Assessment and Management of Concurrent Substance Use in Patients Receiving Repetitive Transcranial Magnetic Stimulation for Depressive, Obsessive-Compulsive, Psychotic, and Trauma-Related Disorders: A Delphi Consensus Study and Guideline
Bibliographic record
Abstract
OBJECTIVE: Limited data are available to inform clinicians on how to manage concurrent substance use in the context of repetitive transcranial magnetic stimulation (rTMS) for the treatment of depressive, obsessive-compulsive, psychotic, or trauma-related disorders. The authors convened an international panel of 24 rTMS experts, representative of different geographic regions and subspecialities, and created a consensus guideline for clinicians and researchers on approaches to concurrent substance use in patients receiving rTMS as treatment for primary psychiatric disorders. METHODS: A Delphi method survey and expert opinion elicited over consecutive rounds of surveys were used, with feedback and discussion after each round. Recommendation statements were established upon very high (≥80%) agreement. RESULTS: Three rounds of surveys and feedback were sufficient to reach a consensus for most topics; where consensus could not be reached, the panel discussed limitations in the current evidence base. Informed by a synthesis of the literature and practice-based evidence, the expert panel provides several consensus recommendations on the topics of screening, monitoring, risk assessment, and mitigation associated with various degrees of substance use, and specific considerations for alcohol, cannabis, stimulants, and opioids. Instead of excluding all people who use substances, a nuanced approach should be taken based on an assessment of risk factors for clinical instability and severity of use. The most important safety risk with substance use is the presence of intoxication or withdrawal states, with the most data supporting seizure risk in unstable alcohol or nonmedical stimulant use. Although there is no evidence of reduced rTMS efficacy for a psychiatric disorder in the presence of concurrent substance use, the lack of data in this area warrants caution. CONCLUSIONS: These recommendations can be readily implemented clinically and provide a framework for future research. In patients receiving rTMS for a primary psychiatric disorder, assessment and management of co-occurring substance use is complex, requiring greater attention, standardization, and further study.
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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 | 0.100 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".