Childhood treatment with psychotropic medication and development of comorbid medical conditions in adolescent‐onset bipolar disorder
Bibliographic record
Abstract
OBJECTIVE: This study aims to investigate the association between early treatment with psychotropic medications and the development of medical comorbidities in pediatric patients who develop bipolar disorder (BD). METHODS: Data from the South Carolina Medicaid program covering all medical services and medication prescriptions between January 1996 and December 2005 were used to determine the association between childhood exposure to psychotropic medications (i.e., psychostimulants, antidepressants, and antipsychotics) and the diagnosis of select comorbid medical conditions in 1841 children and adolescents diagnosed with Diagnostic and Statistical Manual IV defined BD. RESULTS: In separate regressions controlling for all psychotropic medications prescribed and all comorbid medical conditions diagnosed prior to the BD, hypertension and cardiovascular disorders were more likely in those prescribed second generation antipsychotics or psychostimulants, whereas obesity/overweight was more likely in those taking serotonin norepinephrine reuptake inhibitor/heterocyclic antidepressants, and asthma was more likely in those taking selective serotonin reuptake inhibitors. CONCLUSION: Childhood cardiometabolic events appear to be systematically associated with specific classes of psychotropic medications, but no innate, developmental sequencing of cardiometabolic abnormalities was apparent before early adolescence in patients subsequently diagnosed and treated for BD.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".