Comorbidity in pediatric bipolar disorder: An unmet challenge in need of treatment studies
Bibliographic record
Abstract
In this edition of Acta Psychiatrica Scandinavica, Fahrendorff and colleagues report findings from their systematic review examining psychiatric comorbidity in pediatric bipolar disorder (1).The scientific literature regarding pediatric bipolar disorder has increased significantly over the past two decades, and this manuscript provides a helpful synopsis regarding psychiatric comorbidity in children and adolescents with bipolar disorder.Before turning to the details of the current study, it is important to provide context from the international epidemiology of psychiatric comorbidity in adult bipolar disorder.A World Mental Health Survey Initiative study, which included 61,392 community adults from 11 countries in the Americas, Asia, and Europe, examined psychiatric comorbidity among individuals with bipolar spectrum disorders (2).The most common comorbidities were anxiety disorders, behavior disorders, and substance use disorders.Comorbidity patterns for anxiety disorders and substance use disorder showed substantial international consistency, although rates of comorbid behavior disorders were much higher in the U.S. and New Zealand than in most other countries.Over three-quarters of adults with bipolar disorder had at least one psychiatric comorbidity, and nearly half had three or more comorbidities.This is remarkable for a number of reasons, including the fact that the sample was community based, rather than clinical, and the fact that these data are not constrained to one country or one sample, but rather reflective of a highly consistent pattern of multi-comorbidity in bipolar disorder.Discourse regarding psychiatric comorbidity in pediatric bipolar disorder often focuses on differential diagnosis in general, and the issue of overlapping diagnostic criteria in particular (3).This relates especially to attention deficit hyperactivity disorder (ADHD) and diagnoses characterized by severe irritability (e.g.disruptive mood dysregulation disorder [DMDD], oppositional defiant disorder [ODD]).Interwoven within this discourse are the themes of international differences in diagnostic practices and concerns around so-called overdiagnosis (i.e.false positives).While the aforementioned findings regarding comorbidity in adult bipolar disorder do not resolve debates around differential diagnosis or international differences in diagnostic approaches, they do establish that multi-comorbidity is a reality
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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 | 0.024 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".