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The clinical study about levetiracetam on cognitive function and emotional influence in the patients with partial epilepsy

2014· article· en· W3029353040 on OpenAlexaboutno aff
张建磊, 李郭飞, 常娜, 王朝辉, 刘大建, 贺维亚

Bibliographic record

VenueChin J Postgrad Med · 2014
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsLevetiracetamCarbamazepineEpilepsyMedicineCognitionMontreal Cognitive AssessmentMoodPsychologyAnesthesiaPediatricsPsychiatryCognitive impairment

Abstract

fetched live from OpenAlex

Objective To investigate the clinical influence about levetiracetam on cognitive function and emotional influence in the patients with partial epilepsy.Methods A total of 62 patients with partial epilepsy were divided into carbamazepine group (30 cases) and levetiracetam group (32 cases) by random digits table method,carbamazepine group was treated by carbamazepine while levetiracetam group was treated by levetiracetam.The patients were assessed before treatment and 4,8,12,16 weeks after treatment by the Montreal cognitive assessment scale (MoCA),self rating anxiety scale (SAS) and self rating depression scale (SDS).Results There was no significant difference in MoCA score between two groups before treatment and 4 weeks after treatment (P > 0.05).MoCA score at 8,12,16 weeks after treatment in levetiracetam group was better than that in carbamazepine group [(22.6 ± 2.1) scores vs.(20.8 ± 2.6) scores,(23.5±2.7) scoresvs.(21.3± 2.8) scores,(24.6±4.7) scoresvs.(21.2±3.0) scores],the difference was statistically significant (P < 0.05).There was no significant difference between SAS score,SDS score between two groups before and after treatment (P > 0.05).Conclusion In the process of treating the patients with partial epilepsy by drug,levetiracetam is superior to carbamazepine on the improvement of cognitive function,but the mood improvement is not obvious. Key words: Levetiracetam;  Carbamazepine;  Epilepsy;  Cognitive function;  Emotions

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)0.001
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.028
GPT teacher head0.344
Teacher spread0.316 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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