Cross‐prevalence of migraine and bipolar disorder
Bibliographic record
Abstract
OBJECTIVE: In two related studies, we explored the prevalence of migraine and its associated clinical characteristics in patients with bipolar disorder (BD) as well as psychiatric morbidity in patients treated for migraine. METHOD: The first study included 323 subjects with BD type I (BD I) or BD type II (BD II), diagnosed using the Schedule for Affective Disorders and Schizophrenia, Lifetime version (SADS-L) format, or the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID). Migraine history was assessed by means of a structured questionnaire. In a second sample of 102 migraine patients, we investigated current and lifetime psychiatric morbidity using the SADS-L. Statistical analyses were conducted using nonparametric analysis and log-linear models. RESULTS: A total of 24.5% of BD patients had comorbid migraine; those with BD II had a higher prevalence (34.8%) compared to BD I (19.1%) (p < 0.005). BD patients with comorbid migraine had significantly higher rates of suicidal behaviour, social phobia, panic disorder, generalized anxiety disorder, and obsessive-compulsive disorder (all p < 0.05). In the sample of migraine patients, 34.3% had a current psychiatric diagnosis, and 73.5% had a lifetime psychiatric diagnosis. The prevalence of BD I was 4.9%, and 7.8% for BD II. DISCUSSION: Migraine is prevalent within the BD population, particularly among BD II subjects. It is associated with an increased risk of suicidal behaviour and comorbid anxiety disorders. Conversely, migraine sufferers have high rates of current and lifetime psychopathology. A greater understanding of this comorbidity may contribute to our knowledge of the underlying mechanisms of BD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".