A Case-Control Study of Bipolar Depression, Compared with Unipolar Depression, in a Regional Hospital in Hong Kong
Bibliographic record
Abstract
OBJECTIVE: To determine the characteristics of diagnostic conversion from unipolar depression to bipolar depression in psychiatric outpatients, and to compare the profiles of the 2 groups of patients. METHOD: This is a case-control study in which outpatients newly diagnosed with unipolar depression were reviewed. Outpatients who had polarity conversion to bipolar depression were recruited as subjects and control subjects were matched. The diagnostic validity was enhanced by clinical interview, review of case records by an independent specialist psychiatrist, and administration of the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Axis I Disorders. Multivariate conditional logistic regression was carried out to identify the predictors of bipolar switch. RESULTS: Eighty-eight subjects among those who maintained regular outpatient clinic follow-up (n = 823) showed bipolar switch during the period under study. The incidence of polarity conversion was 10.7%. Bipolar switch was associated with family history of bipolar affective disorder, use of 3 or more different types of antidepressants in the first 5 years after presentation, an earlier age at presentation of depressive symptoms of less than 37 years, and males. CONCLUSIONS: Change in diagnostic polarity is not uncommon in Chinese psychiatric outpatients initially presenting with unipolar depression. They share some common risk factors as identified in Western studies. These can be helpful to clinicians as guidance for identification of patients with depression at high risk for a bipolar course.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".