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Record W4401055569 · doi:10.1016/j.eclinm.2024.102760

Antidepressant class and concurrent rTMS outcomes in major depressive disorder: a systematic review and meta-analysis

2024· review· en· W4401055569 on OpenAlexafffund
A. Moin Zaidi, Rafeya Shami, Isabella J. Sewell, Xingshan Cao, Peter Giacobbe, Jennifer S. Rabin, Maged Goubran, Clement Hamani, Walter Swardfager, Benjamin Davidson, Nir Lipsman, Sean M. Nestor

Bibliographic record

VenueEClinicalMedicine · 2024
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsHealth Sciences CentreToronto Rehabilitation InstituteUniversity of TorontoSunnybrook Health Science Centre
FundersSunnybrook Foundation
KeywordsTranscranial magnetic stimulationMajor depressive disorderMedicineAntidepressantDepression (economics)Meta-analysisPsychiatryAdjunctive treatmentStimulationInternal medicineMoodAnxiety

Abstract

fetched live from OpenAlex

Background Repetitive transcranial magnetic stimulation (rTMS) is frequently used as an adjunctive treatment with antidepressants for depression. We aimed to evaluate the clinical efficacy and safety of antidepressant classes when administered concurrently with rTMS for the management of major depressive disorder (MDD). Methods In this systematic review and meta-analysis, MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from inception to April 12th 2024 for terms relating to medication, depression, and rTMS and appraised by 2 independent screeners. All randomized clinical trials that prospectively evaluated a specific antidepressant adjunctively with sham rTMS as a control in MDD were included. The study was registered with PROSPERO (CRD42023418435). The primary outcome measure assessed symptomatic improvement measured by formal depression scales. We used a random-effects model with pooled Standardized Mean Differences (SMDs) and log odds ratios (OR). All studies were assessed for their methodological quality and bias using the Cochrane Collaboration Risk of Bias tool version 2 (RoB2). Findings 14 articles from 5376 identified studies were included in the systematic review and meta-analysis. There was only sufficient trial data to evaluate the effects of rTMS and combination therapy with selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors (SNRIs). Across studies, 848 participants (mean [SD] age:41.1 [18.7] years for SSRIs, 51.8 [3.8] years for SNRIs) prospectively examined the efficacy of antidepressant medication with rTMS. Combining rTMS with SSRIs led to significantly lower depression scores, (SMD [CI] of −0.65 [−0.98, −0.31], p = 0.0002, I 2 = 66.1%), higher response (OR = 0.97 [0.50, 1.44], p < 0.0001, I 2 = 25.33%) and remission rates (OR = 1.04 [0.55, 1.52], p < 0.0001, I 2 = 0.00%) than medication with sham rTMS. No additive benefit was found for SNRIs with rTMS (SMD of 0.10 [−0.14, 0.34], p = 0.42, I 2 = 0.00%; OR = 0.12 [−0.39, 0.62], p = 0.64, I 2 = 0.00%; OR = −0.31 [−0.90, 0.28], p = 0.86, I 2 = 39.9%). The overall risk of bias for the included studies ranged from low to high, with 1 study having a high risk of bias. Interpretation The combination of rTMS with SSRIs, but not SNRIs, significantly reduced depression severity, increasing response and remission rates. Some analyses demonstrated high heterogeneity, which was influenced by an SSRI trial with a high effect size. Overall, these results suggest that not all antidepressant combination therapies are alike, and SSRIs should be considered when initiating rTMS. Funding Donald T. Stuss Young Investigator Research Innovation Award from the Sandra Black Centre for Brain Resilience & Recovery and the Harquail Centre for Neuromodulation through the Sunnybrook Foundation.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0160.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.187
GPT teacher head0.451
Teacher spread0.264 · 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.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations17
Published2024
Admission routes2
Has abstractyes

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