Bibliographic record
Abstract
There is no greater controversy in child and adolescent psychiatry than that related to the diagnosis, treatment, and increasing prevalence of childhood-onset bipolar disorder. In a recent article ominously entitled The Healthcare Crisis of Childhood Onset Bipolar Illness, Post and Kowatch1 note a substantial incidence, an extraordinary delay to first treatment, and worse outcomes for childhood-onset, compared with adult-onset, bipolar disorder. Classic bipolar illness, as described by Kraepelin2 and currently reflected in the DSM-IV-TR3 criteria, is characterized by discrete episodes of mania and depression. However, in 2001, the National Institute of Mental Health Roundtable on prepubertal Bipolar Disorder4 agreed on 2 different phenotypes in children: and broad. Children with the narrow phenotype have the classic symptoms of episodes of mania and depression, although many of these children experience rapid cycling of their mood states and fail to meet the 4- to 7-day criteria for mania, thereby qualifying for a diagnosis of bipolar disorder not otherwise specified (NOS). Children with the broad phenotype present with irritability, mood lability, temper outbursts, hyperactivity, and poor concentration in a nonepisodic illness pattern. To complicate matters, these children frequently fulfill criteria for attention-deficit hyperactivity disorder (ADHD) and can be conceptualized as having ADHD plus affective instability. Other comorbidities are frequently present, further clouding the diagnostic picture. Two speakers at the November 2006 meeting of the Canadian Academy of Child and Adolescent Psychiatry addressed this controversy. Rakesh Jain5 proposed a diagnostic approach that first screens for sensitive symptoms (that is, irritable mood, distractibility, accelerated speech, and increased energy) and then looks for the specific symptoms (that is, elation, grandiosity, flight of ideas, and decreased need for sleep). Gabrielle Carlson6 presented a historic review of diagnostic criteria, noting that the hyperactive child syndrome, a 1960s precursor of the current DSM-IV-TR criteria for ADHD, included criteria of irritability, explosiveness, and sleep problems. She opined that, over the last 30 to 40 years, the criteria for ADHD have been narrowing and the criteria for bipolar disorder have been expanding, which explains the increased use of the diagnosis of bipolar disorder NOS. She argued that children suffering from mania do not grow up to have classic bipolar disorder, although Biederman's group7 appears to have a different view. Further, she cited Lapalme,8 who showed that, although children of parents with bipolar disorder have a 5.4% risk of developing bipolar disorder, they have a 52% risk of developing a wide variety of other mental disorders. Therefore, family history in and of itself does not help clarify the diagnostic uncertainties. To complicate the picture, Thompson,9 working with an older group of patients, found no prodromal features that clearly distinguished between patients who went on to develop bipolar disorder and those who developed schizophrenia. With so much diagnostic uncertainty, clinicians are increasingly faced with difficult treatment decisions. Children with the presenting symptoms of ADHD are frequently started on stimulant medications. When there is no response, or prominent mood symptoms are part of the clinical presentation, bipolar disorder is frequently considered, which leads to treatment options of mood stabilizers and (or) atypical antipsychotics-treatments with significant side effect profiles. When used, at least in adult patients, these medications may be prescribed for years, or even a lifetime. Danielyan and Kowatch10 have recently produced the most succinct and comprehensive treatment review to date. They note a dramatic increase in the use of medication to treat bipolar disorder in children and conclude that atypical antipsychotics may be more effective than mood stabilizers as first-line 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 | 0.014 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.014 | 0.029 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".