Atomoxetine Does Not Improve Complex Attention in Idiopathic Parkinson’s Disease Patients with Cognitive Deficits: A Meta-Analysis
Bibliographic record
Abstract
Objectives. To evaluate the effects of atomoxetine on complex attention and other neurocognitive domains in idiopathic Parkinson’s disease (PD).Methods. Interventional trials reporting changes in complex attention and other neurocognitive functions (Diagnostic and Statistical Manual of Mental Disorders-5) following administration of atomoxetine for at least 8 weeks in adults with idiopathic PD were included. Effect sizes (Cohen’sd), the standardized mean difference in the scores of each cognitive domain, were compared using a random-effects model (MetaXL version 5.3).Results. Three studies were included in the final analysis. For a change in complex attention in PD with mild cognitive impairment (MCI), the estimated effect size was small and nonsignificant (0.16 (95% CI: −0.09, 0.42),n = 42). For changes in executive function, perceptual-motor function, language, social cognition, and learning and memory, the estimated effect sizes were small and medium, but nonsignificant. A deteriorative trend in executive function was observed after atomoxetine treatment in PD with MCI. For a change in global cognitive function in PD without MCI, the estimated effect size was large and significant.Conclusion. In idiopathic PD with MCI, atomoxetine does not improve complex attention. Also, a deteriorative trend in the executive function was noted.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.024 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".