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Record W2074217332 · doi:10.1097/yco.0b013e3283366657

Repetitive transcranial magnetic stimulation for refractory symptoms in schizophrenia

2010· review· en· W2074217332 on OpenAlexafffund
Daniel M. Blumberger, Paul B. Fitzgerald, Benoit H. Mulsant, Zafiris J. Daskalakis

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2010
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsCentre for Addiction and Mental HealthMuscular Dystrophy CanadaUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsTranscranial magnetic stimulationRefractory (planetary science)Schizophrenia (object-oriented programming)NeuroscienceMedicineStimulationDeep transcranial magnetic stimulationPhysical medicine and rehabilitationPsychiatryPsychologyMaterials science

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Schizophrenia is an illness associated with a substantial degree of treatment resistance and suboptimal therapeutic response. In recent years, novel brain stimulation technologies have been identified as potential treatments for schizophrenia and related disorders. Several published studies have assessed the use of repetitive transcranial magnetic stimulation (rTMS) in patients with schizophrenia. RECENT FINDINGS: Most published studies have focused on the use of low-frequency rTMS to treat refractory auditory hallucinations. These studies support the efficacy of stimulation over the temporoparietal cortex. Several other studies have assessed high-frequency stimulation of the prefrontal cortex in the treatment of negative symptoms. Novel protocols to treat auditory hallucinations have been piloted and case reports are emerging on the use of maintenance rTMS to treat auditory hallucinations. SUMMARY: Overall, rTMS studies have demonstrated some promise in the treatment of schizophrenia. However, more research is required to delineate the role of this technique in clinical practice and to explore novel stimulation techniques that may ultimately lead to improved therapeutic efficacy.

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 score0.984
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.091
GPT teacher head0.400
Teacher spread0.309 · 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

Citations27
Published2010
Admission routes2
Has abstractyes

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