Prevalence of Acute-Onset Subtypes in Pediatric Obsessive-Compulsive Disorder
Bibliographic record
Abstract
BACKGROUND: Pediatric obsessive-compulsive disorder (OCD) is a common, debilitating illness. When childhood OCD symptom onset is described as acute and severe, diagnostic criteria for pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS) and pediatric acute-onset neuropsychiatric syndrome (PANS) should be considered. However, the frequency and differentiating features of these putative syndromes within pediatric OCD remain poorly understood. OBJECTIVES: To determine the prevalence and characteristics of those meeting PANDAS and/or PANS criteria within pediatric OCD, as determined by parent report and clinician interview. METHODS: Consecutive youth presenting to a subspecialty pediatric OCD clinic were rigorously assessed through the Anxiety Disorders Interview Schedule for DSM-IV, the Children's Yale-Brown Obsessive-Compulsive Scale, and through self- and parent-report measures, including a medical questionnaire. Strict diagnostic criteria for PANDAS and PANS were applied to determine prevalence rates, and comparative analyses were performed between subgroups. RESULTS: Among 136 youth with a lifetime OCD diagnosis, 5% (n = 7; 95% adjusted Wald interval: 1%-10%) met proposed criteria for PANDAS and/or PANS, of whom two met PANDAS criteria, four met PANS criteria, and one met criteria for both. Those in the PANDAS/PANS subgroup were more likely to have autoimmune illness, less likely to report symmetry factor symptoms, and had greater OCD-related family impairment during their worst OCD episode. CONCLUSION: A small yet significant percentage of pediatric OCD outpatients met criteria for PANDAS and/or PANS, justifying routine screening and attention to related characteristics during assessment and management. Longitudinal studies of these putative subtypes are warranted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".