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Repetitive Transcranial Magnetic Stimulation as Maintenance Treatment of Depression

2025· article· en· W4411329778 on OpenAlexafffund
Yoshihiro Noda, Masataka Wada, Yu Mimura, Keita Taniguchi, Ryosuke Tarumi, Sotaro Moriyama, Naohiro Arai, Sakiko Tsugawa, Kevin E. Thorpe, Zafiris J. Daskalakis, Hiroyuki Uchida, Masaru Mimura, Daniel M. Blumberger, Shinichiro Nakajima

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsCentre for Addiction and Mental HealthHospital for Sick ChildrenPublic Health OntarioUniversity of Toronto
FundersTeijin PharmaCanadian Institutes of Health ResearchKeio UniversityMagVenture
KeywordsDepression (economics)Transcranial magnetic stimulationVenlafaxineRandomized controlled trialAdverse effectMedicineRating scaleMajor depressive disorderBrain stimulationRelapse preventionAntidepressantTreatment-resistant depressionInternal medicinePsychologyPhysical therapyMoodPsychiatryStimulation

Abstract

fetched live from OpenAlex

Importance: Depression relapse poses significant medical and economic challenges. Repetitive transcranial magnetic stimulation (rTMS) as maintenance treatment may prevent relapse of treatment-resistant depression (TRD). Objective: To compare the effectiveness between low-frequency rTMS and lithium in preventing TRD relapse. Design, Setting, and Participants: This randomized clinical trial was conducted from September 1, 2018, to May 31, 2023, at Keio University Hospital and Shinjuku-Yoyogi Mental Lab Clinic, Tokyo, Japan, among 75 participants with TRD aged 18 years or older with moderate-to-severe depressive symptoms despite at least 2 adequate antidepressant treatments who subsequently responded to an acute course of bilateral rTMS. Interventions: Participants were randomly assigned at a 1:1 ratio to receive right dorsolateral prefrontal 1-Hz rTMS (24 weekly sessions; 120% of the resting motor threshold, 900 pulses in 15 minutes) or 24-week maintenance treatment with lithium pharmacotherapy. Participants were maintained on the same venlafaxine dose (150-225 mg/d) as the acute-phase dose. Main Outcomes and Measures: The primary outcome was the between-group difference in baseline-adjusted Montgomery-Åsberg Depression Rating Scale (MADRS) scores (range, 0-60, where 0 indicates no symptoms and 60 indicates most severe symptoms) at week 24, which was analyzed using a linear mixed-effects model for repeated measures in an intention-to-treat sample. The secondary outcome was the time to relapse (defined as a MADRS score ≥22), which was analyzed using Kaplan-Meier survival curves. Adverse events were also compared between groups. Results: Among the 75 participants, 38 were assigned to the rTMS group (mean [SD] age, 44.1 [11.7] years; 21 male participants [55.3%]; baseline mean [SD] MADRS score, 8.9 [4.7]), and 37 were assigned to the lithium group (mean [SD] age, 44.1 [11.1] years; 19 male participants [51.4%]; baseline mean [SD] MADRS score, 7.9 [4.5]). There was no significant between-group difference in the primary outcome at week 24 (0.3 points [95% CI, -2.7 to 3.3 points]; P = .84). Survival analysis showed no meaningful between-group difference in relapse rates. During the 24-week maintenance phase, there were 7 patients who relapsed in each group. There was a higher number of adverse events among participants in the lithium group (n = 16) than in the rTMS group (n = 3; odds ratio, 7.10 [95% CI, 1.84-27.49]; P = .005). Conclusions and Relevance: In this randomized clinical trial, low-frequency rTMS of the right prefrontal cortex as maintenance treatment showed comparable efficacy, as well as better safety and tolerance, compared with lithium. Maintenance low-frequency rTMS could be a promising relapse prevention strategy for patients with TRD. Trial Registration: Japan Registry of Clinical Trials: jRCTs032180188.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.321
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations9
Published2025
Admission routes2
Has abstractyes

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