Lifetime bipolar disorder comorbidity and related clinical characteristics in patients with primary obsessive compulsive disorder: a report from the International College of Obsessive–Compulsive Spectrum Disorders (ICOCS)
Bibliographic record
Abstract
INTRODUCTION: Bipolar disorder (BD) and obsessive compulsive disorder (OCD) are prevalent, comorbid, and disabling conditions, often characterized by early onset and chronic course. When comorbid, OCD and BD can determine a more pernicious course of illness, posing therapeutic challenges for clinicians. Available reports on prevalence and clinical characteristics of comorbidity between BD and OCD showed mixed results, likely depending on the primary diagnosis of analyzed samples. METHODS: We assessed prevalence and clinical characteristics of BD comorbidity in a large international sample of patients with primary OCD (n = 401), through the International College of Obsessive-Compulsive Spectrum Disorders (ICOCS) snapshot database, by comparing OCD subjects with vs without BD comorbidity. RESULTS: Among primary OCD patients, 6.2% showed comorbidity with BD. OCD patients with vs without BD comorbidity more frequently had a previous hospitalization (p < 0.001) and current augmentation therapies (p < 0.001). They also showed greater severity of OCD (p < 0.001), as measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). CONCLUSION: These findings from a large international sample indicate that approximately 1 out of 16 patients with primary OCD may additionally have BD comorbidity along with other specific clinical characteristics, including more frequent previous hospitalizations, more complex therapeutic regimens, and a greater severity of OCD. Prospective international studies are needed to confirm our findings.
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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 | 0.001 |
| 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 | 0.000 | 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".