The clinical trajectory of emerging bipolar disorder among the high-risk offspring of bipolar parents: current understanding and future considerations
Bibliographic record
Abstract
BACKGROUND: Relatively little is known about the onset of bipolar disorder, yet the early illness course is already associated with significant morbidity and mortality. Therefore, characterizing the bipolar illness trajectory is key to risk prediction and early intervention advancement. MAIN BODY: In this narrative review, we discuss key findings from prospective longitudinal studies of the high-risk offspring of bipolar parents and related meta-analyses that inform us about the clinical trajectory of emerging bipolar disorder. Challenges such as phenotypic and etiologic heterogeneity and the non-specificity of early symptoms and syndromes are highlighted. Implications of the findings for both research and clinical practice are discussed. CONCLUSION: Bipolar disorder in young people at familial risk does not typically onset with a hypomanic or manic episode. Rather the first activated episode is often preceded by years of impairing psychopathological states that vary over development and across emerging bipolar subtype. Taking heterogeneity into account and adopting a more comprehensive approach to diagnosis seems necessary to advance earlier identification and our understanding of the onset of bipolar disorder.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".