The Significance of At-Risk or Prodromal Symptoms for Bipolar I Disorder in Children and Adolescents
Bibliographic record
Abstract
While in the early identification and intervention of psychosis-specific instruments and risk criteria have been generated and validated, research into indicated preventive strategies for bipolar I disorder (BD I) has only recently gained momentum. As the first signs of BD I often start before adulthood, such efforts are especially important in the vulnerable pediatric population. Data are summarized regarding the presence and nature of potentially prodromal, that is, subsyndromal, symptoms prior to BD I, defined by first-episode mania, focusing on pediatric patients. Research indicates the possibility of early identification of youth at clinical high risk for BD. Support for this proposition comes from retrospective studies of BD I patients, as well as prospective studies of community samples, offspring of BD I subjects, youth with depressive disorders, and patients at high risk for psychosis or with bipolar spectrum disorders without lifetime history of mania. These data provide essential insight into potential signs and symptoms that may enable presyndromal identification of BD I in youth. However, except for offspring studies, broader prospective approaches that focus on youth at clinical high risk for BD I and on developing specific interviews and (or) rating scales and risk criteria are mostly missing, or in their early stage. More work is needed to determine valid and sufficiently specific clinical high-risk criteria, to distinguish risk factors, endophenotypes, and comorbidities from prodromal symptomatology, and to develop phase-specific interventions that titrate the risk of intervention to the risk of transition to mania and to functional impairment or distress. Moreover, studies are needed that determine potential differences in prodromal symptoms and trajectories between children, adolescents, and adults, and the best phase-specific interventions.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".