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Record W4292314164 · doi:10.3724/sp.j.1329.2021.06003

Effect of High Frequency Repetitive Transcranial Magnetic Stimulation on Depression after Cerebral Infarction

2021· article· en· W4292314164 on OpenAlexaboutno aff
Linlin JIANG, Lingchuan NIU, Yule WANG, Baotong YANG, Hao LI, Jiani LI

Bibliographic record

VenueRehabilitation Medicine · 2021
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTranscranial magnetic stimulationMedicineStimulationHamdMontreal Cognitive AssessmentBrain stimulationDeep transcranial magnetic stimulationAnesthesiaCerebral infarctionDepression (economics)ParoxetinePsychologyPhysical medicine and rehabilitationPhysical therapyAudiologyCardiologyAntidepressantInternal medicineCognitionPsychiatryAnxietyHippocampusCognitive impairment

Abstract

fetched live from OpenAlex

<sec><title>Objective</title> To explore the effect of high-frequency repetitive transcranial magnetic stimulation (rTMS) on depression, cognitive function and activities of daily living in patients with depression after cerebral infarction. </sec><sec><title>Methods</title> A total of 50 patients with depression after cerebral infarction from the departments of neurology and rehabilitation of the Second Affiliated Hospital of Chongqing Medical University from July 2018 to February 2020, which were randomly divided into the control group and the observation group, with 25 cases in each group. All of the patients received conventional drug therapy, rehabilitation training, and paroxetine antidepressant treatment. On this basis, the control group was given sham stimulation, the coil of magnetic stimulation was placed at 90 degrees perpendicular to the scalp, the stimulation frequency was 10.0 Hz, the stimulation intensity was 80%-90% resting motor threshold (RMT), and the stimulation intensity was adjusted from low to high according to the patients tolerance, two seconds per stimulus, 20 seconds interval, total pulses 1 200, once a day, five days a week, continous treatment for six weeks. The observation group was given high-frequency rTMS treatment, the stimulation site was the left dorsolateral prefrontal cortex (DLPFC), the center point of the coil was tangent to the patients scalp surface, and the treatment parameters and time were the same as those in the control group. Before treatment and after treatment for six weeks, the Montreal cognitive assessment scale (MoCA) was used to evaluate the overall cognitive function of patients; the Hamilton depression scale (HAMD) was used to evaluate the depression of patients; the modified Barthel index (MBI) was used to evaluate the activities of daily living of patients; the auditory event-related potential P300 was used to evaluate cognitive function and the adverse reactions of the two groups were compared. </sec><sec><title>Results</title> There were no significant differences in MoCA, HAMD, MBI scores and P300 between the two groups before treatment (<italic>P</italic>>0.05). Compared with before treatment, MoCA scores, subitem scores of MoCA (such as visuospatial/executive function, attention/calculation) and MBI score of both groups after treatment for six weeks were significantly higher (<italic>P</italic><0.05), HAMD score and P300 latency of both groups were significantly lower, the difference was statistically significant (<italic>P</italic><0.05). Compared with the control group, the MoCA scores and subitem scores of MoCA (such as attention/calculation and delayed memory) of the observation group were significantly higher (<italic>P</italic><0.05), and HAMD score and P300 latency were significantly lower, the difference was statistically significant (<italic>P</italic><0.05). There were no significant differences in MBI score and occurrence of adverse events between the two groups (<italic>P</italic>>0.05). </sec><sec><title>Conclusion</title> High frequency rTMS can effectively improve the depressive state and cognitive function of patients with post-stroke depression, which is worthy of clinical application. </sec>

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.278
Teacher spread0.270 · 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 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

Citations4
Published2021
Admission routes1
Has abstractyes

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