Course of illness following prospectively observed mania or hypomania in individuals presenting with unipolar depression
Bibliographic record
Abstract
OBJECTIVES: In a well-defined sample, we sought to determine which clinical variables, some of potential nosological relevance, influence subsequent course following prospectively observed initial episodes of hypomania or mania (H/M). METHODS: We identified 108 individuals in the National Institute of Mental Health Collaborative Depression Study diagnosed with unipolar major depression at intake who subsequently developed H/M. We assessed time to repeat H/M based on whether one had been started on an antidepressant or electroconvulsive therapy within eight weeks of developing H/M, had longer episodes, or had a family history of bipolar disorder. RESULTS: Modeling age of onset, treatment-associated H/M, family history of bipolar disorder, duration of index H/M episode, and psychosis in Cox regression analysis, family history of bipolar disorder (n=21) was strongly associated with repeat episodes of H/M [hazard ratio (HR)=2.01, 95% confidence interval (CI): 1.06-3.83, p=0.03]. Those with treatment-associated episodes (n=12) were less likely to experience subsequent episodes of H/M, although this was not significant in the multivariate model (HR=0.25, 95% CI: 0.06-1.05, p=0.06). These individuals also had a later age of onset for affective illness and were more likely to be depressed. Duration of illness with a temporal resolution of one week, psychosis, and age of onset were not associated with time to repeat H/M episode. CONCLUSIONS: A family history of bipolar disorder influences the course of illness, even after an initial H/M episode. In this select sample, treatment-associated H/M did not appear to convey the same risk for a course of illness characterized by recurrent H/M episodes.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".