Differences between unipolar mania and bipolar‐I disorder: Evidence from nine epidemiological studies
Bibliographic record
Abstract
OBJECTIVES: Although clinical evidence suggests important differences between unipolar mania and bipolar-I disorder (BP-I), epidemiological data are limited. Combining data from nine population-based studies, we compared subjects with mania (M) or mania with mild depression (Md) to those with BP-I with both manic and depressive episodes with respect to demographic and clinical characteristics in order to highlight differences. METHODS: Participants were compared for gender, age, age at onset of mania, psychiatric comorbidity, temperament, and family history of mental disorders. Generalized linear mixed models with adjustment for sex and age as well as for each study source were applied. Analyses were performed for the pooled adult and adolescent samples, separately. RESULTS: Within the included cohorts, 109 adults and 195 adolescents were diagnosed with M/Md and 323 adults and 182 adolescents with BP-I. In both adult and adolescent samples, there was a male preponderance in M/Md, whereas lifetime generalized anxiety and/panic disorders and suicide attempts were less common in M/Md than in BP-I. Furthermore, adults with mania revealed bulimia/binge eating and drug use disorders less frequently than those with BP-I. CONCLUSIONS: The significant differences found in gender and comorbidity between mania and BP-I suggest that unipolar mania, despite its low prevalence, should be established as a separate diagnosis both for clinical and research purposes. In clinical settings, the rarer occurrence of suicide attempts, anxiety, and drug use disorders among individuals with unipolar mania may facilitate successful treatment of the disorder and lead to a more favorable course than that of BP-I disorder.
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 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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".