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Record W2367915008

Effect of Transcranial Magnetic Stimulation in combination with nimodipine on vascular dementia after cerebral infarction

2012· article· en· W2367915008 on OpenAlexaboutno aff
Ruipeng Wu

Bibliographic record

VenueNingxia Medical Journal · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsNimodipineMedicineTranscranial magnetic stimulationVascular dementiaCerebral infarctionAnesthesiaDementiaInfarctionBrain infarctionStimulationIschemiaInternal medicineMyocardial infarction
DOInot available

Abstract

fetched live from OpenAlex

Objective To investigate the effect of Transcranial Magnetic Stimulation(TMS) in combination with nimodipine on vascular dementia after cerebral infarction.Methods 114 patients with vascular dementia after cerebral infarction were randomly assigned to the control group(n=35),nimodipine group(n=40) and nimodipine combined TMS group(n=39).Each patient was given conventional drugs therapy.The control group was only given conventional drugs.Nimodipine group was added nimodipine tablets(30mg,qd,four weeks).TMS group was added low frequency electromagenetic therapy.Nimodipine in combination with TMS therapy group received TMS treatment for 30 minutes(two times a day,for 28 days).The three groups were assessed with mini-mental state examination(MMSE),Montreal Cognitive Assessment Scale(MoCA) and Hasegawa Dementia scale(HDS-R) before and after treatment.Results After four weeks,MMSE scores,MoCA scores and HDS-R scores of nimodipine combined with TMS therapy increased compared with the other two groups(P0.05).The total effective rate was 87.18%,and curative powers was superior to using nimodipine alone or conventional drugs therapy(P0.05).Conclusion Comprehensive treatment of nimodipine in combination with TMS therapy could improve clinical symptoms of patients with VD.

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 score0.075
Threshold uncertainty score0.888

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)0.0010.000

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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
Published2012
Admission routes1
Has abstractyes

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