Cognitive preservation and antidepressant efficacy of magnetic seizure therapy in adolescents with treatment resistant major depressive disorder in China: A randomized controlled trial
Bibliographic record
Abstract
Objective To compare the antidepressant efficacy, cognitive impact, and safety profile of magnetic seizure therapy (MST) vs. modified electroconvulsive therapy (MECT) in Chinese adolescents with treatment-resistant major depressive disorder (MDD). Methods This single-center, evaluator-blinded, prospective randomized controlled trial enrolled 120 adolescents aged 13-18 years diagnosed with treatment-resistant MDD. Participants were randomly assigned to either the MST group or the MECT group (n = 60 per group). The primary outcome was improvement in depressive symptoms measured by the Beck Depression Inventory-II (BDI-II) score. Secondary outcomes included changes in cognitive function assessed by the Montreal Cognitive Assessment (MoCA), time to reorientation, and adverse event incidence per CTCAE 5.0 criteria. Results The reduction of depressive symptoms on the BDI-II was significantly greater in the MECT group (51.8%) compared to the MST group (46.5%) ( P < 0.001), although clinical response rates were similar (90.0% vs 91.1%). The MST group showed significant improvement in MoCA total score, whereas the MECT group demonstrated a slight decline ( P < 0.001). MST was associated with greater cognitive preservation (+0.96 vs 0.36 MoCA score), fewer adverse events (28.9% vs 64.0%, P < 0.001), and faster reorientation (6.9 ± 1.8 min vs 18.7 ± 6.8 min, P < 0.001) compared to MECT. Conclusion MST exhibited comparable antidepressant efficacy to MECT while offering superior cognitive protection and safety in adolescents with treatment-resistant MDD. These findings suggest MST may be a preferred treatment option balancing symptom relief with neurodevelopmental preservation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".