Effects of Repetitive Transcranial Magnetic Stimulation (rTMS) on Cannabis Use and Cognitive Outcomes in Schizophrenia
Bibliographic record
Abstract
Effects of Repetitive Transcranial Magnetic Stimulation (rTMS) on Cannabis Use and Cognitive Outcomes in Schizophrenia Karolina Bidzinski nee KozakDoctor of Philosophy 2021 Institute of Medical Science University of Toronto ABSTRACTRationale: Schizophrenia is a debilitating psychiatric disorder, with poor functional outcomes. Problematic cannabis use among the schizophrenia population is high, with 26% diagnosed with comorbid cannabis use disorder (CUD), which negatively impacts psychosocial functioning. These patients also have greater difficulty quitting cannabis, which may reflect putative deficits in the prefrontal cortex. To date, there are still no established evidence-based treatments for this comorbidity. Aims: Primary: Determine effects of high frequency (20 Hz) repetitive transcranial magnetic stimulation (rTMS) on cannabis use outcomes in outpatients with schizophrenia and CUD. Secondary: Examine effects of active vs. sham rTMS on cannabis craving/withdrawal, psychiatric symptoms, and cognitive functioning. Hypotheses: Primary: Active vs. sham rTMS will result in significantly greater reductions of cannabis use and cannabis abstinences rates. Secondary: Active vs. sham rTMS will result in significantly greater reductions in cannabis craving/withdrawal symptoms, and positive and negative symptoms of schizophrenia, and greater improvements in cognition. Methods: A preliminary double-blind, sham-controlled randomized trial. A total of N=24 subjects were enrolled, and n=19 participants were randomized to receive either active (n=9) or sham (n=10) high frequency rTMS 5x/week for 4 weeks, combined with weekly behavioural support sessions. Cannabis use and symptomatology were monitored weekly through self-report and urine toxicology. A cognitive/neurophysiological battery was administered at pre (Baseline) and post (Day 28). Results: Although no significant differences in cannabis use from Baseline to Day 28 between active and sham treatment were found, contrast estimates indicated greater reductions in cannabis use in the active group (GPD: Estimate=0.33, p=0.207). A trend toward significantly greater reduction in craving score (MCQ Factor 3) over time was found in active vs. sham (Estimate=3.92, p=0.064). Significant reductions in PANSS positive (Estimate=2.42, p=0.018) and total (Estimate=5.03, p=0.019) symptoms over time were found in active vs. sham groups. Significant improvement in Continuous Performance Test (e.g., sustained attention) over time was found in active vs. sham groups (Estimate=6.58, p=0.048). rTMS was safe and well-tolerated, with a high retention rate of 17/19 (90%) outpatients completing the study. Conclusions: Our preliminary findings support the notion that rTMS is a safe and potentially effective treatment for comorbid CUD and schizophrenia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".