LONG-TERM ATOMOXETINE ADMINISTRATION FOR YOUNG CHILDREN WITH ATTENTION-DEFICIT/HYPERACTIVITY DISORDER
Bibliographic record
Abstract
Objectives: The purpose of this presentation is to report on the efficacy and tolerability of long-term atomoxetine treatment among young children with attentiondeficit/ hyperactivity disorder (ADHD). Methods: Data from 6- and 7-year old children (n=192) enrolled in similarly designed clinical trials that met DSM-IV criteria for ADHD were pooled. The children had a minimum of 12 months of atomoxetine treatment and 97 (51%) receive treatment for >24 months. The mean modal dose (SD) of atomoxetine was 1.55mg/kg/day (0.32). The primary efficacy outcome measure was the mean change from baseline to endpoint in the ADHD Rating Scale-IV (ADHD RS). The Conners' Parent Rating Scale-Revised: Short Form (CPRS-R:S) was a secondary efficacy measure. Results: Significant mean treatment effects from baseline to endpoint for ADHD RS and CPRS-R:S scores were observed (P<.001). The effectiveness of atomoxetine treatment for children was maintained over long-term treatment as demonstrated by ADHD RS total and T-scores. Adverse events were clinically minor and transient, and only 1.6% of children discontinued due to adverse events. There were no clinically meaningful changes in laboratory tests. Also, further follow-up and analyses are ongoing. Conclusion: Long-term atomoxetine treatment appears to be well-tolerated and effective in young children with 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".