long-Term OCD Study, children and adolescents with OCD who were rated as nonresponders to 14 weeks of open-label CBT were randomized to continued CBT (n=28) or SRT treatment (n=22) for an additional 16 weeks of treatment. We investigated whether the presence or absence of comorbid tic disorder moderated treatment outcomes on the Children's Yale-Brown Obsessive Compulsive Scale (CY-BOCS). RESULTS: Twelve out of 50 (24.0%) participants were diagnosed with comorbid tic disorder, with 7 receiving continued CBT and 5 receiving SRT, respectively. In patients without tic disorder, results showed no significant between-group differences on average CY-BOCS scores. However, in patients with comorbid tic disorder, those who received SRT had significantly lower average CY-BOCS scores than those who received continued CBT. CONCLUSIONS: Children and adolescents with OCD and comorbid tic disorder, who are nonresponders to an initial 14 week course of CBT, may benefit more from a serotonin reuptake inhibitor (SRI) than from continued CBT.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".