P.005 Lisdexamfetamine precipitated pathological gambling
Bibliographic record
Abstract
Background: Lisdexamfetamine has not heretofore been reported to cause pathological gambling. Such a case is presented. Methods: A middle-aged woman, without past interest in gambling, gaming, or risk taking behavior, with childhood history of attention deficit hyperactivity disorder presented with difficulty focusing and concentrating. Lisdexamfetamine was started at 20 mg daily and gradually escalated due to lack of efficacy. At 70 mg daily, she began binging on sweets and gambling all day, every day at nearby riverboats, which she had never frequented previously. Upon reduction to 60 mg daily, the gambling resolved. Ritalin 20 mg every morning and 50 mg every afternoon was used without gambling reoccurrence. Results: Mental Status Examination: Alert, cooperative and oriented x 3 with good eye contact. Euthymic, without mania, thoughts logical and goal directed. Conclusions: Enhanced dopamine in the nucleus accumbens may induce hedonic activities including gambling, binging on sweets, or sexual activity (Moore et al. 2014). Lisdexamfetamine has been described to induce mania, and pathological gambling may have been an isolated manifestation of early mania. In those who have recently begun lisdexamfetamine, query should be made regarding change in gambling behavior and in those who are pathologically gambling, investigation should be entertained as to whether they are taking lisdexamfetamine.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".