Major Depression with ADHD: In Children and Adolescents.
Bibliographic record
Abstract
The objective of this paper is to review recent studies on comorbidity and treatment of major depression (MD) and attention deficit/hyperactivity disorder (ADHD) in children and adolescents. Both ADHD and MD are commonly associated with other DSM-IV Axis I psychiatric disorders. ADHD is more commonly associated with oppositional defiant disorder and conduct disorder in children and adolescents. The literature on comorbidities of MD and ADHD suggests that when these two disorders occur together, they bring their own unique profiles, often including a number of other psychiatric disorders and severe symptoms. The guidelines for the use of first-line ADHD medications (psychostimulants and atomoxetine) and the use of antidepressants in patients with MD comorbid with ADHD (with and without psychostimulants) will also be reviewed. Recommendations for the sequencing of these medications in patients with comorbid MD and ADHD and other disorders (anxiety disorders, oppositional defiant disorder, conduct disorder) will also be made. The concept of "goodness of fit" as it applies to medication choices will also be outlined. Some antidepressants, such as imipramine, desipramine, and bupropion have been effective in treating major depression, anxiety disorders, and ADHD in adults. Tricyclic antidepressants have not been as effective in treating MD in children and adolescents; however, they can be used to treat adults with ADHD and MD. Some of the SSRIs are proven to be effective and safe in children and adolescents and can be considered in patients with comorbid MD and ADHD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".