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Record W4412638837 · doi:10.1097/yco.0000000000001029

Scaling up a success story: how do we achieve universal access to transcranial magnetic stimulation?

2025· review· en· W4412638837 on OpenAlexaff
Jonathan Downar

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2025
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsQueen's UniversityUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsTranscranial magnetic stimulationTolerabilityNeuroplasticityMedicinePhysical medicine and rehabilitationPsychologyNeurosciencePsychiatryStimulationInternal medicineAdverse effect

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Over one billion people suffer from psychiatric and/or neurological disorders for which transcranial magnetic stimulation (TMS) has shown efficacy. Achieving widespread TMS access will require major improvements to cost and convenience. A key figure of merit for a given TMS protocol concerns not its remission rate or tolerability, but simply its treatment time per remission (TTPR). RECENT FINDINGS: Outcomes for conventional bilateral TMS protocols imply a TTPR of more than 100 h - incompatible with widespread access. However, briefer accelerated and/or theta-burst protocols may improve TTPR to less than 20 h. Personalization strategies that improve remission rates sometime improve TTPR, depending on associated cost-penalties of time or complexity. A potentially groundbreaking new strategy to improve TTPR involves pharmacological augmentation of neuroplasticity, using agents such as D -cycloserine. Plasticity-augmentation may improve TTPR by improving remission rates, and by reducing the number of required sessions. Recent literature suggests that TTPR values of under 5 h per remission may be achievable via neuroplasticity augmentation. SUMMARY: The most recent plasticity-augmented TMS protocols may approach or exceed cost-parity with pharmacotherapy, in terms of reducing the prevalence of depression. With the health economics of TMS improving steadily, a pathway to universal access may be within reach.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.122
GPT teacher head0.419
Teacher spread0.297 · 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 designOther design
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

Citations2
Published2025
Admission routes1
Has abstractyes

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