MétaCan
Menu
Back to cohort

Low frequency repetitive transcranial magnetic stimulation in the diagnosis and treatment of cranial dystonia

2008· article· en· W3031647676 on OpenAlexaboutno aff
Ning-jiang Liu

Bibliographic record

VenueChin J Neurol · 2008
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsTranscranial magnetic stimulationDystoniaSpasmodic TorticollisMedicineTorticollisPsychologyAnesthesiaPhysical medicine and rehabilitationStimulationSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Objective To study the therapeutic effects of low frequency repetitive transcranial magnetic stimulation(rTMS)in cranial dystonia.Methods Twenty cranial dystoina patients were treated with low frequency rTMS.Their motor threshold,cortical silent period(CSP)were evaluated before and after the rTMS and after 1,2,6 months as well as the spares and Toronto Western Spasmodic Torticollis Rating Scale(TWSTRS)to evaluate the effects of rTMS in the treatment of cranial dvstonia.Results The patients scored(23.5±14.0)significantly lower after l and 2 months(17.6 ±14.3,18.5±14.2,t=2.632,2.149.both P<0.05).But there was an increasing tendeney of the score after 2 months.The 2-month efficient rate of low-frequency rTMS Was 60%(12/20),yet the long-term effect of rTMS was still to be studied.There was a very significant improvment of relaxed(46.5%±7.3%vs49.9%±9.2%,t=-3.235.P<0.05)and active threshold(40.2%±5.9%/)5 43.9%±8.8%,t=-2.339,P<0.05),prolongation of CSP((96.1±24.5)ms vs(121.6±27.7)ms,t=-7.223,P=0.000).Conclusion The low frequency rTMS is efficient to relieve the clinical symptoms of cranial dystonia. Key words: Torticollis;  Magnetics; Treatment outcome

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueChin J NeurolSame topicNeurological disorders and treatmentsFrench-language works237,207