Accelerated intermittent theta burst as a substitute for patients needing electroconvulsive therapy during the COVID-19 pandemic: study protocol for an open-label clinical trial
Bibliographic record
Abstract
Abstract Background Treatment resistant depression (TRD) is one of the leading causes of disability in Canada and is associated with significant societal costs. Repetitive transcranial magnetic stimulation (rTMS) is an approved, safe, and well-tolerated intervention for TRD. In the setting of the COVID-19 pandemic, reducing the number of visits to the clinic is a potential approach to significantly minimize exposure and transmission risks to patients. This can be accomplished by administering multiple treatment sessions in a single day, using an rTMS protocol known as accelerated intermittent theta burst stimulation (aiTBS). The objective of this novel study is to assess the feasibility, acceptance and clinical outcomes of a practical high-dose aiTBS protocol, including tapering treatments and symptom-based relapse prevention treatments, in patients with unipolar depression previously responsive to electroconvulsive therapy (ECT) or patients warranting ECT due to symptom severity. Methods All patients with unipolar depression referred to the brain stimulation service at the Centre for Addiction and Mental Health (CAMH) who warrant ECT will be offered screening to assess for eligibility to enroll in this trial. This open label, single group trial consists of 3 phases. In the acute treatment phase, treatment will occur 8 times daily for 5 days a week, until symptom remission is achieved or a maximum of 10 days of treatment. In the tapering phase, treatments will be reduced to 2 treatment days per week for 2 weeks, followed by 1 treatment day per week for 2 weeks. Patients will then enter the symptom-based relapse prevention phase including virtual check-ins and a treatment schedule based on symptom level. Remission, response and change in scores on several clinical measures from baseline to the end of the acute, tapering and relapse prevention phases represent the clinical outcomes of interest. Discussion Findings from this novel clinical trial may provide support for the use of aiTBS, including tapering treatments and symptom-based relapse prevention treatments, as a safe and effective alternative intervention for patients needing ECT during the COVID-19 pandemic. Trial registration Clinicaltrials.gov: NCT04384965
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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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.040 | 0.009 |
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".